Method, Program, and Apparatus for Detecting Small Intestinal Bacterial Overgrowth

FIELD

This invention lies in the field of medicine and healthcare and in particular to digestive and gastrointestinal health. The invention specifically relates to detection, diagnosis, and/or measurement of small intestinal bacterial overgrowth (SIBO).

BACKGROUND

Accurate diagnosis of small intestinal bacterial overgrowth (SIBO) has been a challenge for clinicians and researchers. The accepted standard for SIBO diagnosis is jejunal aspirate, which involves endoscopic retrieval of a fluid sample from the proximal end of the small bowel and subsequent analysis of bacterial content. Aspirate is prone to inaccuracies - false negatives are common as endoscopic tubes cannot reach distal areas of the small bowel, and false positives can occur due to contamination of the sample by flora native to the mouth or oesophagus (Ghoshal et al., 2011). The invasive nature of the jejunal aspirate test is unpleasant for patients.

An alternative diagnostic tool currently in use is the breath test, which measures the H2 or CH4 percentage in the breath. Breath testing has low sensitivity, around 40%, however is less invasive than aspirate and so is more commonly used (Paterson et al. 2017). Massey et al. (2021) has suggested that both diagnostic tools lack specificity for SIBO, instead differentiating only between healthy and unhealthy states.

A further complication is that SIBO is commonly a comorbidity for other gastrointestinal diseases, including Irritable Bowel Syndrome (IBS), which could affect the specificity of diagnostics. A positive outcome of this is that many papers have investigated the co-incidence of IBS and SIBO and, while reported prevalence of SIBO in IBS patients can vary widely between studies, this provides a large data set linking SIBO to a more easily diagnosed GI disease. It is desirable to develop a SIBO diagnostic method that compares favourably in terms of prevalence among IBS patients to prevalence among IBS patients in the literature.

References:

Ghoshal, U. How to Interpret Hydrogen Breath tests. J Neurogastroenterol Motil. 2011 July; 17(3) Paterson, W., Camilleri, M., Simren, M., Boeckxstaens, G., Vanner, S. Breath Testing Consensus Guidelines for SIBO: RES IPSA LOCQUITOR. Journal of Gastroenterology. 2017 December Massey, B., Wald, A. Small Intestinal Bacterial Overgrowth Syndrome: A Guide for the Appropriate Use of Breath testing. Digestive Diseases and Sciences. 2021; 66:338-347. SUMMARY

Embodiments include a method for detecting small intestinal bacterial overgrowth, SIBO, the method comprising: obtaining data representing a time series of readings from gas sensor hardware housed within an ingestible capsule device orally ingested by a subject, the time series of readings being taken during exposure of the gas sensor hardware to a gas mixture at the ingestible capsule device during passage of the ingestible capsule device through a gastrointestinal tract of the subject, each reading representing a composition of the gas mixture at the location of the ingestible capsule device in the gastrointestinal tract of the subject; detecting an ileocecal junction transition indicator among the obtained data, and based on a timing of the detected ileocecal junction transition indicator, detecting a fermentation indicator among the obtained data representing readings preceding the timing of the detected ileocecal junction indicator among the time series of readings; in response to detecting the fermentation indicator, determining presence of SIBO in the subject and generating a report indicating the determined presence of SIBO in the subject.

Optionally, embodiments further comprise: based on the detected fermentation indicator, measuring a level of fermentation activity detected in the small bowel of the subject, and including the measured level in the generated report.

Optionally, the gas sensor hardware comprises a VOC gas sensor configured to generate readings sensitive to a concentration of volatile organic compounds in the gas mixture at the location of the ingestible capsule device; wherein detecting the ileocecal junction transition indicator and detecting the fermentation indicator is by detecting a characteristic feature among a plurality of consecutive readings, the characteristic feature comprising a first, earlier, increase in concentration of volatile organic compounds in the gas mixture at the location of the ingestible capsule device, and a second, later, increase in concentration of volatile organic compounds in the gas mixture at the location of the ingestible capsule device; the first, earlier, increase being the detected fermentation indicator, and the second, later, increase being the ileocecal junction transition indicator.

Optionally, the ingestible capsule device comprises a single gas sensor, the single gas sensor being the VOC gas sensor.

Optionally, the characteristic feature is an earlier portion of consecutive readings preceding a gradient change and having an earlier portion gradient, the earlier portion being the fermentation indicator, and a later portion of consecutive readings proceeding the gradient change and having a later portion gradient, the later portion being the ileocecal transition junction indicator, the earlier portion and the later portion being separated from one another by the gradient change; and the method further comprising determining that the characteristic feature is a diagnostic indicator of SIBO based upon a comparison of the earlier portion with the later portion.

Optionally, determining that the characteristic feature is a diagnostic indicator of SIBO comprises calculating a ratio of: an earlier change being a change in value of readings from an earliest to a latest reading in the earlier portion, to a later change, being a change in value of readings from an earliest to a latest reading in the later portion; and comparing the calculated ratio with a predefined threshold configured to distinguish positive or negative SIBO diagnosis.

Optionally, the gradient change is detected by calculating a first derivative being a rate of change of the values among the plurality of consecutive readings on a rolling basis, and calculating a second derivative being a rate of change of the first derivative, and detecting when the second derivative exceeds a predefined threshold.

Optionally, the gradient change is detected by a pattern matching algorithm.

Optionally the gas sensor hardware comprises two or more separate gas sensors including: a first gas sensor being a VOC gas sensor configured to generate readings sensitive to a concentration of volatile organic compounds in the gas mixture at the location of the ingestible capsule device; and a second gas sensor being one from among: an H2 gas sensor configured to generate readings sensitive specifically to a concentration of H2 in the gas mixture at the location of the ingestible capsule device, a CH4 gas sensor configured to generate readings sensitive specifically to a concentration of CH4 in the gas mixture at the location of the ingestible capsule device, and a further VOC gas sensor configured to generate readings sensitive to a concentration of volatile organic compounds in the gas mixture at the location of the ingestible capsule device; wherein the ileocecal junction transition indicator is detected in the readings of the first gas sensor, and wherein the fermentation indicator is detected in the readings of the second gas sensor.

Optionally, the gas sensor hardware further comprises a TCD gas sensor, and wherein the method includes detecting a further ileocecal junction transition indicator in data representing a time series of readings from the TCD gas sensor, and wherein the timing of the detected ileocecal junction transition indicator is compared with the timing of the detected further ileocecal junction transition indicator to set an upper bound on timing of the fermentation indicator.

Optionally, one or more from among: the fermentation indicator, the ileocecal junction transition indicator, and the characteristic feature, is detected by a convolutional neural network trained to detect presence of the said one or more from among the fermentation indicator, the ileocecal junction transition indicator, and characteristic feature, in a visual or geometric representation of the readings of the gas sensor hardware.

Optionally, the detected ileocecal junction indicator represents an increase in detected concentration of volatile organic compounds at the ingestible capsule device, the increase exceeding a predefined threshold configured to indicate transition of the ingestible capsule device across the ileocecal junction, or the increase rising to a concentration of volatile organic compounds predefined to indicate transition of the ingestible capsule device across the ileocecal junction.

Optionally, the ingestible capsule device further comprises processor hardware, memory hardware, and a wireless data transmitter, and the processor hardware in cooperation with the memory hardware is configured to perform the method during passage of the ingestible capsule device through the gastrointestinal tract of the subject, and to transmit data comprising the generated report to a receiver device via the wireless data transmitter.

Optionally, the ingestible capsule device further comprises a wireless data transmitter, and the wireless data transmitter is configured to transmit the time series of readings from the gas sensor hardware to a receiver device, the method being executed by processor hardware and memory hardware at the receiver device or at a computing device in data communication with the receiver device.

Optionally, the method includes ingesting the ingestible capsule device by the subject, and/or providing the ingestible capsule device to the subject for ingestion.

Embodiments include a method comprising: performing a method of an embodiment on plural distinct occasions over a period of time during which a patient is receiving a treatment for SIBO, the patient being the subject orally ingesting an ingestible capsule device on each distinct occasion, including, based on the detected fermentation indicator, measuring a level of fermentation activity caused by SIBO in the subject, and including the measured level in the generated report; and, based on the generated reports from the plural distinct occasions, assessing patient response to the treatment for SIBO.

Embodiments include an apparatus comprising memory hardware and processor hardware, the memory hardware storing processing instructions which, when executed by the processor hardware, cause the processor hardware to perform a method of an embodiment. Optionally the memory hardware and processor hardware are housed within the ingestible capsule device, the ingestible capsule device further comprises a wireless transmitter, and the processor hardware is configured to perform the method during passage of the ingestible capsule device through the gastrointestinal tract of the subject, and further to diagnosing SIBO in the subject, to transmit data indicating the diagnosis to a receiver device via the wireless transmitter.

Embodiments include an ingestible capsule device comprising: an ingestible indigestible biocompatible housing; and, within the housing: a power source; sensor hardware including gas sensor hardware; processor hardware; memory hardware; and a wireless data transmitter; the memory hardware storing processing instructions which, when executed by the processor hardware, cause the processor hardware to perform a process comprising: obtaining data representing a time series of readings from the gas sensor hardware, the ingestible capsule device having been orally ingested by a subject, the time series of readings being taken during exposure of the gas sensor hardware to a gas mixture at the ingestible capsule device during passage of the ingestible capsule device through a gastrointestinal tract of the subject, each reading representing a composition of the gas mixture at the location of the ingestible capsule device in the gastrointestinal tract of the subject; detecting an ileocecal junction transition indicator among the obtained data, and based on a timing of the detected ileocecal junction transition indicator, detecting a fermentation indicator among the obtained data representing readings preceding the timing of the detected ileocecal junction indicator among the time series of readings; in response to detecting the fermentation indicator, determining presence of SIBO in the subject and generating a report indicating the determined presence of SIBO in the subject.

Embodiments include a computer program which, when executed by a processor, causes the processor to perform a process comprising: obtaining data representing a time series of readings from gas sensor hardware housed within an ingestible capsule device orally ingested by a subject, the time series of readings being taken during exposure of the gas sensor hardware to a gas mixture at the ingestible capsule device during passage of the ingestible capsule device through a gastrointestinal tract of the subject, each reading representing a composition of the gas mixture at the location of the ingestible capsule device in the gastrointestinal tract of the subject; detecting an ileocecal junction transition indicator among the obtained data, and based on a timing of the detected ileocecal junction transition indicator, detecting a fermentation indicator among the obtained data representing readings preceding the timing of the detected ileocecal junction indicator among the time series of readings; in response to detecting the fermentation indicator, determining presence of SIBO in the subject and generating a report indicating the determined presence of SIBO in the subject. Advantageously, embodiments provide a reliable and accurate diagnosis method which relies upon data obtained by ingestion (and excretion) of an ingestible capsule device by a subject. The data obtained from the capsule enables accurate determination of ileocecal junction transition timing such that a closely preceding increase in detected volatile organic compounds in the gas mixture at the capsule, or some other fermentation indicator preceding ileocecal junction transition, is attributable to SIBO. The inventors have identified a technique for detecting SIBO by detecting an ileocecal junction transition indicator in a time series of readings from gas sensor hardware on board an ingestible capsule device, and using the timing of that ileocecal junction transition indicator to detect a fermentation preceding the ileocecal junction transition indicator. Wherein, by virtue of preceding the ileocecal junction transition indicator chronologically, the fermentation indicator can be attributed to activity in the small bowel, and thus determined to have been caused by fermentation in the small bowel.

In a particular example, the inventors have identified a signature in the signal output by a VOC gas sensor housed within an ingestible capsule device that is diagnostic of SIBO: wherein an increase in concentration of sensed volatile organic compounds is divisible into two distinct increases in close succession such that an earlier increase is attributable to SIBO and a later increase is attributable to ICJ transition. The inventors have identified a characteristic of the two distinct increases that is diagnostic of SIBO, wherein trials have shown diagnoses made by said characteristic compare favourably with incidence rates of SIBO expected based on the published literature.

Detailed Description

Embodiments are described below, by way of example, with reference to the accompanying drawings, in which:

Figure 1A illustrates an ingestible capsule device of an embodiment;

Figure IB illustrates an ingestible capsule device of an embodiment;

Figure 1C illustrates a system encompassing an embodiment;

Figure 2 illustrates an ingestible capsule device of an embodiment;

Figure 3 illustrates changing sensitivity to constituent gases with operating temperature;

Figure 4a illustrates a method of an embodiment;

Figure 4b illustrates a SIBO diagnostic method according to an embodiment;

Figure 5a illustrates data obtained from an ingestible capsule device in a trial;

Figure 5b illustrates data obtained from an ingestible capsule device in a trial;

Figure 6 illustrates data obtained from an ingestible capsule device in a trial;

Figure 7 illustrates data obtained from an ingestible capsule device in a trial;

Figure 8 illustrates gas concentrations in a bench-top assessment;

Figure 9 illustrates sensor responses and gas concentrations in a bench-top assessment;

Figure 10 illustrates SIBO diagnostic results of patients in atrial; Figures 11A to 11D illustrate hydrogen concentration in colonic transit split into four quarters for positive and negative SIBO patients according to breath test results;

Figures 12A to 12D illustrate hydrogen concentration in colonic transit split into four quarters for positive and negative SIBO patients according to jejunal aspirate test results;

Figure 13 illustrates a plot of data generated by an embodiment;

Figure 14 illustrates a plot of data generated by an embodiment;

Figure 15 illustrates a plot of data generated by an embodiment;

Figure 16 illustrates a plot of data generated by an embodiment;

Figure 17 illustrates a plot of data generated by an embodiment;

Figure 18 illustrates a plot of data generated by an embodiment.

