FIELD OF INVENTION [0001] The present invention generally relates to movement disorders assessment methods and systems, and more particularly to a tremor assessment method and system.

BACKGROUND OF INVENTION [0002] Tremor is commonly known as a movement disorder, generally characterised by clinical manifestations of involuntary, repetitive movements associated to a body part that can be classified or identified in many ways. It is often crucial to monitor and study the different types of tremors that may occur in a human body, in order to detect any form of disorder or disease.

[0003] One of the important criteria of a tremor assessment tool is that it has to provide data that are presenting the correct and true tremor condition for the judgment of the condition of the same or different subjects especially those suffering from neurological disorders such as Parkinson's disease (PD) and essential tremor (ET). Besides, the sufficiency of the tremor information also dictates the usefulness of the tremor assessment tool in serving various purposes of tremor study. Providing sufficient details of the tremor reading may assist in the advancement sports science and neurological disorder area. The effect of certain sport equipment design or feature on the tremor of the users can be studied with the help of a tool to identify the location and characteristic of the tremor for different user behaviour of using the sports equipment.

[0004] Tremor study of the neurological disorders can help in differentiating PD and ET. A clinical observational tremor assessment on 50 PD and 50 ET shows that the two disorders exhibit different motions of tremor. Typical examples of the observed motions or directionality of the tremors are flexion-extension, abduction-adduction and pronation-supination. Sternberg et al. 2013 emphasized the need to observe tremor across the joints rather than general body locations such as head, upper limbs, trunk and lower limbs. [0005] Numerous tools and systems for detecting tremors have been developed and progressively improved over time, primarily to meet challenges associated to precision and introducing features that have the ability to use gathered input for further assessment. Some of the common tremor sensing devices are force or moment transducer, inertial sensing device and electromyography.

[0006] Force plate and electrocardiogram have been disclosed in the United States Patent No. 6,936,016 for detecting abnormal tremor. Normal body microvibration is said to be mainly contributed by the cardiac activity and an abnormal vibration of the body will result in the increase in the spectral amplitude and a shift to a dominant frequency which is not at heartbeat frequency and / or the associated harmonics. This novel system of identifying the body tremor requires very simple setup without extra weight and hindrance introduced to the subject. This method of measuring tremor however is only suitable for tremor signals that are strong enough to be transmitted to the force transducer, causing possible loss in some smaller amplitude tremors located farther away from the force transducer. The location of the tremor and the direction of the tremor at can be measured are also limited by the suitability of the positioning of the device to allow force exertion on the transducer.

[0007] Three-dimensional inertial sensing devices have been introduced in the United States Patent No. 8, 187,209. This patent emphasizes on its tremor measurement system for having the features of wireless transmission and reception of tremor data and the use of both kinetic information and electromyography (EMG) data for tremor severity quantification. This patent covers the processing of the gyroscopes and accelerometers readings to produce peak frequency, average amplitude and average power; as well as the use of the EMG reading to obtain the electromyography frequency. These tremor symptom variables are fit to the qualitative clinicians Unified Parkinson's Disease Rating Scale scores by multiple linear regression model or neural network. The idea of the correlating or fitting the tremor symptom variables has the potential of replacing the physicians' observational assessment. Despite of all these strengths, there is no magnetometer used in this system for providing long term attitude and position accuracy. Although more than one unit of the inertial sensing device can be used throughout the whole body, no association of the readings among the inertial sensing devices is made, making the tremor readings absolute at any point on the body.

[0008] The need and the effort to support body parts not to be assessed in order to make sure that the tremor occurs at the measuring location are shown in United States Patent No. 4,306,291. This device measures postural tremor by using an accelerometer placed on the subject hand. The signal of the tremor is obtained by controlling and adjusting the amplifier signal. Since only vertical motion of the hand is to be measured, the forearm has to be supported up to wrist joint and preferably the fingers are taped to reduce the independent motions about the metacarpophalangeal joints. Restricting motions as such can make sure that the motion data picked up by the accelerometer is strictly limited to the vertical motion of the wrist joint. This implies that if a specific motion is to be measured at a specific joint using limited motion sensing device or absolute motion reading, refrainment of other unrelated the motion is inevitable. Nevertheless, this restriction does not allow the measured hand to be in the natural condition or slight discomfort may even be introduced to the subject.

[0009] In short, the current tremor assessment systems are still lacking of the capability to (1) identify the particular location of tremor, typically at the joint, (2) identify the particular joint motions involved in tremors and (3) quantify the tremors in relative motions of the adjacent segments, particularly tremor which occurs when there is intended multi-degrees-of-freedom relative movement. None of the discussed prior art explicitly provides or teaches the ability to relate tremor of adjacent segments that have experienced multiplanar relative movements and to accurately present these results in a manner such that they can be easily interpreted by a medical personnel.

