FIELD OF THE INVENTION

The present invention relates to a haircare appliance.

BACKGROUND OF THE INVENTION

A haircare appliance may comprise a sensor for sensing the proximity of an object to the haircare appliance. However, the sensor is typically incapable of discriminating between hair and other objects.

SUMMARY OF THE INVENTION

According to a first aspect of the present invention, there is provided a haircare appliance comprising: a body for engaging hair in use; a sensor arrangement configured to output a plurality of signals, each signal being indicative of a presence of an object at a respective region of the body; and a control unit configured to determine whether the object is hair based on temporal differences between the signals.

This may allow for a reliable determination of whether an object engaging a body of a haircare appliance is hair. For example, hair detection based only on a signal associated with a single region of the body may be prone to returning false positives, i.e. prone to returning a determination that hair is present when in fact some other object is present, such as a table or a user’s hand. Sensing the presence of an object at multiple regions of the body independently may not significantly improve this situation. However, by determining whether an object is hair based on temporal differences between a plurality of signals each of which being indicative of a presence of an object at a respective region of the body, such false positives can be reduced or eliminated, i.e. it can be more reliably determined whether the object is hair. In particular, rather than a static evaluation of whether an object is hair, use of the temporal differences between the signals allows for the dynamics of the engagement of the object with the body to be incorporated into the determination. Since the dynamics of the engagement of hair with the body may be relatively specific, for example follow certain paths and/or move relative to the body at certain rates or with certain other characteristics, the specificity and reliability with which hair presence at the body can be determined may accordingly be improved. Improving the reliability of a determination of whether an object engaging a body of a haircare appliance is hair is in itself an advantage, but this may also, in turn, allow for numerous other benefits to be provided for, such as improved styling, improved energy efficiency, and improved product safety, as described in more detail below.

As mentioned, each signal is indicative of a presence of an object at a respective region of the body. In examples, each signal may be binary. For example, each signal may be logically low when an object is not present at the respective region and may be logically high when an object is present at the respective region. In other examples, each signal may be nonbinary, for example have a range or continuum of values. For example, the magnitude of amplitude of each signal may indicate the proximity of the object to the respective region or otherwise a degree to which the object is present at the respective region. In some examples, an object being present at a region may correspond to the object being in contact with the region. In other examples, the object being present at a region may correspond to the object being near or proximate to the region.

In some examples, a first signal of the plurality of signals changes in response to an object present at a first region of the body; a second signal of the plurality of signals changes in response to an object present at a second region of the body; and the control unit is configured to determine whether the object is hair based on a temporal difference between the changes in the first signal and the second signal.

It will be appreciated that, in some examples, more than two signals may be used. For example, each signal of the plurality of signals may change in response to an object present at a respective region of the body; and the control unit may be configured to determine whether the object is hair based on the temporal differences between the changes in the plurality of signals. For example, when an object becomes present at a region, the respective signal may increase in response. The dynamics with which hair becomes present at different regions of the body when the haircare appliance is in use may be reliably differentiated from that of other objects. Accordingly, basing the determination on temporal differences between changes that occur in response to an object being present at the respective regions may allow for reliable and/or robust determination of whether the object is hair. In some examples, the control unit is configured to determine, based on changes in the signals, a sequence in which an object becomes present at different respective regions of the body, and the control unit is configured to determine whether the object is hair based on the determined sequence. For example, the sequence in which the object becomes present at different respective regions may be inferred from the sequence in which the changes in the signals for the respective regions occur. In some examples, the sequence may comprise an order in which an obj ect becomes present at different regions and/or a time between an obj ect becoming present at different regions. Determining whether the object is hair based on the determined sequence may allow for the way in which hair is engaging with the body in use, and specifically the movement of hair relative to the body, to be incorporated into the determination. This may accordingly improve the reliability of the determination.

In some examples, the control unit is configured to determine that the object is hair responsive to the determined sequence corresponding to a predefined sequence. For example, the predefined sequence may be a sequence that has been measured or otherwise observed to occur when hair engages the body of the haircare appliance in use. In some examples, there may be a plurality of predefined sequences. Determining that the object is hair responsive to the determined sequence corresponding to a predefined sequence may allow, for example, for one or more ways in which hair is expected to engage or interact with body when the haircare appliance is in use to be incorporated into the determination. For example, if an object is engaging the body in a way that has been observed or is otherwise expected when the body engages hair, then the chances of the object being hair are relatively high, whereas if an object is engaging with the body in a way that is different to what has been observed or is otherwise expected when the body engages hair, then the chances of the object being hair are relatively low. This may reduce the possibility that the object is determined to be hair when the haircare appliance is in fact not engaging hair, and hence improve the reliability of the hair presence determination.