DETAILED DESCRIPTION

Ingestible Capsule Overview

Figures 1A and IB illustrate an ingestible capsule 10. A system including the ingestible capsule 10 of Figures 1A and IB is illustrated in Figure 1C, during a live phase of the ingestible capsule 10 (i.e. while the ingestible capsule 10 is obtaining readings from within the GI tract of a subject mammal 40).

As shown in Figures 1A and IB the typical capsule 10 consists of a housing such as a gas impermeable shell 11 which has an opening covered by a gas permeable membrane 12. A membrane 111 separates an exposed interior cavity exposed to the environmental gases entering the capsule 10 through the membrane 12 from a sealed-off interior cavity that is not exposed to the environmental gases.

As shown in Figure 1C, the system, in addition to the capsule, further comprises a receiver apparatus 30 which receives data transmitted by the capsule from within the GI tract of the subject mammal during the live phase. Concurrently or subsequently, the receiver apparatus 30 processes the received data and may also upload some or all of the received data to a remote processing apparatus such as a cloud-based service for further processing. The remote computer may be a cloud resource, or may be a standalone computer at a clinician premise at which the subject is a patient, or may be a server (be it cloud-based or otherwise) at a service provider to which the clinician is a subscriber/customer/servicer user.

Optionally, a system may further comprise a remote processing apparatus 20 such as a server forming part of a cloud computing environment or some other distributed processing environment. The remote processing apparatus 20 may be a server provided by or on behalf of a clinical centre at which subject 40 is a patient and taking responsibility for interpreting the results generated by the capsule 10 (i.e. the data transmission payload) and reporting them to the subject 40. Connectivity between the capsule 10 and the receiver apparatus 30 is via the data transmitter on the capsule, which may be part of a wireless transceiver, for example a Bluetooth transceiver, which may operate according to a standard Bluetooth transmission protocol or according to Bluetooth Long Range transmission protocol. Other operable communication technologies include LoRa, wifi and 433 MHz radio.

Internally the capsule 10 includes gas sensor hardware 131, 132, an environmental sensor 14, and processor hardware 151 and memory hardware 152. The processor hardware 151 and memory hardware 152 may be a microcontroller. The processor hardware 151 may be a microprocessor. The memory hardware 152 may be a non-volatile memory and the data stored thereon is accessible by the processor hardware 151. The processor hardware 151 processes data from signals received from the gas sensor hardware and the environmental sensor (and optionally also the reflectometer and accelerometer) and stores the processed data on the memory hardware 152. The processed data, or a portion thereof, is stored on the memory hardware 152 as a data transmission payload ready for transmission to a receiver apparatus 30 by the data transmitter 18.

By way of example, the capsule illustrated in Figure 1C houses, as sensor hardware, an environmental sensor 14 in the form of a temperature sensor 14a and/or a humidity sensor 14b, gas sensors in the form of a TCD gas sensor 131 and a VOC gas sensor 132, an accelerometer 19, and a reflectometer. Embodiments may include any single or combination of those individual sensors. Alternatively or additionally, embodiments may include one or more sensors not illustrated in Figure 1C such as a spectrophotometer, Surface Acoustic Wave sensor, and/or Bulk Acoustic Resonator Arrays.

The environmental sensor 14 may be a temperature sensor 14a or may be a temperature sensor 14a and a humidity sensor 14b. The gas sensors may be a TCD gas sensor 131, a VOC gas sensor 132, or a TCD gas sensor 131 and a VOC gas sensor 132. As illustrated in Figure 2A, the internal electronics may also include a power source 16, for example, silver oxide batteries, an antenna 17, a wireless transceiver 18. The internal electronics may also include a reed switch. Other options for keeping the device switched off (or otherwise not consuming power) during storage include a physical switch pressed via a flexible part of the housing, or a photodetector and coupled field effect transistor that latches the microcontroller on when exposed to light. The internal electronics may further comprise an accelerometer 19 from which accelerometer data (i.e. a signal) is received at the processor hardware 151 for processing and subsequent storage at the memory hardware 152 and transmission by the data transmitter 18.

The gas sensors 131, 132 are less than several mm in dimension each and are sensitive to particular gas constituents including oxygen, hydrogen, carbon dioxide and methane. In fact, the VOC gas sensor 132 may be configured to give sensor side readings and driver or heater side readings. The heater side readings may be used to determine thermal conductivity of a surrounding gas and thereby the heater side readings of the VOC gas sensor are TCD readings. The sensor side readings are used to determine concentrations of volatile organic compounds in the surrounding gases and are VOC readings. The TCD gas sensor 131 may be, for example, a heating element coupled to a thermopile output, with the thermopile temperature, and therefore its output, varying due to energy conducted into the gas at the location of the capsule 10. The TCD gas sensor 131 measures rate of heat diffusion away from the heating element.

As illustrated in Figure 3, the heater side of the VOC gas sensor 132 (operating as a TCD sensor) and the sensor side of the TCD gas sensor 131 have different operating ranges, so TCD readings from the two sensors collectively span a wider range of operating temperatures than either of the sensors individually. Both sensors have heating elements. The TCD gas sensor 131 has a low operating temperature but with a high precision. The heater side of the VOC gas sensor 132 increases the operating range but has a lower precision for TCD readings than the TCD sensor. The larger collective thermal range achieved by the two gas sensors 13 in concert enables better resolution of analytes in the event that the signals from the gas sensors are processed to resolve the analytes. The thermal conductivity of constituent gases in the gas mixture of the GI tract varies with temperature and so by obtaining TCD readings at different operating temperatures the different gases can be resolved from each other. This is leveraged in a gas resolution processing branch, which is to determine identity and concentrations of constituent gases in the gas mixture surrounding the capsule 10. The gas resolution processing may be performed on-board the gas capsule 10, at the receiver apparatus 30, or at a remote processing apparatus . The gas resolution processing is optional depending on the implementation.

The gas sensors 13 are contained in a portion of the capsule 10 sealed from the power source 16 and other electronic components by a membrane 111. Such an arrangement minimises volume of the sensing headspace (i.e. the sealed portion) and minimises risk of a leak caused by a perforated membrane allowing Gl-tract gases from the headspace to reach the power source. However, since the power source may be configured so that exposure to Gl-tract gases does not adversely impact performance, the membrane may be omitted. That is, the membrane 111 is optional. The membrane 111 is permeable by electronic circuitry required to connect the components housed on either side. For example, wiring may pass through the membrane 111 in a sealed manner. The outer surface of the sealed portion of the capsule is composed of a selectively permeable membrane. Selectively permeable in the present context indicates that liquids are not allowed to permeate whereas gases are. The selectivity does not extend to allowing only a subset of gases to permeate. For example, the gas sensors 13 include respective heaters which are driven to heat sensing portions of the respective gas sensors 13 to temperatures at which sensor readings are obtained (i.e. a measurement temperature). The heaters may be driven in pulses so that there is temporal variation in the sensing portion temperature and so that measurement temperatures are obtained for periods sufficient to take readings but without consuming the power that would be required to sustain the measurement temperature continuously.

The gas sensors 13 are calibrated, so that a gas sensor reading can be used to identify the composition and concentration of a gas to which they are exposed. Calibration coefficients are gathered in manufacturing and testing, and are applied to the recorded readings at the processing stage (i.e. by a server such as on the cloud or by an on-board processor 151). Otherwise, this calibration could be performed on the capsule 10, at the receiver apparatus 30, or on any device having access to the calibration coefficients and the recorded readings from the gas sensors 13. Such calibration relates to a gas resolution branch of processing concerned with measuring the concentration of constituent gases in the gas mixture at the capsule 10. Context for the outputs of that branch of processing is provided by a motility branch of processing, which determines (or predicts to within predefined confidence level) a location of the capsule 10 within the GI tract at which said gas mixture is found. In the motility (or location determination) processing branch, some calibration may also be required in seeking to find gastric-duodenal transition indicators, since ingested foodstuffs at different temperatures change the environmental temperature in the stomach, which influences rate of heat diffusion. In the case of gas sensor readings taken after ingestion and before the gastric-duodenal transition (i.e. whilst the capsule 10 is in the stomach), processing of readings may include applying a moderation to TCD readings, from either gas sensor, in order to correct for variations in environmental temperature, based on environmental temperature readings by the temperature sensor 14a. TCD readings are effectively measuring rate of heat loss to surroundings, and so accuracy is improved by measuring the temperature of the surroundings rather than by relying on assumption (i.e. prior knowledge of internal temperature of the subject mammal). However, the processing may rely on assumption, for example, if there is some issue with the temperature sensor readings, or, for example, if the level of accuracy provided by assumption is acceptable in a particular implementation. Gastric temperature may vary based on, for example, ingestion of liquids or foodstuffs by the subject mammal, or physical activity undertaken by the subject mammal 40. Environmental temperature is a term used in this document to refer to the temperature of the environment in which the capsule 10 is located, as distinct from operational temperatures of the gas sensors 13. The sensitivity of the gas sensors 13 to different constituent gases vary according to the operating temperature of the sensors and the processing of the readings includes calibrating (also referred to as moderating or correcting) readings from the gas sensors according to contemporaneous operating temperature and optionally also according to contemporaneous environmental temperature.

It is noted that the motility branch of processing and the gas resolution branch of processing are not independent of one another. Some motility indicators (i.e. features or characteristics of sensor output signals used to determine timing of motility events) may be found in readings of concentration of a single analyte gas in the gas mixture at the capsule, obtained by processing the output of one or more of the gas sensors 13.

In addition to the gas sensors 13 and the temperature sensor 14a, the capsule electronics further include processor hardware 151, memory hardware 152, a power source 16, an antenna 17, a wireless transmitter 18, and optionally a reed switch. The wireless transmitter 18 operates in concert with the antenna 17 to transmit readings from the sensors (collectively referring to the gas sensors 13 and the temperature sensor 14a, and optionally also the accelerometer 19 and reflectometer) to a receiver apparatus 30 for processing thereon or at a remote processing apparatus to which the receiver apparatus is in data communication, or the processor hardware 151 processes the signals received from the sensors to identify motility indicators (or otherwise to extract information from the sensor readings).

The wireless transmitter 18 (also referred to as data transmitter 18) may be provided as part of a wireless transceiver 18. The wireless transceiver 18 includes an antenna 17. Optionally, the wireless transceiver 18 also includes a directional coupler 171. The wireless transceiver 18 may transmit data in accordance with the Bluetooth protocol, the Bluetooth Long Range (Coded-PHY) protocol, the LoRa protocol, the wifi protocol, or using another mode of transmission such as 433 MHz radio wave transmission.

Figure 2A illustrates the antenna 17 and directional coupler 171 as elements of the wireless transmitter 18, since the antenna is the physical means by which the wireless transmitter 18 transmits data to the receiver apparatus 30. The wireless transmitter 18 is also configured to buffer data for transmission. The wireless transmitter 18 may also be configured to encode the data with a code unique to the capsule 10 among a population of like capsules 10.

Interconnections between electronic components in Figure 3 may be via a central bus. This is one example of how power and data may be distributed between components. Other circuitry architecture may be implemented, for example, all connections may be via a microcontroller which coordinates distribution of data and power between components. The sensors (the TCD sensor 131, the VOC sensor 132, the temperature sensor 14a, the accelerometer 19, and the directional coupler 171) take readings under the instruction of a microcontroller, powered by the power source 16, and transfer the readings (or results of processing the readings) to the wireless transmitter 18 for transmission to the receiver apparatus via the antenna 17. For example, the processor hardware 151 and memory hardware 152 may collectively be referred to as a microcontroller.

The dimension of the capsule may be less than 11.2 mm in diameter and less than 27.8 mm in length. The housing of the capsule 10 may be made of indigestible polymer, which is biocompatible. The housing may be smooth and non-sticky to allow its passage in the shortest possible time and to minimise risk of any capsule retention. Optionally, the ingestible capsule may be less than 32.3mm in length and less than 11.6mm in diameter.

The antenna 17 may be in series with a directional coupler 171. The directional coupler 171 and the antenna 17 are configured as a reflectometer. The reflectometer measures the amplitude of reflected signals by means of a diode detector. The measurements of the reflectometer are readings that represent electromagnetic properties of material in the vicinity of the capsule. The reflectometer readings provide a basis for differentiating between gaseous, liquid, and solid matter at the location of the capsule in the GI tract. Readings of the reflectometer enable the antenna 17 and directional coupler 171 to operate in cooperation as an environmental dielectric sensor.

The readings of the ingestible capsule 10, which include one or more from among readings from: the temperature sensor 14a, the heater side 132b of the VOC gas sensor 132, the sensor side 132a of the VOC gas sensor 132, and the TCD gas sensor 131, may also include readings of the reflectometer. Hence, change in capsule location within the GI tract causes a change in reflectometer readings, and therefore provide an indicator that a transition event between two sections of the GI tract has occurred.

The ingestible capsule 10 may further comprise an accelerometer 19. The accelerometer 19 may be a tri -axial accelerometer. A rate of change of angular position or orientation of the capsule 10 is somewhat dependent upon location within the GI tract, and therefore accelerometer readings provide an indicator that a transition event between two sections of the GI tract has occurred. The accelerometer readings may measure angular acceleration about three axes of rotation, wherein the three axes of rotation may be mutually orthogonal.