[0010] An object of the present invention is to attend to all the aforesaid niche of the tremor assessment technologies in order to fulfil the needs for various subtle tremor characteristics study and medical assessment purposes.

SUMMARY OF INVENTION

[0011] In one aspect, there is disclosed a method of quantifying tremor motion in a subject comprising: attaching a least one pair of sensor on two adjacent segments of the subject body; acquiring data from the sensors; whereby the sensor data are taken when there are multiplanar relative movements of the two adjacent segments; computing the multiplanar relative motions of the two adjacent segments to obtain a joint angle in each relative motion; subjecting the joint angle to a filtering process to obtain a joint angular displacement; and quantifying the tremor motion two adjacent segments using the joint angular displacement.

[0012] Preferably, the method further includes using the joint angular displacement for any tremor analysis process.

[0013] In a preferred embodiment, the sensor data is in the form of quaternion data.

[0014] Preferably, method is used for assessing or quantifying tremors associated to multiple degrees of relative movements.

[0015] Preferably, the filtering process is for removing signal not related to human tremor.

[0016] Preferably, filtering process is performed by a bandpass filter having a passband of 3-30 Hz, whereby the filtering process is performed to remove the large non- oscillatory content of the tremor data, which are typically caused by intended motion and some other unintended large motions; as well as signal noise.

[0017] In the preferred embodiment, the multiplanar relative movements are related to the relative movements of the segments associated to the muscle contraction. The typical said movements, include, but are not limited to flexion-extension, abduction- adduction and pronation-supination.

[0018] Preferably, computing relative motions of adjacent segments in terms of joint angle includes: obtaining motion and indicator axes of the associated motions by determining the respective unit vectors, computing a correction of quaternion rotation, q _c , correcting the distal indicator axis based on the computed quaternion rotation correction, and computing the angles between the corrected distal 1 oiSTALi_correct ^an d proximal indicator axes IpRoxi of the said adjacent segments. [0019] In a preferred embodiment, acquiring quaternion data includes: detecting the motion for each joint using sensing elements and acquire data from said sensing elements to obtain the quaternion data. [0020] Preferably, determining the unit vectors of the motion and indicator axes for any joint motion can be obtained using predetermined equation.

[0021] It is further preferred that the correction of the quaternion rotation, q _c includes the orientation rotation that aligns the distal motion axis M _D1STALi to the proximal motion axis, M _PROXi based on each motion detected so as to position these axes on the same plane.

[0022] Preferably, correcting the distal indicator axis, IDISTAU based on the computed corrected quaternion rotation q _c includes rotating the distal indicator axis IDISTAU based on the corrected quaternion rotation q _c so as to obtain the corrected indicator axis IoiSTALLcorrect °f the distal end associated to the joint.

[0023] Further in the preferred embodiment, computing angles between the corrected distal indicator axis loisTALi_correct ^ar >d original proximal indicator axes IpRoxi result in the attainment of the joint angle.

[0024] In another aspect, the method is used for quantifying hand-arm tremor of a subject's body. [0025] For hand-arm tremor quantification, computing the relative motion includes: obtaining motion and indicator axes of wrist and elbow; determining the unit vectors of said motion and indicator axes, computing a correction of quaternion rotation, correcting the distal indicator axis based on the computed quaternion rotation correction, and computing the angles between the corrected distal indicator axes and original proximal indicator axes.

[0026] Preferably for quantifying the hand-arm tremor, the acquisition of the sensing element data of the hand-arm tremor includes: detecting motions of the distal end of the upper arm and sending signals based on the detection; detecting motions of a distal end of the lower arm and sending signals based on the detection; and detecting the motions of a dorsum portion of the hand and sending signals based on the detection.

[0027] Preferably, classifying the detected motions of the hand-arm tremor includes: classifying the detected motions into four motions i.e. wrist flexion-extension (WFE), wrist abduction-adduction (WAA), elbow flexion-extension (EFE) and elbow pronation-supination (Eps)

[0028] In a further aspect, there is provided a system for quantifying at least one joint tremor(s) motion of a subject; the system comprising: a pair of sensors positioned adjacent to at least one joint on the subject's body; wherein the movements detected from each sensor are recorded and used for classifying and quantifying the hand-arm tremor motions; and for acquiring the joint angular displacement for each motion.