In some examples, the body comprises a curved portion and the regions are distributed so as to follow a curve of the curved portion. Certain haircare appliances such a styling wands, wraps and brushes may have a curved portion over or around which hair may be engaged in use. Hair may be formed of numerous relatively flexible strands which may accordingly readily follow a curve of the curved portion in use. Accordingly, having regions for which signals are output distributed so as to follow a curve of the curved portion may allow for the wrapping motion of hair along the curve to be encoded into the determination of whether the object is hair. Similarly to as above, this may improve the reliability of the determination.

In some examples, the curved portion has the shape of a cylinder or cone and the regions are distributed around a circumference of the cylinder or cone. This may allow for the degree to which an object is wrapped, or whether an object is fully wrapped, around the body to be encoded into the determination of whether the object is hair. Similarly to as above, this may improve the reliability of the determination.

In some examples, the sensor arrangement comprises a plurality of sensors, each sensor being located at a respective region of the body and being configured to output one of the plurality of signals. This may provide for a robust way to provide the plurality of signals. For example, each sensor may output a signal independently of the other sensors. This may for example allow a clear and reliable signal as to the presence of an object at each region. Moreover, this may allow for the determination as to whether the object is hair to be carried to be robust with respect to the failure of one of the sensors. In some examples, one or more of the sensors are non-contact sensors. For example, a non-contact sensor may be configured to output a signal indicative of an object being present at the sensor without the object necessarily coming into physical contact with the sensor itself. Examples of non-contact sensors include a capacitance sensor (e.g. either a self-capacitance sensor or a mutual capacitance sensor), a light sensor, and an ultrasonic sensor. In some examples, one or more of the sensors may be a contact sensor, i.e. one which is configured to output a signal indicative of an object being present at the sensor only when an object comes into physical contact with the sensor itself. Examples of contact sensors include touch sensors, force sensors, and pressure sensors. Another example of a contact sensor is an element coupled with a temperature sensor configured to measure the temperature of the element and whereby contact of an object with the element causes a change in the temperature of the element and thereby a change in a signal output by the temperature sensor. Other types of sensor may be used.

Non-contact sensors allow for determination of whether an object is hair even when the object is not physically touching the sensors. However, a haircare appliance using non- contact sensors to detect the presence of hair, and in particular one in which those sensors are positioned so as to sense into free space, may be particularly prone to false positives as hair could be erroneously detected even when the body is not touching any object. Accordingly, the present invention may be particularly effective in improving the reliability of hair presence detection for a haircare appliance which uses non-contact sensors.

In some examples, each signal comprises a temporal series of values or the control unit samples each signal as a temporal series of values, and each of the values is indicative of the degree to which an object is present at the respective region at a given time. This may allow for the determination to be readily carried out by a microcontroller or other computer processor, which may provide for a cheap, simple, flexible and/or low weight means by which to determine whether an object is hair. This is for example as compared to using hardwired circuit logic, which may nonetheless in some other examples be used.

In some examples, the control unit is configured to determine whether the object is hair based on temporal differences between the plurality of signals that occur within a given time window. This may allow the determination of whether the object is hair to be made for a specific time period. This may allow, for example, for the determination to be made periodically and/or repeatedly at successive times, which may in turn allow for the reliable updating of the determination as time progresses. Where each signal comprises or is sampled as a temporal series of values, the control unit may be configured to determine whether the object is hair based on values of the plurality of signals that occur within the given time window.

In some examples, the control unit is configured to: between successive determinations of whether the object is hair, move the given time window so as to include the most recent values and remove the oldest values of the plurality of signals. This may allow for the determination of whether the object is hair to be made in an efficient manner. For example, by including only the most recent values of the plurality of signals, the control unit can provide up-to-date hair presence determinations in relatively quick succession, while the processing and memory resource consumption by the control unit can be kept at or below an appropriate level. In some examples, the control unit is configured to determine whether the object is hair using a trained machine learning model. For example, the trained machine learning model may be or comprise a regression model. In some examples, the machine learning model may be a trained neural network, although other trained machine learning models may be used. In some examples, the control unit may be configured to: input the plurality of signals into the trained machine learning model to obtain an output, and determine whether the object is hair based on the output. For example, the trained machine learning model may have been trained to, based on an input of a plurality of such signals, output a determination of whether an object is hair. For example, the machine learning model may have been trained based on a training data set comprising a plurality of training data samples, each training data sample comprising a plurality of such signals and a label indicating whether an object associated with the plurality of signals is hair. In some examples the training data set may comprise positive training data samples comprising a plurality of such signals and a label indicating that the object associated with the plurality of signals is hair, and negative training data samples comprising a plurality of such signals and a label indicating that the object associated with the plurality of signals is not hair.