Processor Hardware, Memory Hardware

The processor hardware and memory hardware may be separate components or may be part of the same single integrated chip. The processor hardware and memory hardware are selected according to the particular implementation requirements of each design or version of the capsule 10, noting that constraints such as power consumption, cost, data throughput, size of data transmission payload, etc, will vary between designs or versions. The processor hardware may be a processor or a plurality of interconnected processors.

Pairing

The wireless data transmitter may be a Bluetooth transmitter, a wifi transmitter, a radio transmitter, or another form of wireless data transmitter. A radio transmitter may be configured to transmit in the 433 MHz band. In any case, the wireless data transmitter may be provided as part of a wireless data transceiver. For example, the wireless data transceiver may receive signals at least in performing pairing or any other form of coupling to a recipient device 30. The capsule 10 may be configured to enter into a wireless pairing or coupling mode immediately upon initiation (i.e. first power-on), wherein a subject or another user is instructed (via written instructions or via an application running on the recipient device itself) to pair or couple the capsule 10 to the recipient device 30 prior to ingestion of the capsule 10. However, embodiments may be configured such that pairing or coupling is not necessary, for example the capsule 10 may be configured to broadcast data to a recipient device in a data transmission technique that is agnostic to pairing or coupling status, as discussed in more detail below.

Data Transmission Techniques

There are two principal data transmission techniques, which ingestible capsules may be configured to use either or both of, depending on implementation details (i.e. use case). In a post-excretion data transmission technique, signals from the sensors are received at the processor hardware 151 (utilising also the storage capabilities of the memory hardware 152) and processed on-board the capsule 10 in order to identify and record motility indicators (and optionally also other characteristics of the sensor output or sensor readings of interest or groups of sensor readings of interest) and the recorded motility indicators (and optionally also the other characteristics, metrics, and readings or groups of readings of interest, such as peak H2, area under a plot of H2 against time) are stored on the memory hardware 152 as a data transmission payload. Other characteristics and readings or groups of readings of interest may include, for example, maximum or minimum readings from specific sensors or from metrics calculated by combining sensors. The maximum or minimum readings may be local maximum or local minimum readings, wherein local is defined by, for example, predefined timings or motility events determined to have occurred by the capsule 10 itself. A specific example is maximum or minimum H2 concentration, which is a metric calculated from the gas sensor readings by an appropriately calibrated processor hardware. The data transmission payload is transmitted by the wireless transceiver once excretion of the capsule 10 from the GI tract is detected (for example by the temperature sensor 14a signal and/or by the accelerometer 19 signal). Metrics further include peak H2 level or value, timing of peak H2, and total H2 (area under the curve). Such metrics may be calculated by the on-board processor hardware 151 during passage through the GI tract of the subject, and transmitted away from the capsule 10 to a receiver device in post-excretion transmission as part of a report or otherwise.

In the post-excretion data transmission technique, the transmission may be via a Bluetooth transmission mode that is not dependent upon pairing status. That is, for example, if the Bluetooth transceiver is paired to a receiver device then it transmits the data transmission payload to the paired receiver device, and if the Bluetooth transceiver is unpaired then it broadcasts the data transmission payload to a recipient device in the absence of pairing in an inquiry mode (which may be referred to as discovery mode or beacon mode). Bluetooth protocol has an inquiry mode in which a device broadcasts a unique identifier, name and other information. The data transmission payload, or part thereof, may comprise or be included in the said other information. In particular, the data transmission payload may be prioritised or otherwise filtered by the processor hardware 151 so that information deemed particular important such as an indication that excretion has occurred (it is important for clinical reasons to know that the capsule 10 has been excreted) and potentially information such as timing of determined motility events, is transferred away from the capsule 10 in preference to other information. Following the inquiry mode transmission, the transceiver may again attempt to pair, connect, or otherwise couple, with the recipient device, and if successful, to transmit the remainder of the data transmission payload. Of course, said pairing, connecting, or coupling, may have been performed initially pre-ingestion so that postexcretion the Bluetooth transceiver is attempting to re-pair, re-connect, or re-couple, with the receiver device 30. It is noted that the present discussion uses Bluetooth as an example of a transmission protocol, but that the same techniques could be applied to different transmission protocols.

In the event that there is data transmission payload pending transmission away from the capsule 10 after the broadcast of the unique identifier, name, and other information during the Bluetooth inquiry mode, then capsule 10 may be configured to initiate or re-initiate a data communication connection (i.e. a pairing or re-pairing) with a receiver device 30. Upon successful initiation or re-initiation of the communication connection, transmission of the said data transmission payload pending transmission away from the capsule 10 is performed whilst the data communication connection remains active.

The Bluetooth transceiver 18, or any other wireless data transmitter 18, may be configured to automatically re-connect following an initial (i.e. pre-ingestion) connection to a receiver device 30. The receiver device 30 may run an app or web app to guide the subject in terms of how to ingest the capsule 10, to notify the subject that the excretion event has been determined, and optionally also that the data transmission payload has been successfully transmitted to the receiver device 30 and so the capsule 10 may be flushed away. It is noted that the terms pair, connect, and couple, are interchangeable in the present document, each representing the establishment of a wireless connection between two devices for wireless data transfer.

It is noted that data transmission payload may be being transmitted throughout passage of the capsule 10 through the GI tract, dependent upon pairing, coupling, or connection to the receiver device 30. However, confirmation that occurrence of an excretion event has been determined by the capsule is information that is of particular importance since safety of capsule 10 is reliant on the capsule 10 being excreted. Therefore, information representing determination of occurrence of the excretion event (i.e. a report thereof) is prioritised and may be transmitted in a broadcast or inquiry mode, whereas the remaining data transmission payload is transmitted once connection between the wireless data transmitter 18 and the receiver device 30 is established. In Bluetooth inquiry mode, data can be transmitted to the receiver apparatus 30, or to any Bluetooth receiver apparatus within range of the capsule 10, without pairing. The wireless transceiver 18 is operable in a Bluetooth inquiry mode or a Bluetooth long range (Coded-PHY) mode. Capsules 10 may store and transmit among the data transmission payload readings from one or more sensors representing a predefined period either side of the identified motility indicators. For example, gas sensor signals only, or for all sensors. Such readings may be used to add confidence to the identified motility indicators in terms of determining whether or not a motility event has occurred, and/or may provide other information useful in a health or clinical context.

More generally, data transmitted according to the post-excretion data transmission technique may be any of the data transmission payload that has not already been transmitted. For example, the wireless data transmitter 18 may be configured to transmit the data transmission payload to a paired receiver apparatus while still in the GI tract (this transmission is referred to herein as pre-excretion data transmission technique). However, owing to issues such as signal attenuation, noise, power supply issues, temporary pairing failure, or if pairing was never performed in the first place, or for any other reason, some or all of the data transmission payload may be pending transmission at the point of excretion. In that case, the remaining data transmission payload is transmitted according to the postexcretion data transmission technique once excretion is detected. It is noted that down-sampling of the data transmission payload may be performed prior to transmission via the post-excretion data transmission technique. Furthermore it is noted that some elements of the data transmission payload may be prevented from transmission via the post-excretion data transmission technique. For example, since bandwidth, and also time within which to transmit, may be limited, it may be that the motility event indicators and diagnostic indicators themselves are included, but that sensor readings are excluded from the data to be transmitted according to the post-excretion data transmission technique.

In a pre-excretion data transmission technique, the sensor signals are transmitted continuously by the wireless transceiver 18. In the pre-excretion data transmission technique, the process hardware 151 coordinates the receipt of the signals from the sensors and the storage at the memory hardware 152 for transmission by the wireless transceiver 18.

In the example of a Bluetooth wireless transceiver 18, in the pre-excretion transmission technique the transceiver may be operated according to a long-range or coded-PHY Bluetooth transmission procedure, such as BTLE Coded PHY. A signal power enhancement of around lOdB is achievable via BTLE Coded PHY Bluetooth transmission procedure.

During a data transmission phase of the ingestible capsule 10 (i.e. which in the post-excretion data transmission technique is in a short burst post-excretion and in the pre-excretion data transmission technique is continuous while the ingestible capsule 10 is in use, that is, in the GI tract of a subject mammal 40 and obtaining and transmitting readings) the wireless transmitter 18 transmits the readings to a receiver apparatus 30, which may be a dedicated device for receiving and storing the readings (and optionally with a user interface) or may be a multi-function device such as a mobile phone (such as a smart phone). The mobile phone may be running an application which processes some or all of the data transmission payload to generate a motility report or diagnosis of a medical condition based on motility indicators and diagnostic indicators either included in the data transmission payload or derivable therefrom. Alternatively, the application may be configured to transmit the data transmission payload on to a server or another processing apparatus to generate the motility report or diagnosis based on the data transmission payload. The subject mammal need not remain within a specific range of the remote computer 20 during the live phase. Capsules 10 equipped with a Bluetooth transceiver 18 may communicate directly with a smartphone of a user, which obviates any need for a dedicated receiver apparatus (the smartphone taking on the role of receiver apparatus 30). The receiver apparatus 30 (whether a dedicated device or a mobile phone or tablet computer) may process the readings itself or may upload the readings to a remote computer 20 for processing (i.e. identifying motility indicators, determining motility event timings, resolving gas analytes). The upload may be continuous during a live phase of the capsule, or the upload may be after the live phase of the capsule is terminated. The receiver apparatus 30 may also store the readings, so that loss of connectivity between the receiver apparatus 30 and a remote processing apparatus is not critical.

The on-board processor 151 may apply one or more processing or pre-processing steps, as discussed in more detail below. Digitisation of the readings is performed either by the sensors themselves, by the processor 151 or by the wireless transceiver 18. The digitised readings are transmitted via the antenna 17. The readings of the capsule 10 are made at an instant in time and are associated with the instant in time at which they are made. For example, a time stamp may be associated with the readings by the microcontroller 15, the wireless transmitter 18, or at the receiver apparatus 30 or remote computer 20. For example, if readings are made and transmitted more-or-less instantaneously (i.e. within one second or a few seconds) by the wireless transmitter 18 then the time of receipt by the receiver apparatus may be associated with the readings as a time stamp. Processing of the readings discussed further below is somewhat dependent on the relative timings of the readings (i.e. so that contemporaneous readings from the different sensors can be identified as contemporaneous), however accuracy to the level of one second, a few seconds, or 10 seconds, is sufficient.

In a hybrid mode, capsules 10 may combine the two data transmission techniques. For example, the capsule 10 may process sensor readings on-board to identify motility markers (and optionally also other readings or groups of readings of interest) for transmission in Bluetooth inquiry mode immediately post-excretion. In addition, the capsule 10 may continuously transmit sensor readings to a paired receiver apparatus. Optionally, the continuous transmission may be of the gas sensor signals only, or gas sensor signals and temperature sensor signals required to calibrate gas sensor signals. Gas sensor signals are of particular interest in providing health and clinical information, particularly once combined with motility indicators provided by the other sensors such as accelerometer, reflectometer. Gas sensor signals may be downsampled or subject to other compression techniques by the on-board processor prior to transmission. Optionally, the on-board processor hardware 151 may apply one or more fdters, such as a high pass or low pass fdter applied to the values themselves or to the derivative with respect to time, so that only gas sensor signals meeting particular thresholds are included in the data transmission payload. Metrics representing gas sensor signals, such as peak of a derived H2 value, or area under a plot of derived H2 value with respect to time, may be maintained and transmitted away from the capsule 10.

For capsules 10 configured to perform data transmission during passage through the GI tract (i.e. preexcretion data transmission technique), commercial bands (such as 433 MHz) are used by the antenna 17 as electromagnetic waves in this frequency range can safely penetrate the mammalian tissues 40. Bluetooth may also be used in such capsules, wherein Bluetooth may be long-range Bluetooth, particularly when BMI of the subject (human) is above a threshold, or a high level of attenuation is expected for some other reason. Other commercial bands and protocols may be used in various applications, such as LoRa. Coding may be applied at the digitisation stage to assure that the data transmitted by the capsule 10 is distinguishable from data transmitted by other similar capsules 10. The transmission antenna 17 may be, for example, a pseudo patch type for transmitting data to the outside of the body data acquisition system.

Power source 16 is a battery or super capacitor that can supply the power for the sensors and electronic circuits including the processor hardware 151 and memory hardware 152. A life time of at least 48 hours may be set as a minimum requirement for digestive tract capsules. A number of silver oxide batteries in the power source 16 is configurable, depending on the needed life time and other specifications for the capsule. For example, long-range Bluetooth may consume more power than standard Bluetooth. Capsules may be configured to switch from long-range Bluetooth transmission to standard Bluetooth transmission once the stored energy in the battery (or batteries) drops below a predefined threshold, wherein the on-board processor is configured to monitor stored energy level.

Data Processing Approaches

The on-board sensors generate a large amount of data. Limitations such as energy capacity of power source mean that it may be preferable to process some data on-board the capsule 10 in order to extract a (relatively smaller) data transmission payload from the (relatively larger) generated data. In addition to extraction, data processing techniques may summarise or otherwise represent the generated data in order to reduce the size of the data transmission payload. The processor hardware 151 may be configured to prioritise contents of the data transmission payload. In particular, data representing that the excretion event has been determined and the timing thereof may be given highest priority (i.e. transmitted in preference to other content of the data transmission payload pending transmission at the same time as the data representing that the excretion event is pending transmission).