BRIEF DESCRIPTION OF DRAWINGS

[0029] The present invention features, objects and advantages thereof may be best understood by reference to the following detailed description when read with accompanying drawings in which:

[0030] FIG. 1 provides the overall process flow for the method in accordance with an embodiment of the present invention; [0031] FIG. 2 provides an example of coordinate frames of any arbitrary two adjacent segments and motion axes about a joint in accordance with an embodiment of the present invention;

[0032] FIG. 3 depicts an exemplary of hand-arm tremor quantifying method that applies the steps of the present invention;

[0033] FIG. 4 depicts the steps involved in calculating the joint angle associated with multi— degrees— of— freedom relative motion in accordance with an embodiment of the present invention. DETAILED DESCRIPTION

[0034] In line with the above summary, the following description of a number of specific and alternative embodiments is provided to understand the inventive features of the present invention. It shall be apparent to one skilled in the art, however that this invention may be practiced without such specific details. Some of the details may not be described at length so as not to obscure the invention. For ease of reference, common reference numerals will be used throughout the figures when referring to the same or similar features common to the figures.

[0035] The system and method of the present invention can be used to assess tremor associated to at least one joint or a connection between segments of the subject's body, and more particularly for assessing tremor associated with multiplanar relative movements. In a preferred embodiment, the method of the present invention enables quantification of tremor that involves multi-degrees-of-freedom relative motions, which has yet to be addressed in the prior art systems.

[0036] In a preferred embodiment and as shown in FIG. 1, the multi-degrees-of- freedom tremor motion quantifying system comprises: at least one pair of sensing elements for data acquisition 101 from whioh raw sensing element data is passed to the tremor data processing algorithm 102 before tremor data analysis 103 useful for tremor study can be carried out. It should be noted that, each sensor is configured to detect movements with a predetermined degree of freedom for each segment.

[0037] Tremor data processing algorithm 102 in accordance with the preferred embodiment of the present invention comprises: axes assignation for tremor motion classification 102A; computing the joint angle of multi-degrees-of-freedom relative motion 102B and filtering to remove non-tremulous motion from captured motion 102C. Each of these steps will be further elucidated in the following paragraphs.

Axes assignation for tremor motion classification

[0038] The system is used for assessing or quantifying tremor motion in accordance with the present invention will now be further elucidated using any arbitrary two adjacent segments and a joint. In a preferred embodiment, there is at least one sensing element positioned at each of the adjacent segments. The coordinate frames of the proximal and distal sensing devices are depicted as coordinate frames 1 201 and 2 202 respectively in FIG. 2. The two axes to be predefined for motion classification 102A are motion and indicator axes. The axes about which individual motions rotate are the motion axis. In the algorithm, the motion axis assumes one of the proximal axes, depending on the particular motion to be computed. The assumed axes are denoted as Mpnoxi where M indicates the motion axis and / ^' can be x, y or z axis. The term M _DISTALi refers to the distal motion axis parallel with the M _PROXi when the segments are in neutral position. The indicator axes are defined such that the angle between distal and proximal indicator axes is joint angle. IpRoxi ^an< i IDISTALI ^are the notation for the proximal and distal indicator axes IpRoxi- AH the axes assignation is important in the computation of the joint angle of multi-degrees-of-freedom relative motion.

[0039] The method and system of the present invention may be implemented for hand- arm tremor quantification, whereby an example of how the method is implemented is shown below as EXAMPLE 1.

EXAMPLE 1

Hand-arm Tremor Motion Assessment

[0040] In the event that the present invention is used for assessing hand-arm tremor motions, the step 101 of acquiring the sensing element data includes: detecting the motions of dorsum portion of the hand and sending signals based on the detection; detecting the motions of a distal portion of the lower arm and sending signals based on the detection; and detecting the motions of a distal portion of the upper arm and sending signals based on the detection. The motions are detected by sensing elements with which a data acquisition and signal processing system is connected for data logging and further processing for tremor assessment and analysis.

[0041] In the preferred embodiment and referring to FIG. 3, detecting the motions at several locations of the hand-arm or any joint of a subject can be achieved by various means. In an example, and as discussed in one of the preceding paragraphs, a plurality of sensing elements are attached or mounted on at least three locations, in particular segments of a subject's hand-arm areas. The locations include: dorsum of the hand, distal end of the lower arm and distal end of the upper arm. It is preferred that the sensing elements are mounted during the upper limb is in a neutral position, so as to record the values of the joint angle with reference to the neutral position. The said hand-arm neutral position refers to a position where the elbow is in full extension, neither pronated nor supinated; and no abduction-adduction nor flexion-extension of the wrist joint. An example of the sensing element that can be used is Attitude and Heading Reference System (AHRS). Suitably, the X K _{i 5} and Zj, axes of each AHRS or sensing element are the axes of the sensing elements' coordinate frames, as depicted in FIG. 3.