Using a trained machine learning model may allow for a reliable and/or flexible determination of whether the object is hair. For example, this may be as compared to applying a hard-coded algorithm to the plurality of input signals to determine whether the object is hair. For example, such a hard-coded algorithm or set of rules would be inflexible with respect to timings of changes in signals, which timings were not contemplated when the rules were written. However, the trained machine learning model may generalise from training samples on which it has been trained, and hence be more flexible with respect to such uncontemplated timings. As another example, using a hard-coded algorithm or set of rules would require the set of rules to be written, which is not only labour intensive but may necessarily involve assumptions on the way in which hair interacts with the body of the haircare appliance and may not account for the precise way in which hair interacts with the body. On the other hand, using a machine learning model, which for example may have been trained using training data including actual signal values for when it is known hair is engaging with the body (and e.g. for when hair is not engaging with the body, and/or for when the body is engaging something other than hair, such as a hand), may automatically encode the precise way in which hair actually interacts with the body in use, and hence may allow for a more reliable determination of whether the object is hair.

In some examples, the control unit is configured to: concatenate the values of each of the plurality of signals included in the given time window with one another, thereby to obtain an input for the machine learning model. This may allow for the time series of data to be converted into a column vector, which in turn may allow for the ready input of the plurality of signals in a given time window into a machine learning model, for example a neural network having an input layer in this format.

In some examples, the control unit is configured to control an operating mode of the haircare appliance in response to the determination. This may allow the haircare appliance to operate more precisely with respect to whether hair is engaging the body of the haircare appliance. For example, this may allow for improved styling or other functionality, improved energy saving, and/or improved product safety. For example, controlling the haircare appliance to operate in a styling mode (which may e.g. involve heating to a certain temperature and/or an airflow being expelled at a certain flow rate) precisely when hair is engaged with the body may allow for the more precise styling of hair. As another example, operating the appliance in an idle mode when it is not determined that hair is present and operating the appliance in a styling mode when it is determined that the object is hair, may allow for power consumption to be reduced as compared to the appliance being in the styling mode even when not engaging hair. As another example, operating the appliance at a lower temperature when it is determined the object is not hair and operating the appliance at a higher temperature when it is determined the object is hair, may allow for the reduction of risk of a user accidently burning themselves or other objects e.g. when the appliance is not actively being used to style hair. As another example, operating the appliance to expel or generate an airflow having a lower flow rate when it is determined the object is not hair and operating the appliance to expel or generate an airflow having a higher flow rate when it is determined the object is hair, may allow for the reduction of risk of a user inadvertently directing airflow at an unintended object.

In some examples, the control unit may comprise a controller that is configured to both determine whether the object is hair and, in response, control the operating mode of the haircare appliance. In other examples, the control unit may comprise a first controller configured to determine whether the object is hair, a second controller configured to control the operating mode of the haircare appliance. In this latter case, the first controller may be configured to output, for example to the second controller, a signal indicative of the result of the determination of whether the object is hair.

In some examples, the haircare appliance expels an airflow, and the control unit is operable to control one or more of a flow rate and a temperature of the airflow in response to the determination. Similarly to as mentioned above, this may allow for improved styling or other functionality, improved energy efficiency, and/or improved product safety.

In some examples, the control unit is configured to: operate the haircare appliance in a first mode in response to determining that the object is not hair; and operate the haircare appliance in a second mode in response to determining that the object is hair, wherein operation in the first mode consumes a lower electrical power than operation in the second mode. Similarly to as mentioned above, this may allow for improved energy efficiency. Improving energy efficiency (e.g. reducing overall energy consumption) may be particularly important in battery operated appliances, which have a limited energy storage capacity. As such these features may allow for an improved run-time of the device, and/or for a smaller battery to be used, which may reduce the weight of the appliance.

In some examples, the haircare appliance comprises a heater, and the control unit is configured to operate the heater at a first temperature in the first mode and to operate the heater at a second temperature in the second mode, the second temperature being greater than the first temperature. Similarly to as mentioned above, this may allow for improved styling or other functionality, improved energy efficiency, and/or improved product safety.

In some examples, the haircare appliance comprises an air inlet, an air outlet, and an air flow generator for generating an airflow from the air inlet to the air outlet, and the control unit is configured to operate the airflow generator at a first flow rate in the first mode and to operate the airflow generator at a second flow rate in the second mode, the second flow rate being greater than the first flow rate. Similarly to as mentioned above, this may allow for improved styling or other functionality, improved energy efficiency, and/or improved product safety. According to a second aspect of the present invention, there is provided a control unit for a haircare appliance, the control unit configured to: receive a plurality of signals, each signal being indicative of a presence of an object at a respective region of a body of the haircare appliance; and determine whether the object is hair based on temporal differences between the signals. This may allow for similar advantages to as described above for the first aspect. In some examples the control unit may be the same as described above with reference to the first aspect. In some examples, the control unit may be located in a main part, for example a handle, of a haircare appliance. In some examples, the signals may be received from an attachment, for example an attachment that includes the body, which attachment is attachable to and/or detachable from the main part. This may allow for improved flexibility in the functioning of the haircare appliance. The signals may be received wirelessly or over wires or conductive tracks, for example.