It will be appreciated that there is a full spectrum of possibilities between, at one extreme, transmitting all generated data away from the ingestible capsule device 10 for processing elsewhere (i.e. from capsule perspective a high data transmission burden and low data processing burden) and at the other extreme performing a high degree of processing on board to determine results including timings of motility events to a high degree of certainty and even to diagnose specific health conditions or ailments, and only transmitting the said processing results (i.e. from capsule perspective a low data transmission burden and high data processing burden).

Embodiments are configurable at the design stage according to implementation requirements to combine data processing and data transmission in a manner that enables data processing to occur, whether on-board or at a receiving apparatus 30 or remote data processing apparatus 20, to determine motility events, and other gut health indicators such as gas constituent concentrations at one or more locations/timings in the GI tract, and to identify or detect diagnostic indicators.

The term signal may refer to the output signal produced by a sensor, whereas the term reading may refer to a specific measurement of the signal taken at or otherwise associated with an instant in time, which instant in time may be included with or associated with the reading explicitly or implicitly (i.e. if the reading is the 1000 ^th reading in a series and readings are taken at a rate of 1Hz and the timing of the first reading in the series is known, then the position of the reading in the series implicitly represents the timing). Time stamps or other timing indicators may be provided by the processor hardware 151. Data represents a reading as a value or a vector comprising plural components, such as one for timing, one for reading value, and optionally further information such as sensor temperature at time of reading, etc.

On-board processing may be performed in more-or-less real time, allowing for latency caused by transfer between components and processing itself. Alternatively, the readings may be received by a receiver apparatus 30 processed thereby and/or stored for upload and processing retrospectively by a remote processing apparatus 20 Dependencies may exist between indicators or markers in the data which constrain an order in which readings are processed. For example, in methods which specifically relate to analysing data representing an increase in detected concentration of volatile organic compounds at the capsule, an on-board processor 151 may extract readings representing an increase in detected concentration of volatile organic compounds from those not representing an increase, and add the extracted readings to the data transmission payload whilst discarding the remainder. So that the on-board processor 151 performs pre-processing, and an off-board processor receives the extracted readings to perform the diagnostic method.

Alternatively, the on-board processor 151 may be configured to perform methods, such as those illustrated in Figures 0 and 4, by executing processing instructions stored on the on-board memory hardware 152. Data processing overhead is increased in this case, which increases performance requirements and thus cost of the on-board processor 151 and memory 152, but reduces the data transmission overhead thus suppressing performance requirements of the wireless data transmitter 18. On the assumption that processing data on-board consumes less energy than transmitting said data to a receiver apparatus 30 for off-board processing, the on-board processing case also reduces stored energy requirements at the power source 16.

In the off-board processing case, the processing may be executed at a receiver apparatus 30 in direct communication with the ingestible capsule device 10, or at a computing apparatus 20 in data communication with the receiver apparatus 30. For example, the receiver apparatus 30 may be a dedicated device configured to receive signals transmitted by the wireless data transmitter 18, such as signals transmitted in the 433MHz radio band. Alternatively the receiver apparatus 30 may be a general purpose computing apparatus such as a smartphone or tablet computer configured to receive signals transmitted by the wireless data transmitter 18, such as signals transmitted according to the Bluetooth transmission protocol, or according to the LoRa transmission protocol.

Communication between the capsule 10 and the receiver device 30 may be via a wireless data transmitter 18 on the capsule 10 configured to transmit signals according to the LoRa data transmission protocol.

Communication between the capsule 10 and the receiver device 30 may be via a wireless data transmitter 18 on the capsule 10 configured to transmit signals according to the Bluetooth data transmission protocol.

Communication between the capsule 10 and the receiver device 30 may be via a wireless data transmitter 18 on the capsule 10 configured to transmit signals according to the Bluetooth data transmission protocol. Communication between the capsule 10 and the receiver device 30 may be via a wireless data transmitter 18 on the capsule 10 configured to transmit signals according to the Bluetooth long-range (coded-PHY) transmission protocol.

Specifically the signals transmitted according to the Bluetooth transmission protocol may be transmitted according to a post-excretion transmission mode, being a term referring to a transmission mode that does not depend upon paired status, by virtue of broadcasting data, or by virtue of initially attempting to transmit data to a couple/paired device but broadcasting data as a fallback in case coupling/pairing is unsuccessful. Broadcasting data may be executed in a handshake mode, inquiry mode, or discovery mode, in which data is broadcast by the data transmitter. For example, a generated report such as illustrated in Figure 4a at step S50 may be included in broadcast data.

In the post-excretion transmission mode, the wireless data transmitter may initially attempt to pair to a receiver, and implement the broadcasting if the pairing attempt is unsuccessful. The pairing attempt may be an attempt to re-pair to a receiver that has previously been paired to the transmitter. Data may be transmitted according to a coded-PHY Bluetooth transmission protocol, or according to a standard Bluetooth transmission protocol.

In the post-excretion transmission mode example, excretion of the ingestible capsule device 10 from the subject may be detected by an on-board environmental temperature sensor 14, the measurements, signal, or readings of which are monitored by the on-board processor 151 which triggers the beacon transmission mode of the wireless data transmitter 18 to transmit a data transmission payload immediately upon detection of capsule excretion.

The post-excretion transmission mode may be triggered by determination that an excretion event has occurred (i.e. that the capsule has been excreted) based on readings of an on-board temperature sensor, and specifically a decrease from the in-vivo temperature. In a case in which the capsule device 10 has already been paired to a receiver 30 such as a smartphone, for example during an initiation procedure, the capsule device 10 may attempt to re-pair, and if successful, transmit a data transmission payload to the paired receiver 30. In the event of re-pair being unsuccessful, for example after a finite number of attempts or after a timeout (for example, 1 second, 3 seconds, 5 seconds), the wireless data transmitter 18 is configured to transmit a data transmission payload in a discovery, inquiry, or handshake mode, which is ordinarily a pre-cursor to pairing and enables some data transfer. A dedicated application at the receiver 30 is configured to access and process the data transmission payload so transferred.

The data transmission payload may comprise one or more from among: a diagnosis outcome (positive/negative), an indication that SIBO has been determined to be present in the subject, a measured level of fermentation activity measured in the small bowel of the subject, and one or more calculated metrics or parameters leading to the diagnosis, detection, determination, or measured level. In a further example, the data transmission payload may comprise a representation of a predefined characteristic feature in the readings generated by a specific gas sensor such as the VOC gas sensor, whether that representation be the underlying readings from the specific gas sensor, or a parameter derived therefrom such as an indication of presence/absence of an increase in concentration of a particular component in the gas mixture. An example of a predefined characteristic feature is a double increase in concentration of VOCs detected in VOC gas sensor readings, wherein the double increase may be represented by an increase magnitude ratio or other characterisation of the a double increase in concentration of VOCs where present.

The present methods for determining presence of SIBO was developed in specific trials and other data- gathering exercises in which ingestible capsule devices 10 such as disclosed in Australian patent application number 2022900873 and predecessor versions thereof (all housing gas sensor hardware inter aha other sensor devices and electronic components) are ingested by subjects (some having positive SIBO diagnoses based on other tests such as jejunal aspirate test and some having negative diagnoses) and the data generated by the on-board sensors analysed to identify characteristics or features that are indicative of SIBO.

Description of Method in Figure 4a

Figure 4a illustrates a method. The method of Figure 4a may be a computer-implemented method. The method of Figure 4a may be executed by processor hardware 151 in cooperation with memory hardware 152 on board an ingestible capsule device 10. The method of Figure 4a may be executed by a receiver device 30 configured to receive data representing a time series of readings from gas sensor hardware housed within an ingestible capsule device 10 from the ingestible capsule deice 10, or by a remote computing apparatus 20 in data communication with such a receiver apparatus 30. The method of Figure 4a may be executed by a combination of the processor hardware 151 on board the ingestible capsule device 10, the receiver apparatus 30, and/or the remote computing apparatus 20.

Figure 4a illustrates a method for detecting small intestinal bacterial overgrowth, SIBO. At step S10 data is obtained representing a time series of readings from gas sensor hardware housed within an ingestible capsule device 10 orally ingested by a subject 40, the time series of readings being taken during exposure of the gas sensor hardware to a gas mixture at the ingestible capsule device 10 during passage of the ingestible capsule device through a gastrointestinal tract of the subject 40, each reading representing a composition of the gas mixture at the location of the ingestible capsule 10 device in the gastrointestinal tract of the subject 40. Obtaining data S 10 may be by receiving the data from the sensor hardware itself or from, for example, a sampler configured to periodically sample an output signal from sensor hardware. Obtaining data S10 may be by receiving data from the ingestible capsule device 10 itself. Obtaining data S10 may be by reading data from a predefined storage location. The time series of readings may be time-stamped values, or the temporal component may be implicit via a placement in a chronological sequence of readings.

The gas sensor hardware may include, for example, an H2 gas sensor specifically sensitive to changes in concentration of H2 in the gas mixture at the location of the ingestible capsule device 10. The gas sensor hardware may include, for example, a CH4 gas sensor specifically sensitive to changes in concentration of CH4 in the gas mixture at the location of the ingestible capsule device 10. The gas sensor hardware may include, for example, a TCD gas sensor 131 sensitive to changes in thermal conductivity of the gas mixture at the location of the ingestible capsule device 10, which is correlated with changes in concentration of different constituent gases, and thus by taking TCD gas sensor readings at different operating temperatures and based on the correlation, concentrations of different composite gases are derivable. The gas sensor hardware may be or may include, for example, a VOC gas sensor 132 sensitive to changes in concentration of volatile organic compounds in the gas mixture at the location of the ingestible capsule device 10.

The gas sensor hardware may comprise two separate VOC gas sensors, with differing sensitivities, wherein detecting ileocecal junction transition indicator at S20 is based on the readings of a first of the two VOC gas sensors, detecting fermentation at S30 is based on the readings of a second of the two VOC gas sensors. The two VOC gas sensors may operate with different deposited sensing materials. The second VOC gas sensor may be more sensitive than the first VOC gas sensor.

The method includes, at S20, detecting an ileocecal junction transition indicator among the obtained data, and a timing thereof. Since the readings are a time series, a timing of the readings in which the ileocecal junction transition indicator is detected may be given as the detected timing of the ileocecal junction transition indicator. Optionally, buffer periods may be added to the start of the detected timing, so that at step S30 fermentation occurring after ileocecal junction transition is not erroneously attributed to the small bowel. Techniques for detecting ileocecal junction transition indicator are discussed in more detail below.

The method includes, at step S30, detecting a fermentation indicator among readings preceding the timing of the ileocecal junction transition indicator. The timing of the ileocecal junction transition indicator provides an upper bound of the timing of readings which are processed to identify a fermentation indicator. Methods may also apply a lower bound. The lower bound may be a predefined temporal duration before the detected timing of the ileocecal junction transition indicator, such as one hour or less, half an hour or less, twenty minutes or less, or fifteen minutes or less. Alternatively, the lower bound may be determined by detecting gastric emptying, i.e. gastric-duodenal transition of the ingestible capsule device 10 into the small intestine, and the timing of the gastric-duodenal transition being the lower bound. Gastric-duodenal transition may be detected by processing TCD gas sensor readings, for example. More detail is provided below on detecting the gastric-duodenal transition indicator. Alternatively, readings from a sensor such as an accelerometer 19 or a reflectometer 18, or both in combination, may be utilised to detect presence of the ingestible capsule device in the small intestine and thus to set the earliest of said detected presence as the lower bound on the timing of the fermentation indicator. For example agitation of the ingestible capsule increases in the small intestine relative to the stomach and this is represented in the output signal of the accelerometer 19. Similarly the dielectric constant of the stomach is different to that of the small intestine and hence readings from a reflectometer 18 can be processed to detect that the capsule 10 is in the small intestine.

The fermentation indicator may be detected in the readings of the same individual sensor as the ileocecal junction transition indicator. For example, a VOC gas sensor 132 generating readings representing two increases in concentration of VOCs separated by a gradient change. Alternatively, the fermentation indicator may be detected in the readings of a different sensor from the ileocecal junction transition indicator. For example, ileocecal junction transition indicator may be detected in the readings of the VOC gas sensor 132 whereas the fermentation indicator may be detected in the readings of a separate, more sensitive VOC gas sensor, in the readings of a dedicated H2 gas sensor, and/or in the readings of a dedicated CH4 gas sensor. Readings of plural sensors may be combined to detect the fermentation indicator, by detecting contemporaneous indicators in the readings of the plural sensors.

At Step S40, the method includes, in response to detecting the fermentation indicator, determining presence of SIBO in the subject. For example, fermentation indicator alone may not be sufficient to determine that SIBO is present in the subject. At step S40, a threshold or some other criterion or criteria is applied to the detected fermentation indicator to determine whether or not SIBO is present in the subject. In a particular example of a double increase in sensed concentration of VOCs by a VOC gas sensor, it may be that a threshold is applied to a ratio of the magnitudes of the concentration increases. Wherein if a ratio of magnitude of increase in VOCs of the fermentation indicator to magnitude of increase in VOCs of the ileocecal junction transition indicator does not exceed a threshold, then SIBO is not determined to be present in the subject, whereas if it does exceed the threshold, then SIBO is determined to be present. Equivalent approaches may be performed with other sensor hardware arrangements, noting that it may not always be a ratio that is considered: for example it may be that a threshold is applied to the fermentation indicator itself independent of the ileocecal junction indicator. In any configuration, preprocessing in trials and/or using published data is performed to determine a threshold value deterministic of SIBO in the relevant fermentation indicator. At step S50 a report is generated indicating one or more from among: the determined presence of SIBO in the subject; the determined absence of SIBO in the subject; a level of detected fermentation activity. Further data may be included in the report such as readings forming the ileocecal junction transition indicator, or a representation thereof, readings forming the fermentation indicator, or a representation thereof.