[0042] Classifying the tremor for hand-arm include classifying the detected motions into four motions i.e. wrist flexion-extension (WFE), wrist abduction-adduction (WAA), elbow flexion-extension (EFE) and elbow pronation-supination (Eps). From the detected AHRS orientations, preferably quaternion values are taken for the subsequent processing to obtain joint angular displacement for each of the aforesaid motions for further analysis of tremor.

Joint Angle of Multi-degrees-of-freedom Relative Motion [0043] The algorithm of computing the joint angle of multi-degrees-of-freedom relative motion 102B for obtaining the joint angle will be described based on a flowchart, as depicted in FIG. 4. At 401, the detected motions of hand-arm joints are subjected to an algorithm. The algorithm begins with the determination of the unit vectors of the motion axis, M and indicator axis, / 402; followed by the computation of the correction quaternion rotation, q _c 403; and the correction of the distal indicator axis 404 based on the q _c before computing the angles between the corrected distal indicator axes, I oiSTALi_correct ^an d the proximal indicator axis IpRoxi °f the joint 405.

[0044] From the step 402, the unit vectors of the motion and indicator axes for any joint motion can be obtained from the quaternion of each sensing element using the quaternion multiplication; whereby an example of the equation that may be applied is as below:

p' = qpq ^'1

Wherein; p is any three— dimensional vector p' is the new vector rotated by the sensing element quaternion q is the quaternion of the sensing element

qr ^_1 is the inverse or the conjugate of the sensing element quaternion [0045] In a preferred embodiment, the unit vectors, Xi , Y _t and Z _t of the motion and indicator axes are rotated from the orientation (1,0,0), (0,1,0) and (0,0,1)

respectively.

[0046] The X Y _t and Zj axes may be expressed in various ways. In an example for assessing hand-arm tremor, the X Yi and Z _t axes of the sensing elements are aligned on the upper limb in neutral posture in the predetermined directions as depicted in the coordinate frame in FIG. 3. The X _t axis points from proximal to distal part of the upper limb and aligned with middle finger, the Z _t axis points from the dorsal to palmar of the hand, and the axis is perpendicular to both X _t and Z _t axes.

[0047] Next is calculating the quaternion rotation correction 403, q _c . It should be noted that the q _c is calculated and required for the purpose of positioning the distal indicator axes IDISTAL _I to ^De on the same plane as the proximal indicator axes IpRoxi- Accordingly, the q _c is computed from the axis and angle of orientation rotation of the distal motion axis M _DISTALi to align with the proximal motion axis M _PR0Xi for each motion to be quantified. Next at step 404, the IDISTA is accordingly rotated based on the q _c , to obtain the corrected indicator axis of the distal sensing element, I DiSTALi_correct- ^m the preferred embodiment and referring to step 405, calculating the angles between the I DiSTAL correct ^ar >d IpRoxi results in the attainment of the multi- degrees-of-freedom joint angle.

Filtering to remove non-tremulous motion from captured motion

[0048] The multi-degrees-of-freedom joint angle is subjected to a filtering process 102C to obtain the joint angular displacement, i.e. the tremulous component. The filtering process is performed to remove the large non-oscillatory content of the data captured by the sensing element that may be caused by intended motion and some other unintended large motions; as well as high frequency sensing element signal noise. The filtering may be performed by a bandpass filtering device, for frequencies within the range of 3 to 30 Hz which covers all the possible tremor frequencies. This allows the present invention to be used to assess tremor when a subject is performing various actions which are of multi-degrees of freedom.

Further Analysis of tremor data

[0049] The method and system of the present invention may be used as tremor evaluation by clinicians and researchers. Accordingly, the computed joint angular displacement can be displayed in time series to study the change of tremor over recorded time for the onset and the subsidence of the tremor. The joint angular displacement can also be expressed in terms of root mean square (RMS) for ease of tremor severity comparison among the subjects and within individual for longitudinal study to monitor the progression of the tremor throughout a certain period of time. In another embodiment, a short-time Fourier transform (STFT) can be performed on the joint angular displacement for providing analysis of the change in the tremor frequency spectrum over time. This STFT is particularly useful for tremor assessment since tremor has a non-stationary nature, where the frequency contents are transient. [0050] From the foregoing, it would be appreciated that the present invention may be modified in light of the above teachings. It is therefore understood that, within the scope of the appended claims, the invention may be practiced otherwise than as specifically described.