According to a third aspect of the present invention, there is provided a method of determining whether hair is present at a body of a haircare appliance, the method comprising: receiving a plurality of signals, each signal being indicative of a presence of an object at a respective region of the body; and determining whether the object is hair based on temporal differences between the signals. This may allow for similar advantages to as described above for the first aspect. In some examples, the method may be performed by a control unit of a haircare appliance. In other examples, the method may be performed by a separate entity for example remotely from the haircare appliance. For example, the signals may be transmitted to and received by a remote processor, and the determination may be made by the remote processor. In some examples, the result of the determination may be transmitted to and received by the haircare appliance, which may in turn, for example, control an operating mode on the basis of the determination.

BRIEF DESCRIPTION OF THE DRAWINGS

Further features and advantages will now be described, by way of example only, with reference to the accompanying drawings of which:

Figure l is a schematic diagram that illustrates a side view of a haircare appliance according to an example; Figure 2 is a schematic diagram that illustrates a perspective view of a body of a haircare appliance according to an example;

Figure 3 is a schematic diagram that illustrates the engagement of hair with a body of the haircare appliance over time, according to an example;

Figure 4 is a schematic diagram that illustrates a plot of signal value output as a function of time for a plurality of signals corresponding to a respective plurality of regions of a body of a haircare appliance, according to an example;

Figure 5 is a schematic diagram that illustrates a plot of signal value as a function of element number of a column vector that can be used as an input to a machine learning model, according to an example;

Figures 6a and 6b are schematic diagrams that illustrate a perspective view and a side view, respectively, of a body of a haircare appliance according to an another example;

Figure 7 is a schematic diagram that illustrates a control unit according to an example; and Figure 8 is a schematic diagram that illustrates a method of determining whether hair is present at a body of a haircare appliance, according to an example.

As used herein, like reference numerals denote like features.

DETAILED DESCRIPTION OF THE INVENTION

Referring to Figure 1, there is illustrated a haircare appliance 102 according to an example.

The haircare appliance 102 comprises a body 104 for engaging hair in use (hair is not shown in Figure 1 but see e.g. the hair tress 354 in Figure 3 described below). The body 104 comprises a plurality of regions A, B, C. The haircare appliance 102 comprises a sensor arrangement 128. The sensor arrangement 128 is configured to output a plurality of signals, each signal being indicative of a presence of an object at a respective region A, B, C of the body 104 (an object is not shown in Figure 1, but see e.g. the hair tress 354 in Figure 3 described below). The haircare appliance 102 comprises a control unit 122. As described in more detail below, the control unit 122 is configured to determine whether the object 354 is hair based on temporal differences between the signals.

In this example, the haircare appliance 102 comprises a main part 106 and the body 104 is provided as an attachment 104 that is attachable and/or detachable from the main part 106. The main part 106 comprises an airflow generator 124 and a heater 126. The airflow generator 124 is configured to generate an airflow from an air inlet 120 to an air outlet 123. In this example, the air inlet 120 is in the main part 106, and the air outlet 123 is in the body 104. The heater 126 is located downstream of the airflow generator 124. The heater 126 may be configured to heat the airflow so as to provide a heated airflow at the air outlet 123. The body 104 of this example is shown in more detail in Figure 2. In this example, the body 104 is generally in the form of a cylinder or a cone. In this example, each region A, B, C corresponds to an elongate member. In this example these regions/members A, B, C are distributed around a circumference (see 213 in Figure 2) of the cylinder or cone forming the body 104. In this example, an air outlet 123 is provided by a gap in between each member A, B, C which directs airflow across the surface of an adjacent member A, B, C. As is known per se, in use, the airflow expelled from these air outlets 123 causes, via the Coanda effect, hair, or more specifically a hair tress 354, in the vicinity of the body 104 to wrap around the body 104, where it can be styled. In some examples, the control unit 122 may be configured to control an operating mode of the haircare appliance 102, for example control one or more of a flow rate and a temperature of the airflow, for example control a flow rate of the airflow generated by the airflow generator 124 and/or control a temperature at which the heater 126 is operated. In some examples, the control unit 122 may be configured to control the operating mode in response to the determination that the object 354 is hair. As explained in more detail below, this may allow for improved styling, improved energy efficiency, and/or improved product safety of the haircare appliance 102.