The generated report is output, for example, in embodiments in which the report is generated at the ingestible capsule device 10 the generated report is output to a receiver device 30 via the wireless data transmitter, either during passage through the remainder of the GI tract of the subject, or upon detection of excretion. In embodiments in which the report is generated by the receiver device 30 or processing apparatus 20 in data communication therewith, the output may be transmission to a clinician and/or patient via a messaging interface, or the output may be display of the report on a user interface.

The level of fermentation activity in the small bowel may be indicated by the fermentation indicator itself or by a related metric. For example, the level of fermentation activity in the small bowel may be measured or calculated by area under a plot of H2 concentration against time. Noting, for example, that H2 may be directly measured or may be calculated as a derived metric from readings from sensors such as TCD gas sensor 131. Level of fermentation activity is a quantification of fermentation occurring in the time series of readings from the gas sensor hardware determined to be taken during residence of the capsule 10 in the small bowel, whether that be by detecting entry and exit to and from the small bowel, or by detecting exit and setting a predefined duration preceding timing of detected exit during which fermentation activity is measured (i.e. fermentation indicator is sought).

Level of fermentation activity is a measurable physical effect of SIBO, noting that factors such as circadian rhythm, diet, among others, may influence level of fermentation activity. A patient may be monitored over a period of weeks or months to assess effectiveness of a SIBO treatment by performing the method of Figure 4a on distinct occasions and monitoring how the reported level of fermentation activity changes.

Generated reports may include further information such as determined ingestion timing, determined excretion timing, other metrics such as peak hydrogen, total hydrogen, etc.

Detecting Ileocecal Junction Transition Indicator

Step S20 detecting ileocecal junction transition indicator (referring to transition of the ileocecal junction by the ingestible capsule device 10) may be detected according to a number of techniques. Readings of H2 levels may be used as a basis for detecting an ileocecal junction transition indicator at S20. H2 levels may be detected directly by an H2 gas sensor sensitive specifically to changes in H2 concentration. Alternatively, an ileocecal junction transition indicator may be detected by identifying an increase in concentration of volatile organic compounds indicated by VOC gas sensor output exceeding a predefined threshold (either the increase exceeding a predefined threshold or the level itself exceeding a predefined threshold) with a contemporaneous (or temporally adjacent to within a predefined temporal distance either side) increase in H2 levels exceeding a predefined threshold (either the increase exceeding a predefined threshold or the level itself exceeding a predefined threshold). Noting that H2 levels are determined from the TCD gas sensor output and/or heater-side VOC sensor output. H2 levels are determined from TCD gas sensor output by taking TCD readings at different operating temperature setpoints of the TCD gas sensor along with predefined calibration data correlating changes of thermal conductivity at different operating temperature setpoints with variations in concentration of different constituent gases.

Similarly, readings of CH4 concentration may be used as a basis for an ileocecal junction transition indicator. CH4 concentration may be detected directly by a CH4 gas sensor sensitive specifically to changes in CH4 concentration. Alternatively, an ileocecal junction transition indicator may be detected by identifying an increase in concentration of volatile organic compounds indicated by VOC gas sensor output exceeding a predefined threshold (either the increase exceeding a predefined threshold or the level itself exceeding a predefined threshold) with a contemporaneous (or temporally adjacent to within a predefined temporal distance either side) increase in CH4 levels exceeding a predefined threshold (either the increase exceeding a predefined threshold or the level itself exceeding a predefined threshold). Noting that CH4 levels may be determined from the TCD gas sensor output and/or heaterside VOC sensor output.

An ileocecal junction transition indicator may be detected as an increase in concentration of VOCs in the gas mixture at the capsule 10 indicated by the time series of readings from a VOC gas sensor 132. Since an increase in concentration of VOCs in the gas mixture at the capsule 10 may be caused by fermentation in the small bowel, it may be necessary to distinguish one increase from another. Such distinction is by identifying a gradient change, wherein readings proceeding a gradient change are a detected ileocecal junction transition indicator, and readings preceding the gradient change are processed at S30 to determine whether a fermentation indicator (i.e. the other increase) is detectable therein.

Detecting Gastric Duodenal Transition Timing

Gastric emptying or crossing the interface between the stomach and the duodenum may be detected to set a lower bound on timing of the fermentation indicator. Such a process is optional since the lower bound may be set by a predefined fixed duration relative to detected ileocecal junction transition timing, or otherwise by detecting presence of the capsule 10 in the small intestine (i.e. not necessarily detecting the transition into the small intestine itself). Gastric duodenal indicator or indicators may be detected in a first subset of recorded readings, the first subset being defined temporally by starting after an ingestion event. Ingestion event may be determined by readings from a temperature sensor or by a user interaction with an interface on a receiver apparatus 30 or remote computer 20. Furthermore, the first subset may be constrained by sensor, comprising readings from the TCD gas sensor 131. The first subset may further comprise readings from the reflectometer (i.e. the antenna 17 and directional coupler 171) and/or the accelerometer 19.

The gastric -duodenal transition indicator in the TCD gas sensor readings may be a, spike, step change or an inflection point in the TCD gas sensor readings. A correction may be applied to the TCD gas sensor readings to account for changes in environmental temperature, based on recorded readings from the environmental temperature sensor 14a. The correction may be applied at the detecting stage so that the recorded readings themselves are corrected to account from changes in environmental temperature, and a gastric-duodenal transition indicator is detected in the corrected readings. Alternatively, the gastric-duodenal transition indicator may be detected in the raw readings (i.e. the uncorrected readings) and then at the determining step check performed to determine whether or not the indicator is attributable to a change in the environmental temperature or not, and if not, then it is either determined that the gastric-duodenal transition indicator is caused by a gastric-duodenal transition by the capsule 10, or a further condition is applied in the determination (for example, recorded readings from another sensor are checked for a contemporaneous indicator). Alternatively, the further condition may be a threshold or some other condition applied to the detected spike, step change, or inflection point itself.

The primary physical mechanism being sensed in the TCD gas sensor readings in detecting the gastric- duodenal transition indicator is as follows: Hydrochloric acid in the gastric juices leaving the stomach mixes with bicarbonate within the bile acids that is released by the pancreas. This bile acid works to neutralize the pH of the liquid and a by-product of this reaction is CO2. In this area of the GI tract the surrounding gases are primarily N2 and 02 with some trace amounts of CO2. The amount of CO2 created in this reaction are significantly higher than the trace amounts that are around due to swallowing of exhaled breath. Therefore, simply using the TCD sensor output without calculating CO2 is appropriate . In other words, the TCD gas sensor readings, once corrected for environmental temperature variations, themselves provide the gastric-duodenal transition indicator, owing to a change in heat conductivity caused by variation in CO2 concentration across the two sides of the gastric -duodenal transition. For motility purposes (i.e. for determining the location of the ingestible capsule 10) there is no particular need to calculate the actual CO2 concentration. As the TCD sensor 131 is affected by the temperature of the gas mixture at the location of the capsule, a temperature correction process is required to account for changes in the external environmental temperature changes i.e. drinking cold water, exercise, eating etc. Starting from the determined ingestion event timing, the first bump, step change or large inflection in the readings of the TCD gas sensor 131 plotted against time, that is not associated with an environmental temperature change, identifies the gastric -duodenal transition.

Figure 13 illustrates recorded readings of an environmental temperature sensor 14a (top line of readings on the top graph) against time, and corrected TCD gas sensor readings against time for an instance of capsule ingestion and progression through a GI tract. The gastric-duodenal transition indicator, which may be labelled gastric emptying, is indicated by a spike above a threshold height in the corrected TCD gas sensor readings. Spike height may be measured, for example, by distance (e.g. as a proportion, as an absolute value, or as a number of standard deviations) from a trend line fitted against the readings up to that point, or from an average value up to that point (wherein the processor maintains an average value).

Figure 14 shows gastric emptying as visible in TCD sensor output and CO2 readings. CO2 is produced when the hydrochloric acid in the gastric juices leave the stomach and mix with bicarbonate in the bile acids released by the pancreas. This reaction also neutralizes the pH of the liquid. Embodiments use the temperature compensated raw TCD sensor output to detect this event, rather than the calculated CO2, since it contains much less noise. The TCD sensor output is adjusted to compensate for the temperature fluctuations measured by the environmental temperature sensor 14a. An algorithm is used to find the moment CO2 increases by removing drinking events and searching for a distinct discontinuity in the TCD output between ingestion and ICJ transition.

As illustrated in Figure 2A, the circuitry includes a directional coupler 171 in series with the antenna 17, which operate as a reflectometer. A diode detector measures the amplitude of reflected signals from the antenna. The measurements of the diode detector are the reflectometer readings, and measure the reflected energy from the antenna, i.e. energy that was not radiated from the antenna 17 due to impedance mismatches. The reflectometer readings measure the antenna's radiation efficiency which is affected by the dielectric of the material surrounding the capsule

The readings may become noisy and/or a baseline shift occurs at the timing of the gastric -duodenal transition event. For example, the increase in noise and/or the baseline shift are detectable as transition indicators. Figure 15 illustrates (on the uppermost plot on the lower of the two sets of axes) reflectometer readings against time (labelled “Ant” for antenna), and is marked with the gastric emptying event. The antenna 17 and directional coupler 171 function as a reflectometer to measure the reflected energy from the antenna, i.e. energy that wasn’t radiated out of the antenna. This signal varies as the surrounding dielectric properties change, most notably when the capsule leaves the cavernous fluid filled stomach and transitions to being surrounded by tubular tissue in the small intestine. A shift in the reflectometer readings is observed to be coincident with the TCD marker, adding confidence, as a secondary measure.

Figure 16 is a plot of recorded readings (or processed versions thereof) against time for a number of sensors and pseudo sensors in the capsule 10. A gastric emptying (gastric -duodenal transition) event is labelled. The top plot in the graph of Figure 16 is reflectometer readings against time (labelled “Ant” for antenna). It can be seen that a baseline shift occurs at a time coincident with the spike in corrected TCD gas sensor readings. For example, a baseline shift may be detected by, on a progressive/rolling basis, comparing a mean value of a latest number (e.g. five, ten, or twenty) of consecutive readings, with a mean value of a number of readings preceding (or proceeding in the case of reverse chronological processing) the latest number of consecutive readings. A baseline shift may be indicated by a difference more than a threshold, wherein the threshold may be an absolute value, a proportion, or determined relative to a standard deviation in the readings. Detecting a coincidental gastric-duodenal indicator in the output of the reflectometer may be sufficient to confirm that the first gastric duodenal transition indicator is caused by gastric-duodenal transition of the capsule 10 and thus to determine the timing of the gastric -duodenal transition. Alternatively, the combination of the two indicators may be assessed via a probability model to revise the confidence score and compare the revised confidence score with a threshold, wherein meeting the threshold is to determine that the first gastric duodenal transition indicator is caused by gastric-duodenal transition of the capsule 10 and thus to determine the timing of the gastric -duodenal transition.

An exemplary accelerometer 19 measures roll about three mutually orthogonal axes. The readings from the accelerometer 19 may be vectors with a component per axis, with each component indicating an instantaneous angular acceleration about the corresponding axis, or an average acceleration about the corresponding axis over the time period since the preceding live reading. Alternatively, the readings may give a three dimensional orientation of the capsule. On-board the capsule, at a receiver apparatus 30 or at a remote computer 20, processing of the readings from the accelerometer may be performed to generate a representation (such as a plot vs time) of aggregated (i.e. all three axes) accelerometer readings from which a marker (i.e. a gastro-duodenal transition indicator) is identifiable. Such a plot or representation may also be used to identify markers for other events including excretion event. In Figure 16, an “angle travelled” plot is generated. It is an accumulation of scalar angular displacement about all three axes cumulatively over time, wherein a low pass filter is applied to filter out small angular displacements. Angle travelled is an exemplary metric that may be calculated periodically to represent the accelerometer data, with the periodical calculated values being included in the data transmission payload in place of the relatively larger data load of the raw accelerometer data.

Figure 17 shows roll in each of three mutually orthogonal dimensions and is marked with gastric emptying event, from which it can be seen that the change in accelerometer readings correlates temporally with the change in corrected TCD readings (i.e. can be used to add confidence to a detection of gastric-duodenal transition indicator in the temperature corrected TCD readings). The capsule orientation is measured using a triaxial accelerometer and tracking the gravity vector with respect the capsule frame of reference. When the capsule leaves the stomach it tends to experience rapid changes in its orientation as it transits through the duodenum and small intestine. “Angle Travelled”, simply accumulates the orientation change in excess of a 90 degree hysteresis angle. This processing technique tends to be robust to small changes in orientation experienced in the stomach and avoids some of the complexities of other approaches.