As mentioned, the haircare appliance 102 comprises a sensor arrangement 128 configured to output a plurality of signals, each signal being indicative of a presence of an object at a respective region A, B, C of the body 104. In this example, the sensor arrangement 128 comprises a plurality of sensors 114, 116, 118, each sensor 114, 116, 118 being located at a respective region A, B, C of the body 104 and being configured to output one of the plurality of signals. In this example, each sensor 114, 116, 118 is positioned so as to sense radially outwardly from the body 104 (i.e. radially outwardly of the region A, B, C to which the sensor corresponds). In some examples, one or more of the sensors 114, 116, 118 may be non-contact sensors. For example, a non-contact sensor may be configured to output a signal indicative of an object 354 being present at the sensor 114, 116 118 without the object 354 necessarily coming into physical contact with the sensor 114, 116, 118 itself. Examples of non-contact sensors include a capacitance sensor (e.g. either a self-capacitance sensor or a mutual capacitance sensor), a light sensor, and an ultrasonic sensor. Non-contact sensors may allow for determination of whether an object is hair even when the object is not physically touching the sensors. In other examples, one or more of the sensors 114, 116, 118 may be a contact sensor, i.e. one which is configured to output a signal indicative of an object 354 being present at the sensor 114, 116, 118 only when an object comes into physical contact with the sensor itself. Examples of contact sensors include touch sensors (e.g. capacitance sensors or resistance sensors), force sensors, and pressure sensors. Another example of a contact sensor is an element coupled with a temperature sensor configured to measure the temperature of the element and whereby contact of an object with the element causes a change in the temperature of the element and thereby a change in a signal output by the temperature sensor. Other types of sensor may be used. In some examples, one or more of the sensors 114, 116, 118 may be any sensor whose output is affected by the presence of hair, which allows for a high flexibility for product integration. For example, where the regions are heated, a sensor resistant to high temperature may be chosen (such as the heated element coupled with a temperature sensor described above).

In some examples, each signal may be non-binary, for example have a range or continuum of values. For example, the magnitude or amplitude of each signal may indicate the proximity of the object 354 to the respective region A, B, C or otherwise a degree to which the object 354 is present at the respective region A, B, C. In other examples, each signal may be binary. For example, each signal may be logically low when an object 354 is not present at the respective region A, B, C and may be logically high when an object 354 is present at the respective region A, B, C. In some examples, the object 454 being present at a region A, B, C may correspond to the object 354 being near or proximate to the region A, B, C. In other examples, an object 354 being present at a region may correspond to the object 354 being in contact with the region A, B, C.

The sensor arrangement 128 may be connected to the control unit 122 by wired or wireless means, in order to provide the plurality of signals to the control unit 122. In examples where the body 104 is provided by an attachment and the control unit 122 is in the main part 106, the body 104 and the main part 106 may form a connection, which may be wired or wireless, over which the signals may be transmitted from the sensor arrangement 128 to the control unit 122. In some examples, the sensor arrangement 128 may comprise the sensors 114, 116, 118 and the signals output by each sensor may be provided directly to the control unit 122 as the plurality of signals. In other examples, the sensor arrangement 128 may comprise the sensors 114, 116, 118 and a multichannel reader (not shown), and the plurality of signals may be provided to the control unit 122 by the multichannel reader (not shown). For example, the multichannel reader may sample each of the signals output by the sensors as a temporal series of values and provide these temporal series of values to the control unit 122 as the plurality of signals. In any case, the sensor arrangement 128 is configured to output a plurality of signals, each signal being indicative of a presence of an object at a respective region A, B, C of the body 104.

Referring to Figures 3 and 4, Figure 3 illustrates the way in which hair, or more specifically a hair tress 354, may wrap around the cylindrical body 104 of the haircare appliance 102 according to the example of Figure 1 at different successive times Tl, T2, T3, T4; and Figure 4 illustrates a plot of the plurality of signals sA, sB, sC, sD, sE, sF output by the sensor arrangement 128 for a respective one of the plurality of regions A, B, C, D, E, F of the body 104, as a function of time, according to an example. It is noted that regions D, E, F (and their associated sensors) are present on the body 104 illustrated in Figures 1 and 2, but are not visible in Figures 1 and 2. As can be seen from Figures 3 and 4, the regions A to F are distributed around the circumference of the cylindrical body 104 in the order A, B, C, D, E, F. In this example, the larger the degree to which an object 454 is present at a given one of the regions A-F, the larger the signal sA-sF that is output corresponding to that given region A-F.

At time Tl, the hair tress 354 is present at regions A and B, but not at regions C to F. Accordingly, at time Tl, the values of the signals sA and sB have increased, but the those of the other signals sC to sF have not. At a later time T2, the hair tress 354 has wrapped further around the body 104, and is now present at regions A to C, but not at regions D to F. Accordingly, at time T2, the values of the signals sA to sC have increased, but those of the other signals sD to sF have not. At a still later time T3, the hair tress 354 has wrapped still further around the body, and is now present at regions A to D, but not at regions E and F. Accordingly, at time T3, the values of the signals sA to sD have increased, but those of the other signals sE to sF have not. At a yet still later time T4, the hair tress 354 has wrapped yet still further around the body 104, and is now present at regions A to F. Accordingly, at time T4, the values of the signals sA to sF have all increased.

As mentioned, the control unit 122 is configured to determine whether the object 354 is hair based on temporal differences between the signals sA-sF output by the sensor arrangement 128. Temporal differences may be considered as differences between the signals that occur over a period of time and may for example be contrasted with purely static or instantaneous differences. For example, as illustrated above in Figures 3 and 4, each signal of the plurality of signals sA-sF may change (e.g. a value of the signal may increase) in response to an object 454 being present at a respective region A, B, C of the body. The control unit 122 may be configured to determine whether the object 454 is hair based on the temporal differences between these changes in the plurality of signals sA-sF. For example, the temporal difference between two signals may comprise or be based on a time at which a change in one signal (e.g. an increase in the value of one signal) occurs relative to a time at which a change in the other signal (e.g. an increase in the value of the other signal) occurs. For example, the temporal difference between signals may comprise differences in the time at which each change occurred relative to the other changes (which may for example be expressed as a sequence or time-order in which the changes in signals occur), a time in between each change and/or other time-related differences. For example, based on the sequence in which the changes in the signals occur, the time in between each change and/or other temporal differences between the signals, the control unit 122 may determine whether the object 354 is hair. For example, when the temporal differences between the signals output by the sensor arrangement 128 correspond to temporal differences known or expected to occur when hair is engaging the body 104 (e.g. as illustrated in Figure 3), the control unit 122 may determine that the object 354 is hair. For example, when changes in the signals correspond to those which would occur when an object wraps around the circumference 213 of the body, the control unit 122 may determine that the object is hair. It is noted that in the schematic diagram of Figure 4 the signals sA to sF are shown as increasing to a similar value but it will be appreciated that this need not necessarily be the case and that the signals may in principle increase by different amounts but that the control unit 122 may nonetheless determine whether the object is hair based no temporal differences between the signals. Use of the temporal differences between the signals allows for the dynamics of the engagement of the object 354 with the body 104 to be incorporated into the determination by the control unit 122 of whether the object 354 is hair. Since the dynamics of the engagement of hair 354 with the body 104 may be relatively specific, for example follow certain paths and/or move relative to the body 104 at certain rates or with certain other characteristics, the specificity and reliability with which hair presence at the body 104 can be determined may accordingly be improved. Improving the reliability of a determination of whether an object 354 engaging a body of a haircare appliance is hair is in itself an advantage, but this may also, in turn, allow for numerous other benefits to be provided for, such as improved styling, improved energy efficiency, and improved product safety, as described in more detail below.

As mentioned, in some examples, each signal of the plurality of signals sA-sF may change in response to an object 354 present at a respective region A, B, C of the body; and the control unit 122 may be configured to determine whether the object 354 is hair based on the temporal differences between the changes in the plurality of signals. The dynamics with which hair 354 becomes present at different regions A, B, C of the body when the haircare appliance 102 is in use may be reliably differentiated from that of other objects. Accordingly, basing the determination on temporal differences between changes in the signals that occur in response to an object being present at the respective regions A, B, C may allow for reliable and/or robust determination of whether the object is hair.

In some examples, the control unit 122 is configured to determine, based on changes in the signals, a sequence in which an object 354 becomes present at different respective regions A-F of the body 104, and the control unit 122 is configured to determine whether the object 354 is hair based on the determined sequence. For example, the sequence in which the object 354 becomes present at different respective regions may be inferred from the sequence in which the changes (e.g. increases) in the signals for the respective regions A-F occur. For example, a change (e.g. an increase) in the signal for respective regions A, B, C, D may occur at times tA, tB, tC, tD respectively, and for example in the case that tD>tC>tB>tA, it can be inferred that an object 354 becomes present at the respective regions in the order A, B, C, D. Moreover from the difference in time between tA, tB, tC, tD the difference in time between the object becoming present at the regions A, B, C, D respectively can be inferred. In some examples, an object may be determined as becoming present at a given region A, B, C, D when the corresponding signal sA, sB, sC, sD increases to above a threshold value.