A first technique for processing accelerometer data may be referred to as angle travelled. Angle travelled uses vector mathematics to calculate the angle between the gravity vector and a temporary vector. The temporary vector is pulled in the direction of the change in angle, only when this angle exceeds a given threshold (currently 90 Deg) . It is then the accumulation of the change in the temporary vector that is visualized in the representation from which markers are identifiable. What is generally seen is that this measure does not change much in the stomach since the angle between the gravity and temporary vectors rarely exceed the threshold in any one direction, (small back and forth orientation changes in the stomach are effectively ignored by the inherent hysteresis of this algorithm) and that once in the tortuous lumen of the small intestine, this measure accumulates significantly due to the larger, more continuous orientation changes of the capsule. Thus, a step change in the cumulative angle travelled measure is a gastric-duodenal transition indicator, and may be detected on-board the capsule or off-board.

In an exemplary implementation of angle travelled: the accelerometer readings may provide a reading of an orientation of the ingestible capsule relative to a frame of reference in fixed relation to a gravitational vector. Processing of the readings from the accelerometer may comprise recording an orientation of the ingestible capsule given by a first accelerometer reading as a reference orientation, and repetitively in respect of each successive accelerometer reading chronologically: determining whether the orientation of the ingestible capsule given by the respective accelerometer reading is more than a threshold angular displacement from the reference orientation, and if the threshold angular displacement is not met, progressing to the next accelerometer reading without changing the reference orientation, and if the threshold angular displacement is met, changing the reference orientation to align with the orientation of the ingestible capsule given by the respective accelerometer reading. An indicator, such as the gastric -duodenal transition indicator, may be a step change in the rate of change of the reference orientation.

Figure 17 indicates that a step change in a plot of angle travelled is identifiable within a threshold time period of the detected spike in the TCD gas sensor readings. Therefore, the step change in the plot of angle travelled increases confidence in the hypothesis that the detected spike in the TCD gas sensor readings is caused by gastric-duodenal transition. There are two approximately contemporaneous gastric-duodenal transition indicators, which enables the timing of one of the indicators (which one may be pre-selected, for example, the TCD gas sensor readings) to be determined as the timing of the transition event.

A second technique for processing accelerometer data may be referred to as total roll. Total roll calculates the angle between the gravity vector and each of the capsule X, Y and Z axes and expresses this as a continuous measure that can accumulate beyond 360 Deg. For example, if the capsule x axis is at an angle of 350 Deg and rotates by a further 20 Deg, the resulting angle is expressed as 370 Deg rather than 10 Deg. This helps when representing the readings as a plot from which markers are identified since it avoids the sudden angle changes associated with crossing the zero line. In the example a real change of 20 Deg would be visualized instead of an artificial change of 340 Deg. In addition to this basic approach, low pass filtering may be applied to filter the raw data to remove sensor noise. Additionally, angles are only calculated when the raw accelerometer data provide sufficient data to calculate a meaningful angle . An example of where this is not the case is when the two accelerometer axis values used to calculate the orientation angle around the third axis both approach zero. In this case the calculation will be dominated by sensor noise and so a meaningful angle cannot be determined.

The accelerometer readings provide a reading of an orientation of the ingestible capsule relative to a frame of reference in fixed relation to a gravitational vector. Exemplary processing of the readings from the accelerometer may comprise for each of three orthogonal axes in fixed spatial relation to the ingestible capsule derivable from the reading of the orientation, repetitively in respect of each successive accelerometer reading chronologically: calculating, as a scalar value, a change in the orthogonal axis relative to the gravitational vector from the preceding accelerometer reading; applying a low pass filter to the calculated changes; recording the cumulative filtered calculated changes. A marker serving as a gastric-duodenal transition indicator may be, for example, an increase (such as a spike or step change) in the rate of increase in the cumulative filtered calculated changes.

Description of Method in Figure 4b

Figure 4b illustrates a method of diagnosing SIBO in a subject. At S 101 data representing a time series of readings from a VOC gas sensor housed within an ingestible capsule device orally ingested by a subject is received, for example at a processor. The time series of readings are taken during exposure of the VOC gas sensor to a gas mixture at the ingestible capsule device during passage of the ingestible capsule device 10 through a gastrointestinal tract of the subject. Each reading has a value representing a detected concentration of volatile organic compounds in the gas mixture at the capsule. The readings may be taken at predefined intervals, such as every second, every 5 seconds, every 10 seconds, every 15 seconds, every 20 seconds, every 30 seconds, every minute. The readings form a time series. The readings may each include an explicit indication of time such as a time stamp, or time may be implicit by virtue of position within a chronological sequence. For example, post-initiation, the nth reading is at a time of n x m seconds, wherein m is the period between successive readings.

The VOC gas sensor 132 is a sensor apparatus generating an output signal that is sensitive to concentration of volatile organic compounds in a gas mixture to which the sensor apparatus is exposed. A VOC gas sensor 132 may be a heated metal oxide sensor. A VOC gas sensor 132 may be a semiconductor gas sensor.

The processor executing the method may be on-board the ingestible capsule device 10, or off-board, wherein off-board includes being either at a receiver apparatus 30 in direct communication with the ingestible capsule device 10, or at a remote apparatus 20 in data communication with the receiver apparatus 30.

Optionally, the ingestible capsule device further comprises processor hardware 151, memory hardware 152, and a wireless transmitter 18, and the processor hardware 151 in cooperation with the memory hardware 152 is configured to perform the method of Figure 4b during passage of the ingestible capsule device 10 through the gastrointestinal tract of the subject 40, and further to diagnosing SIBO in the subject, to transmit data indicating the diagnosis to a receiver device via the wireless transmitter. The processor hardware and memory hardware may be combined in a single chip.

At SI 02 a characteristic feature is detected among a plurality of consecutive readings representing an increase in detected concentration of volatile organic compounds at the capsule 10. For example, in physical terms the increase in detected concentration of volatile organic compounds may be represented by a drop in resistance at the VOC gas sensor 132. It is noted that there are numerous ways in which a VOC gas sensor 132 may be configured to represent concentration of VOCs in a gas mixture at the sensor, and specifically to represent changes in concentration of VOCs in a gas mixture at the sensor. Therefore, in this document where references are made to signals, readings, signal traces, measurements, or values, representing an increase in concentration of VOCs, it is not limiting in terms of whether the increase is represented by a decrease or an increase in the signal, reading, signal trace, measurement, or value output by the VOC gas sensor 132.

For example, the characteristic feature is an earlier portion of consecutive readings preceding a gradient change and having an earlier portion gradient, and a later portion of consecutive readings proceeding the gradient change and having a later portion gradient, the earlier portion and the later portion being separated from one another by the gradient change. The characteristic feature represents an increase in VOC concentration wherein the increase includes a change in rate of increase such that the increase may be divided into two portions, and thus may be referred to as a double drop, or a double increase, depending on how the ingestible capsule device 10 is configured to represent signal from the VOC gas sensor 132.

Detecting the characteristic feature at SI 02 may comprise maintaining a record of gradient of the readings with respect to time, and identifying when a rate of change of the gradient (i.e. the second order derivative and specifically a magnitude thereof) exceeds a second order derivative predefined threshold, during a period of increase or decrease. A point of gradient rate of change exceeding the threshold may be referred to as a turning point or a discontinuity. Furthermore, a further threshold (a period of increase or decrease threshold) may be applied to identify a subset of readings in which the second order derivative is monitored to detect the gradient change.

At SI 03 a determination is made as to whether or not the detected characteristic feature is a diagnostic indicator of SIBO. The processor is configured to characterise or otherwise represent the characteristic feature to enable a determination to be made as to whether or not SIBO is present in the subject. For example, in case the characteristic feature is an earlier and later portion of consecutive readings each representing an increase in VOC concentration and being separated by a gradient change, a determinant may be a ratio of the magnitude of increase in VOC concentration represented by the earlier portion to the magnitude of increase in VOC concentration represented by the later portion. The determinant may be compared with a threshold determined in the trials discussed further below. In other words, determining that the characteristic feature is a diagnostic indicator comprises calculating a ratio of: an earlier change being a change in VOC concentration represented by value of readings from an earliest to a latest reading in the earlier portion, to a later change, being a change in VOC concentration represented by value of readings from an earliest to a latest reading in the later portion, and comparing the calculated ratio with a predefined threshold configured to distinguish presence or absence of SIBO.

At SI 04 the comparison with the threshold enables a positive or negative SIBO diagnosis to be made, i.e. to determine whether the detected characteristic feature is a diagnostic indicator of SIBO or not. A machine learning algorithm may be trained to perform a method of detecting the characteristic feature, and optionally also determining whether or not a detected characteristic feature is a diagnostic indicator of SIBO.

Any combination of steps SI 02 to SI 04 may be performed by an appropriately trained Al classification algorithm. The underlying algorithm may be a convolutional neural network. Training data in the form of the VOC gas sensor traces from SIBO positive and SIBO negative cases in the PA trial or other supplementary trials with ground truth being a positive or negative diagnosis. The convolutional neural network learns to identify the visual distinction between the gas sensor traces in the positive and negative cases and thus to predict whether test cases are SIBO positive or SIBO negative. Using a comparable approach, the neural network may be trained simply to detect presence or absence of a double increase in sensed VOC concentration or other characteristic feature in the VOC gas sensor traces, with determinative processing then utilised to determine whether or not the detected characteristic feature is a diagnostic indicator of SIBO (this hybrid type approach may be useful in case control over the reasoning behind the diagnosis is required to be tightly maintained).

Diagnosing SIBO in the subject at SI 04 may be a simple Boolean, being positive if SIBO is diagnosed and negative otherwise.

The ingestible capsule devices 10 used in the trials and data gathering exercises are designed and produced by Atmo Biosciences Pty Ltd and may be referred to as Atmo gas capsule.

Princess Alexandra SIBO Trial

A clinical trial was conducted at Princess Alexandra Hospital to test the feasibility of the Atmo gas capsule as a diagnostic device for SIBO. Patients over 18 years old who were scheduled for an upper GI endoscopy were recruited to participate.

In summary, the Princess Alexandra (PA) trial into SIBO diagnostics produced 12 Atmo gas capsule datasets with associated jejunal aspirate and/or breath test SIBO results. Comprehensive analysis of available data was conducted to discover and validate associations between aspirate and breath test results and capsule sensortraces.

Patients were given an Atmo gas capsule to ingest, then underwent their upper GI endoscopy half an hour following the ingestion. The ATMO gas capsule was pushed into the small bowel by the scope, if still in the stomach at that time, and a fluid sample of the upper small bowel was obtained for aspirate analysis. Immediately prior to endoscopy, a baseline breath sample was collected. Thus, the Princess Alexandra (PA) trial provided basis for comparison between jejunal aspirate test results, breath test results, and the present diagnostic method. After endoscopy, breath test samples were taken every 20 minute s for up to 2 hours following . A standard glucose breath te st was given to each patient to complete at home, to be done more than 8 hours after endoscopy. Samples were collected every 20 minutes for 2 hours following ingestion of 75g glucose and analysed for Hydrogen (H2) and Methane (CH4) concentration. The primary outcomes of the trial were breath test results (including H2, CH4 results) (positive or negative for SIBO as assessed by change from baseline to peak), jejunal aspirate results (positive for SIBO indicated by bacterial parts per million > 103) and Atmo gas capsule sensor output traces (wherein a time series of readings may be represented as a trace). The goal of the trial was to determine whether a characteristic feature (i.e. trait, signature, marker) is detectable in the data generated by the Atmo gas capsule during passage through the GI tract of a subject that could be indicative of a positive SIBO diagnosis.

Trial Outcome

Analysis of PA trial data led to the development of the present method. The inventors made the surprising observation that a characteristic feature is identifiable in the Volatile Organic Compound (VOC) sensor trace (see Figure 5a), the characteristic feature being a representation of a period of increase in VOC concentration that is divisible into two portions according to gradient, separated by a point or period of gradient change.

The Atmo gas capsule 10 may contain one, two, or more different sensors to detect gas concentrations. In the PA trial, capsules 10 included two gas sensors: a Thermal Conductivity Detector (TCD) and a Volatile Organic Compound (VOC) gas sensor. The TCD gas sensor 131 detects gas concentrations by measuring changes in conductivity across a heated filament. It is sensitive to Carbon Dioxide (CO2) and Oxygen (02) in particular, as well as Hydrogen (H2). The sensor side of the VOC gas sensor 132a detects all volatile organic compounds, such as H2 and others, which it can detect at lower concentrations than the TCD sensor. Resistance across a filament decreases as VOC concentration increases.

It is noted that the trace is composed of individual readings that can be considered to form a trace when arranged chronologically, noting that the readings are a time series. It is further noted that the capsule output data of Figure 5a also illustrates sensortraces from an environmental temperature sensor 14 and a TCD gas sensor 131, corrected for environmental temperature variation. It is further noted that the VOC sensor side trace is marked as Motility (Hot) in Figure 5a. Figure 5a also indicates gastric emptying time (GET) and small bowel transit time (SITT or SBTT, small intestinal transit time or small bowel transit time), and CTT colonic transit time.. The transition between stomach and small bowel (i.e. gastric-duodenal transition) may be identified on-capsule or off-capsule depending on configuration, and in either case used as a trigger to begin monitoring VOC gas sensor output (sensor side) for readings indicating an increase in detected VOC concentration at the capsule exceeding a predefined threshold rate of change.

The hydrogen concentration trace is not directly detected by the ingestible capsule device 10 but is derivable by combining the corrected TCD trace with the VOC sensor side output trace and predefined calibration data. The present method is not dependent on the hydrogen concentration trace, but it is provided for comparison and completeness.