In some examples, the sequence in which an object 354 becomes present at different respective regions A-F of the body 104 may comprise an order in which the object 354 becomes present at different regions A, B, C, D and/or a time between an object 354 becoming present at different regions A, B, C, D. Determining whether the object is hair based on the determined sequence may allow for the way in which hair is engaging with the body 104 in use, and specifically the movement of hair 354 relative to the body 104, to be incorporated into the determination of whether the object is hair 354. This may accordingly improve the reliability of the determination.

In some examples, the control unit 122 is configured to determine that the object 354 is hair responsive to the determined sequence corresponding to a predefined sequence. For example, the predefined sequence may be a sequence that has been measured or otherwise observed to occur when hair 354 engages the body 104 of the haircare appliance 102 in use. In some examples, there may be a plurality of predefined sequences. Determining that the object is hair responsive to the determined sequence corresponding to a predefined sequence may allow, for example, for one or more ways in which hair is expected to engage or interact with body 104 when the haircare appliance 102 is in use to be incorporated into the determination of whether the object is hair. For example, if an object 354 is engaging the body 104 in a way that has been observed or is otherwise expected when the body 104 engages hair 354, then the chances of the object 354 being hair are relatively high, whereas if an obj ect is engaging with the body 104 in a way that is different to what has been observed or is otherwise expected when the body 104 engages hair 354, then the chances of the object being hair are relatively low. This may reduce the possibility that the object is determined to be hair when the haircare appliance 102 is in fact not engaging hair, and hence improve the reliability of the hair presence determination. For example, the predefined sequence may comprise an order in which hair becomes (and e.g. remains) present at different regions A, B, C and/or a time in between an object becoming present at different respective regions. For example, a predefined order for the body 104 of the example of Figures 1, 2, 4 and 5 may be A, B, C, D, E, F (or indeed B, C, D, E, F, A; C, D, E, F, A, B; D, E, F, A, B, C; E, F, A, B, C, D; F, A, B, C, D, E; or part of any one of those sequences) which follows in sequential order the path that hair is expected to follow when it wraps around the body 104. As another example, the predefined time in between the object becoming present at different regions may be the condition that tB occurs within a predetermined time range relative to tA, and tC occurs within a predetermined time range relative to tB etc.; or for example that tA, tB, and tC all occur within a certain time of one another.

In some examples, each signal comprises a temporal series of values or the control unit 122 may sample each signal as a temporal series of values, and each of the values is indicative of the degree to which an object 354 is present at the respective region A-F at a given time. This may allow for the determination by the control unit 122 to be readily carried out by a microcontroller or other computer processor, which may provide for a cheap, simple, flexible and/or low weight means by which to determine whether an object is hair. This is for example as compared to using hardwired circuit logic, which as mentioned below may nonetheless in some other examples be used.

In some examples, the control unit 122 may be configured to determine whether the object 354 is hair by applying an algorithm to the plurality of signals. In some examples, the algorithm may be implemented by a computer program executing on a processor such as a microcontroller. In other examples, the algorithm may be implemented by control logic circuitry. In either case algorithmic logic may be applied to the plurality of signals to determine whether or not the object is hair based on temporal differences between the signals. For example, the signals associated with respective regions A, B, C may be monitored and a change (e.g. an increase) in the signal value may be observed at respective times tA, tB, tC. A logic may be applied that if these changes occurred in a certain temporal order or sequence (e.g. tA>tB>tC, or tOtB>tC) and/or the difference in time between the times tA and tB, and/or tB and tC is within a certain range, then the object is determined as hair, otherwise the object is determined as not hair. Other algorithmic logic may be applied.

In some examples, the control unit 122 may use other means to determine whether the object 354 is hair based on temporal differences between the signals. For example, the determination of whether the object 354 is hair may be made using a trained machine learning model, e.g. by inputting the plurality of signals into a trained machine learning model which outputs the determination based on the input signals. For example, values representing each of the plurality of signals as a function of time may be input together into the machine learning model, which may, using an inferred function derived from its training, map these input values onto a determination of whether or not the object is hair.

In some examples, the control unit 122 is configured to determine whether the object is hair based on temporal differences between the plurality of signals that occur within a given time window (see e.g. the time window 456 of Figure 4). This may allow the determination of whether the object is hair to be made for a specific time period. This may allow, for example, for the determination to be made periodically and/or repeatedly at successive times, which may in turn allow for the reliable updating of the determination as time progresses. Where each signal comprises or is sampled as a temporal series of values, the control unit 122 may be configured to determine whether the object is hair based on values of the plurality of signals that occur within the given time window 456. As an example, the time window 456 may be on the order of 1 or 2 seconds, for example 1.5 seconds. Each signal may comprise or be sampled as a temporal series of values where the time between each value in the series is 125ms. In the example where the time window 456 is 1.5 second, the time window 456 will accordingly include the signal values of each of the plurality of signals at 13 different moments in time.