It is noted in embodiments that the ingestible capsule device 10 is configured such that the VOC sensor side readings are readings of resistance across a sensor side output electrode or connector of a VOC gas sensor 132a, and therefore the readings drop as detected concentration of volatile organic compounds increases. However, ingestible capsule devices 10 may be configured such that the readings increase as detected concentration of volatile organic compounds increases.

The VOC sensor 132a is more sensitive to increases in Volatile Organic Compounds, specifically H2, compared with the TCD gas sensor 131. Increase in volatile compounds results in a drop in measured resistance (representing an increase in VOC concentration), seen as a drop in the VOC gas sensortrace. This increase in VOC concentration is generally associated with the transition between small and large bowel. As significantly more fermentation occurs in the large bowel compared to the small bowel, a significant change in VOC resistance is observed at the transition between small and large bowel, otherwise referred to as ileocecal junction transition. In most healthy patients (67%) a single increase in VOC concentrattion is observed, representing an increase in VOC concentration (see Figure 5b). In the PA trial results, a double increase in the VOC concentration in the gas mixture at the capsule 10 was observed in 89% of the SIBO cohort, significantly higher incidence than in a healthy population. The inventors therefore hypothesized that the earlier increase in VOC concentration observed in the VOC trace may correspond with early Hydrogen production due to the presence of excessive bacteria in the small bowel, indicative of SIBO, and the later increase in VOC concentration would then correspond with the true transition between small and large bowel.

Validation of Hypothesis

Analysis of the PA trial data showed no significant change in H2 % concentration between healthy and SIBO positive subjects as measured by the TCD gas sensor 131. However, the sensor side output of the VOC gas sensor 132a showed a characteristic ‘double -increase’ feature at a significantly higher incidence in SIBO-positive subjects compared to healthy subjects. This characteristic feature was subsequently validated using bench top testing. Calculation of an increase magnitude ratio, explained further in this report, led to the development of a diagnostic boundary to differentiate between healthy and SIBO-positive patients, labelled the ‘Atmo SIBO Dx Method’ which was applied to a wider data set available to Atmo for further validation (refer to BMTH Final Report). A clinical explanation of this feature is also included below. The calculated increase magnitude ratio enables determination of when presence of the characteristic feature is a diagnostic indicator of SIBO, and when it is not.

Figure 6 highlights the observed correlation between a SIBO-positive aspirate result and a ‘doubleincrease’ response on the sensed VOC concentration (light-blue trace, wherein increase in VOC concentration is a drop in the trace). Figure 6 is equivalent to Figure 5a but from a different subject (i.e. a distinct capsule 10 given to a distinct subject 40).

Figure 5b illustrates a comparable trace from a healthy (non-positive SIBO diagnosis) patient, in which the increase in the sensed VOC concentration is a single increase.

Double-increases in sensed VOC concentration are observed in both healthy and SIBO patients, whereas single-increases in VOC concentration are only observed in healthy patients. Therefore the characteristic feature of the double-increase in VOC concentration is not in itself sufficient as a diagnostic indicator of SIBO. However, the inventors have realised that a ratio of increase magnitude of the first (earlier) increase in sensed VOC concentration to second (later) increase in VOC concentration enables the double -increase traces to be classified into those from patients with SIBO and those without (based on other diagnosis methods).

The increase magnitude ratio may calculated as: increase magnitude ratio equals second increase magnitude divided by first increase magnitude.

When comparing the correlation between confirmed SIBO cases via jejunal aspirate, and the magnitude of the increase-magnitude-ratio, it can be seen that the instances of confirmed SIBO have a much smaller ratio than those who have a negative SIBO diagnosis. This observation indicates that the VOC gas sensors 132a are able to measure the theorised early-rise in H2 caused by SIBO.

The nine complete SIBO data sets from the PA trial (capsule data and aspirate and/or breath test) were compared to data from 109 known healthy patients, with the following results using the VOC double increase characteristic feature:

Therefore, for example, a threshold increase magnitude ratio of 0.075+0.044=0.119 may be utilised in determining when a double increase characteristic feature is a diagnostic indicator of SIBO. It is noted, of course, that specific values and even whether the characteristic feature is drops or increases, is configurable based on the implementation scenario and the capsule design, and specifically the nature of the gas sensor that is sensing the VOC concentration. Furthermore, a different determinant than increase magnitude ratio may be used, for example, a gradient ratio of the two increases in VOC concentration.

Alternatively a threshold increase magnitude ratio is less than the lower bound of the healthy range, 0.233, as diagnostic of SIBO.

Clinical and Physiological Interpretation

SIBO is characterized by excessive bacteria within the small bowel, associated with gastrointestinal (GI) symptoms, weight loss and malabsorption (Dukowicz et al., 2007). In a healthy person, gut bacteria are common within the large bowel, and are responsible for a large amount of digestion, fermenting indigestible carbohydrates into absorbable nutrients as part of a symbiotic system (Oliphant et al., 2019). As part of this fermentation process, bacteria produce volatile organic compounds, for example H2, Nitrogen compounds and Sulphur compounds (Thom et al. 2012). These fermentation by-products are incorporated into a balanced microbiota system within the large bowel in healthy people, but this is not the case for SIBO-positive patients, where these by-products are also produced within the small bowel and can lead to GI distress (Sachdev et al. 2013).

References:

Dukowicz, A., Lacy, B., Levine, G., (2007). Small Intestinal Bacterial Overgrowth. Gastroenterol Hepatol. 3(2): 112-122.

Thorn, R., Greenman, J., (2012). Microbial volatile compounds in health and disease conditions. J Breath Res. 6(2)

Sachdev, A., Pimentel, M., (2013). Gastointestinal Bacterial Overgrowth: pathogenesis and clinical significance. Ther Adv Chronic Dis. 4(5): 223-231

The VOC gas sensor 132 within the ingestible capsule device 10 detects the concentration of VOCs in the gas mixture at the capsule even at low concentrations, represented in output data as a decrease in resistance as VOC concentration increases, or alternatively put, a drop in the VOC trace. Such an increase in sensed VOC concentration is used to distinguish between the location of the capsule 10 in the small and large bowel, and thus provides useful information in tracking motility of the capsule. The increase in sensed VOC concentration is a consequence of the VOC gas sensor 132 detecting the sharp increase in fermentation that is associated with the ileocecal junction transition, i.e. the transition from small intestine to large intestine. Such a technique of determining location of the capsule 10 has shown good compliance with other ways of measuring GI motility, including the Wireless Motility Capsule (WMC) and scintigraphy.

In SIBO, excessive bacteria are present within the small bowel, producing VOCs before the Ileo-Cecal Junction (ICJ), the junction between small and large bowel. This can explain the double-increase seen in the VOC trace for SIBO positive patients such as is illustrated in Figures 4 & 6. The first highlighted increase in VOC concentration represented by the trace is attributable to bacteria within the distal small bowel producing H2 and other VOCs, and the second highlighted increase in VOC concentration represented by the trace is attributable to the typical increase in bacteria - and associated VOCs - and drop in 02 between the small and large bowel.

A physiological interpretation of the smaller increase magnitude ratio observed in SIBO-positive patients is the magnitude of the first increase (a measure of the bacterial content within the small bowel) is much higher than for healthy patients, leading to a smaller ratio of 2nd increase : 1 st increase, wherein the first increase is the earlier of the two increases in sensed VOC concentration (i.e. pre ICJ) and the increase is the later of the two (i.e. post ICJ).

To test the validity of this hypothesis, bench-top assessments were conducted investigating the response from the VOC sensor to small amounts of H2.

Bench-Top Assessment

Having observed the correlation of increase-magnitude-ratios as a characteristic feature that may act as a diagnostic indicator of positive SIBO, a bench-top experiment was devised to simulate a known SIBO case in-vitro to test the validity of the hypothesized clinical explanation and physiological interpretation outlined above. A reference case from the PA trial is capsule number 2100331, output sensor data from which is illustrated in Figure 7. This capsule has a noticeable first-increase in sensed VOC concentration at -6 hours, and another larger increase at -7.25 hours (Figure 7).

A reference Atmo gas capsule, ID number 2100331, was used as an example of a typical doubleincrease case. 02 and H2 % concentration was calculated from the raw data and displayed graphically.

A test Atmo gas capsule, ID number 2100479, a bare board capsule in the gas testing system, was subjected to known concentrations of 02 and H2 to emulate the concentrations calculated from the reference capsule. In this way, the behavior of the VOC, TCD and H2 capsule data traces, when subjected to known concentrations of H2 and 02, were investigated.

For the reference capsule (2100331):

02 (blue trace): The first 4 hours of 210033 l's transit appears to be a stabilization phase. This is estimated to be 02 for the first 0.5 hours at 21%. This is likely to transition from 21% to 6% 02 between 0.5 and 4.5 hours. Between 4.5 and 7.25 the 02 is held constant.

H2 (orange trace): Conversely, H2 is zero at ingestion, and is suspected to rise to 0. 1% H2 at the first VOC bump at 6 hours. At 7.5 hours the H2 is ramped up to 1% over 15 minutes and is then constant for an hour. At ~8 hours the H2 continues to ramp up, reaching 2.5% at the 10-hour mark.

The estimated gas profile of 02 and H2 from 2100331 is illustrated in Figure 8.

The same gas concentrations were simulated in the bench-top test, shown as the blue and orange traces in Figure 9, to verify patterns seen in the VOC and TCD traces.

The benchtop result from capsule 2100479 is illustrated in Figure 9.

There are several phases of the gas profile illustrated in Figure 9 that are noteworthy:

A: Phase A is the 'ingestion' phase and looks normal in terms of VOC rising

B: During this phase the 02 is dropping, this is causing a rise in the TCD signal (i.e. the signal from the TCD gas sensor 131). The VOC signal (i.e. the signal from the sensor side of the VOC gas sensor 132a) remains unchanged.

C: This stable phase looks as expected - no signals are changing.

D: The H2 causes a dramatic decrease in the VOC sensor’s ‘Motility (Hot)’ signal. Minimal response is seen on the Hydrogen trace, and the corrected TCD signal shows only a small movement at that time. This first drop is caused by an increase in VOC concentration and is much bigger in magnitude than was observed on 2100331.

E: In this phase, H2 is held constant and 02 is reduced. A clear drop in the VOC sensor side readings is observable during this phase, representing an increase in sensed VOC concentration. It is anticipated that the dramatic reduction of 02 is typical for an ICJ transition. Interesting to note is the bump in the TCD signal at this time - the clinical capsule 2100331 also shows a TCD bump at this second peak, matching the simulation. F: H2 is quickly increased here. Note that the TCD trace is sensitive to this change in H2, but the VOC sensor trace is largely unaffected by it. It appears the VOC may have reached its saturation limit.

G: In this phase H2 is increased up until the end of the test. The TCD continues to be sensitive to the changing gas concentration, but the VOC sensor is again unaffected by further changes in H2.

Benchtop Assessment Outcomes

Suspected SIBO behavior shown in capsule 2100331 (ie the VOC sensor double-increase in sensed VOC concentration) can be replicated on the bench by increasing H2 concentration and decreasing 02. An increase in H2 of up to 0.1% is shown to cause the first inflection point drop, while the second inflection point can be attributed to a further increase in H2 to 1% concentration, coupled with a decrease in 02 concentration. This aligns with the hypothesized clinical explanation of SIBO, with a slight increase in H2 % concentration in the small bowel due to excessive bacteria, followed by a second, larger increase in H2 % concentration in the large bowel in line with normal microbiota function.

A theory of operation for detecting SIBO has been identified in the form of a VOC gas sensor characteristic feature representing a double increase in sensed VOC concentration and characterisation of the sensed double increase by an increase magnitude ratio of the two increases, which facilitates determination of presence or absence of SIBO, which may be referred to as the present method or the Atmo SIBO Dx Method. The VOC sensor response has been recreated on the bench, and the gas profiles of the bench-top data match with the theory that there is detectable H2 fermentation prior to the transition through the Ileocecal junction.

As both gas concentration and capsule localisation is possible simultaneously, the Atmo Dx Method can identify extra bacterial load within the small bowel, rather than only a change in total H2 production as is detected by breath test. Additionally, the ingestible capsule device 10 is operable to detect gas concentrations throughout the length of the small bowel, including distal changes, whereas jejunal aspirate is restricted to the proximal end of the small bowel.

Supplementary Trials

The Atmo gas capsule has been used in more than 13 different clinical trials investigating different diseased and healthy populations. Data from some of these trials was used to compare population trends between literature values and values observed across Atmo data. Trials included in this analysis were: 6 validation trials in healthy subjects with slight variations between protocols and 2 trials in IBS patients, one dietary intervention study for ROME IV classified IBS conducted at Gothenburg University in Sweden and one dietary intervention study for ROME IV classified IBS-C conducted at KINGS University in Otago. Healthy subjects were self-reported as healthy. For insight into population wide trends, 109 healthy participants were included from across the 6 trials and 64 IBS participants were included from the 2 IBS studies.

Supplementary Trials: Results

The total number of ingested capsules during the PA trial was 12. Of these, two capsules malfunctioned. As a result, the final number of studies was:

10 ingested capsule studies (total)

8 of which had associated breath test results

7 of which had associated jejunal aspirate results

Each study was assessed for SIBO using jejunal aspirate, H2 and CH4 breath test and using the present method (i.e. the Atmo SIBO Dx method) hypothesized as an indicator of SIBO. The results are summarized in the table of Figure 10, wherein + denotes positive and - denotes negative. Only studies with at least one result from an accepted diagnostic (breath test and/or aspirate) were included in the result set.

All SIBO results were analyzed, calculating the increase magnitude ratio of the second increase in VOC concentration divided by the first to find the increase magnitude ratio. The average increase magnitude ratio for SIBO-positive patients was 0.075, with +/- 0.044 95% confidence interval (CI). The incidence of double increase in the SIBO cohort was 0.899.

Therefore, for example, a threshold increase magnitude ratio of 0.075+0.044=0.119 may be utilised in determining when a double increase characteristic feature is a diagnostic indicator of SIBO. It is noted, of course, that specific values and even whether the characteristic feature is drops or increases, is configurable based on the implementation scenario and the capsule design. Furthermore, a different determinant than increase magnitude ratio may be used, for example, a gradient ratio of the two increases in VOC concentration.

Data from 109 healthy participants was collated from past studies. The incidence of double increase in sensed VOC gas concentration in the VOC gas sensor output signal for healthy participants was 0.33. The cases with double increases were analyzed to calculate the increase magnitude ratio for healthy participants, which was 0.447, with +/- 0.214 95% CI.

Finally, historical data of IBS positive, and IBS-C positive, patients was collated and analyzed, totaling 64 studies. The increase magnitude ratio of IBS and IBS-C was 0.649 on average, with +/- 0.27 95% CI. The incidence of double increase in IBS and IBS-C was 0.75. These results are summarized in Table 2.

MAGNITUDE DOUBLE

RATIO INCREASE

HEALTHY 0.447 +/- 0.214 0.33

N=109

SIBO 0.075 +/- 0.044 0.889

N=9

IBS 0.649 +/- 0.313 0.717

N=53

IBS AND IBS-C 0.649 +/- 0.27 0.75

N=64

The healthy dataset was much larger than the unhealthy datasets. This was therefore used to calculate a threshold increase magnitude ratio to classify a VOC double increase characteristic feature as healthy compared to diagnostic of SIBO. The average increase magnitude ratio for SIBO was significantly lower than the increase magnitude ratio for healthy participants, therefore an exemplary threshold increase magnitude ratio is less than the lower bound of the healthy range, 0.233, as diagnostic of SIBO. This was applied to the IBS positive data to estimate the prevalence of SIBO. The prevalence of SIBO was also estimated using only the incidence of the double increase as comparison. The results are summarized in Table 3.

Table 2 Prevalence of SIBO in Healthy, IBS and IBS-C participants.

INCIDENCE OF

PATIENT > = 0.233 = HEALTHY, DOUBLE INCREASE

GROUP <0.233 = SIBO ONLY

% SIBO Count SIBO % SIBO Count SIBO positive positive positive positive

HEALTHY 18.34 20 33 36

N=109

IBS 30.13 16 71 38

N=53

IBS AND IBS-C 32.8 21 75 48

N=64 Using the 0.233 increase magnitude ratio threshold, 32.8% of the total IBS cohort were SIBO positive. This result correlates best with the more recent studies (Abbasi et al., 2015 - 37.4% prevalence and Chu et al., 2016 - 39%) included in Takakura et al.’s meta-analysis (2020). Wu et al., 2019 used a lactose breath test to diagnose SIBO, while Ghoshal et al. (2011) suggest only glucose or lactulose breath testing has application for SIBO diagnosis. The present trial used glucose breath testing throughout, so results are less likely to correlate with Wu et al. 2019.

References:

Abbasi MH, Zahedi M, Darvish Moghadam S, Shafieipour S, HayatBakhsh Abbasi M. Small bowel bacterial overgrowth in patients with irritable bowel syndrome: the first study in iran. Middle East J Dig Dis. 2015 Jan;7(l):36-40.

Chu H, Fox M, Zheng X, Deng Y, Long Y, Huang Z, Du L, Xu F, Dai N. Small Intestinal Bacterial Overgrowth in Patients with Irritable Bowel Syndrome: Clinical Characteristics, Psychological Factors, and Peripheral Cytokines. Gastroenterol Res Pract. 20I6;2016:3230859.

Ghoshal, U, How to Interpret Hydrogen Breath tests. J Neurogastroenterol Motil. 201 1 July; 17(3) Takakura, W., Pimentel, M. Small Intestinal Bacterial Overgrowth and Irritable Bowel Syndrome - An Update. Frontiers in Psychiatry. 2020 July; 11: 1664-0640

W u KQ, Sun WJ, Li N, Chen Y Q, Wei YL, Chen DF. Small intestinal bacterial overgrowth is associated with Diarrhea-predominant irritable bowel syndrome by increasing mainly Prevotella abundance. Scand J Gastroenterol. 2019 Dec;54(I2): 1419-1425.

H2 analysis of Princess Alexandra SIBO trial data

All ingestible capsule devices collected data on H2 % concentration throughout transit. This was investigated in the context of the breath test and aspirate results to observe any difference between positive and negative SIBO patients according to these diagnostic methods.

According to the breath test results, 7 patients were negative SIBO and 2 were positive. Hydrogen statistics were calculated for colonic transit, split into four quartiles according to transit time through the colon. Results were split into ‘negative’ and ‘positive’ according to the breath test result. The results are shown in Figures 11A-1 ID.

The positive SIBO patients (blue, left-hand column per pair) determined by breath test have consistently higher H2 % concentration throughout colonic transit compared to negative SIBO patients (orange, right hand column per pair).

According to the aspirate results, 7 patients were positive for SIBO and 1 patient was negative. The negative SIBO set was supplemented with 6 healthy datasets from other studies, chosen at random. The same analysis of H2 % concentration throughout colonic transit was conducted, with data separated into ‘positive’ and ‘negative’ according to aspirate results. Results are shown in Figures 12A-12D.

Patients that were negative to SIBO according to aspirate (orange) had higher H2 % concentration across all quartiles of the colon compared to positive SIBO (blue). This is the opposite result to the breath test calculations.

This may suggest that breath testing detects overall concentration of H2 and is able to detect a higher or lower total H2 concentration, but lacks the specificity required for localization of H2 production to the small or large bowel, as is required for SIBO diagnosis. This is in line with Massey at al. (2021) and Rezaie et al. (2017), which suggest that glucose breath tests are not adequately specific to localize hydrogen production between the terminal ileum and the cecum. The present ingestible capsule device is able to clearly differentiate between small and large bowel and can therefore localize abnormal VOC and/or gas production to these organs.

Massey, B., Wald, A. Small Intestinal Bacterial Overgrowth Syndrome: A Guide for the Appropriate Use of Breath testing. Digestive Diseases and Sciences. 2021; 66:338-347.

Rezaie, A., Buresi, M., Lembo, A., et al. Hydrogen and Methane-Based Breath Testing in Gastrointestinal Disorders: Tire North American Consensus, Am J Gastroenterol, 2017; 112.

Further Remarks

The PA trial provided comprehensive data that enabled the development of the present method of SIBO diagnosis using the Atmo gas capsule 10. The present method resulted in the same SIBO diagnosis rate as the gold standard jejunal aspirate test for all participants. Extending the investigation to include population trends in IBS and healthy participants, inventors found that 32.8% of IBS participants in Atmo trials had SIBO comorbidity. This is comparable to the prevalence of SIBO in IBS reported in the literature (Abbasi et al., 2015 - 37.4% prevalence and Chu et al., 2016 - 39%). Analysis of Colonic Hydrogen concentration of PA participants suggested that breath test results can detect differences in total hydrogen concentration but may lack the required specificity for isolating hydrogen production to the small bowel, aligning with suggestions from Massey et al. (2021) and Rezaie et al. (2017). Gas capsule device 10 enables collection of gas concentration data simultaneous to capsule localisation within the GI tract and thus to detect motility events in addition to abnormal gas concentrations, thus confidently identifying excess bacterial count occurring within the small bowel.

An ingestible capsule exemplary of the ingestible capsule device is disclosed in Australian patent application number 2022900873 filed on 4 April 2022.

Sensor capsules such as that disclosed in EP3497437A1 house gas sensors and other sensors within an ingestible capsule so that readings may be made from within the gastrointestinal (GI) tract of a mammal, from which readings information about the GI tract may be determined, such as motility reports and concentrations of analyte gases.

A process for determining type and concentration of particular gases in a multi-gas mixture based on readings taken from within the GI tract by gas sensors on-board an ingestible capsule is disclosed in EP3619526A1.

Embodiments

Some embodiments are described in the following numbered statements:

Statement 1. A method for diagnosing small intestinal bacterial overgrowth, SIBO, the method comprising: receiving data representing a time series of readings from a VOC gas sensor housed within an ingestible capsule device orally ingested by a subject, the time series of readings being taken during exposure of the VOC gas sensor to a gas mixture at the ingestible capsule device during passage of the ingestible capsule device through a gastrointestinal tract of the subject, each reading having a value representing a detected concentration of volatile organic compounds in the gas mixture at the capsule; detecting a characteristic feature among a plurality of consecutive readings representing an increase in detected concentration of volatile organic compounds at the ingestible capsule device; determining that the characteristic feature is a diagnostic indicator; and in response to determining that the characteristic feature is a diagnostic indicator, diagnosing SIBO in the subject.

Statement 2. The method according to Statement 1, wherein the characteristic feature is an earlier portion of consecutive readings preceding a gradient change and having an earlier portion gradient, and a later portion of consecutive readings proceeding the gradient change and having a later portion gradient, the earlier portion and the later portion being separated from one another by the gradient change; and determining that the characteristic feature is a diagnostic indicator is dependent upon a comparison of the earlier portion with the later portion.

Statement 3. The method according to Statement 2, wherein determining that the characteristic feature is a diagnostic indicator comprises calculating a ratio of: an earlier change being a change in value of readings from an earliest to a latest reading in the earlier portion, to a later change, being a change in value of readings from an earliest to a latest reading in the later portion; and comparing the calculated ratio with a predefined threshold configured to distinguish presence or absence of SIBO.

Statement 4. The method according to Statement 2 or 3, wherein the gradient change is detected by calculating a first derivative being a rate of change of the values among the plurality of consecutive readings on a rolling basis, and calculating a second derivative being a rate of change of the first derivative, and detecting when the second derivative exceeds a predefined threshold.

Statement 5. The method according to Statement 2 or 3, wherein the gradient change is detected by a pattern matching algorithm.

Statement 6. The method according to Statement 2 or 3, wherein the characteristic feature is detected by a convolutional neural network trained to detect presence of the characteristic feature in a visual or geometric representation of the readings of the VOC gas sensor.

Statement 7. The method according to any of the preceding Statements, wherein the plurality of consecutive readings among which the characteristic feature is detected represent an increase in detected concentration of volatile organic compounds at the capsule, the increase exceeding a predefined threshold configured to indicate transition of the capsule across the ileocecal junction, or the increase rising to a level configured to indicate transition of the capsule across the ileocecal junction.

Statement 8. The method according to any of the preceding Statements, wherein the ingestible capsule device further comprises processor hardware, memory hardware, and a wireless data transmitter, and the processor hardware in cooperation with the memory hardware is configured to perform the method during passage of the ingestible capsule device through the gastrointestinal tract of the subject, and further to diagnosing SIBO in the subject, to transmit data indicating the diagnosis to a receiver device via the wireless data transmitter.

Statement 9. The method according to any of Statements 1 to 8, wherein the ingestible capsule device further comprises a wireless transmitter, and the wireless transmitter is configured to transmit the time series of readings to a receiver device, the method being executed by processor hardware and memory hardware at the receiver device or at a computing device in data communication with the receiver device.

Statement 10. The method according to any of the preceding Statements, wherein the method comprises selecting the plurality of consecutive readings representing an increase in detected concentration of volatile organic compounds at the capsule by monitoring a rate of change of the readings from the VOC gas sensor with respect to time, and when the rate of change represents a rate of increase detected concentration of volatile organic compounds at the capsule exceeding a predefined threshold, the readings representing said rate of increase are selected as the plurality of consecutive readings. Statement 11. The method according to any of the preceding Statements, ingesting the ingestible capsule device by the subject.

Statement 12. An apparatus comprising memory hardware and processor hardware, the memory hardware storing processing instructions which, when executed by the processor hardware, cause the processor hardware to perform a method according to any of Statements 1 to 11.

Statement 13. The apparatus according to Statement 12, wherein the memory hardware and processor hardware are housed within the ingestible capsule device, the ingestible capsule device further comprises a wireless transmitter, and the processor hardware is configured to perform the method during passage of the ingestible capsule device through the gastrointestinal tract of the subject, and further to diagnosing SIBO in the subject, to transmit data indicating the diagnosis to a receiver device via the wireless transmitter.

Statement 14. A computer program which, when executed by a computing processor, causes the computing processor to perform a method according to any of Statements 1 to 11.

Statement 15. A computer-readable medium storing the computer program of Statement 14.

Statement 16. A non-transitory computer-readable medium storing the computer program of Statement 14.

Statement 17. An ingestible capsule device comprising memory hardware and processor hardware, wherein the memory hardware comprises the non-transitory computer-readable medium according to Statement 16 or the computer-readable medium according to claim 15, and wherein the processor hardware comprises the computing processor.

Statement 18. The ingestible capsule device according to Statement 17, wherein the memory hardware and the processor hardware are provided by a single integrated chip component.