In some examples, the control unit 122 is configured to: between successive determinations of whether the object 354 is hair, move the given time window 456 so as to include the most recent values and remove the oldest values of the plurality of signals. This may allow for the determination of whether the object 354 is hair to be made in an efficient manner. For example, by including only the most recent values of the plurality of signals, the control unit can provide up-to-date hair presence determinations in relatively quick succession, while the processing and memory resource consumption by the control unit 122 can be kept at or below an appropriate level. As an example, every 125 ms the oldest values of the signals are removed and the newest values of the signals are added. Between each successive determination, the time window 456 may be moved on by 125 ms. Other example time windows and sampling rates may be used.

In examples where each signal comprises or is sampled as a temporal series of values, and where the control unit 122 is configured to determine whether the object 354 is hair using a trained machine learning model, the control unit 122 may be configured to concatenate the values (of the temporal series of values) of each of the plurality of signals sA-sF included in the given time window 456 with one another, thereby to obtain an input for the machine learning model. This may allow for the time series of data to be converted into a column vector, which in turn may allow for the ready input of the plurality of signals in a given time window into a machine learning model, for example a neural network having an input layer in this format.

For example, a column vector may be formed where the first six entries or elements are the signal values for each of the six signals sA-sF at the earliest sample time included in the given time window 456, the following six entries are the signal values for each of the six signals sA-sF at the second earliest sample time included in the given time window 456, and so on until the last six entries are the signal values for each of the six signals aS-sF at the latest sample time included in the given time window 456. In the case of the given time window 456 including 13 sample times, this would result in a column vector with 78 elements. Referring to Figure 5, there is a shown a plot 560 illustrating the signal value of each element of the column vector as a function of element number or position in the column vector, according to an example. As can be seen, the values, and their position within the column vector, encode the changes in the signals sA-sF occurring as a function of time within the given time window 456, and as such encode the temporal differences between those signals. The conversion of the plurality of signals into this format may provide for the ready input of the plurality of signals into a machine learning model, for example a neural network having an input layer in this format (e.g. a neural network having 78 nodes in its input layer).

In some examples, the machine learning model may be a trained neural network, although other trained machine learning models may be used. In some examples, the trained machine learning model may be or comprise a regression model. In examples where the trained machine learning model comprises a neural network, the neural network may comprise an input layer, one or more hidden layers, and an output layer. In some examples, the output layer may comprise a classifier configured to classify a given input as either relating to a situation where the object is hair or relating to a situation where the object is not hair. In some examples, the control unit 122 may be configured to input the plurality of signals into the trained machine learning model to obtain an output, and determine whether the object 354 is hair based on the output. For example, the input may be in the column vector format as described above with reference to Figure 5. The output may be a classification (e.g. as output by a classifier) of a given input either representing that the object is hair or not representing that the object is hair. The determination of whether the object is hair may be based on this classification, for example, the determination may be taken as the classification result.

The trained machine learning model may have been trained to, based on an input of a plurality of such signals, output a determination of whether an object 354 is hair. For example, the machine learning model may have been trained based on a training data set comprising a plurality of training data samples, each training data sample comprising a plurality of such signals (e.g. in a column vector format as described above) and a label indicating whether an object 354 associated with the plurality of signals is hair. In some examples the training data set may comprise positive training data samples comprising a plurality of such signals and a label indicating that the object associated with the plurality of signals is hair 354, and negative training data samples comprising a plurality of such signals and a label indicating that the object associated with the plurality of signals is not hair, such as a hand or a table. The training may comprise optimising a loss function between the determination output by the model and the label associated with each training data sample.

Using a trained machine learning model may allow for a reliable and/or flexible determination of whether the object 354 is hair. For example, this may be as compared to applying a hard-coded algorithm to the plurality of input signals to determine whether the object is hair. For example, such a hard-coded algorithm or set of rules would be inflexible with respect to timings of changes in signals that were not contemplated when the rules were written. However, the trained machine learning model may generalise from training samples on which it has been trained, and hence be more flexible with respect to such uncontemplated timings. As another example, using a hard-coded algorithm or set of rules would require the set of rules to be written, which is not only labour intensive but may necessarily involve assumptions on the way in which hair 354 interacts with the body 104 of the haircare appliance and may not account for the precise way in which hair interacts with the body 104. On the other hand, using a trained machine learning model, which for example may have been trained using training data including actual signals for when it is known hair is engaging with the body (and e.g. for when hair is not engaging with the body, and/or for when the body is engaging something other than hair, such as a hand), may automatically encode the precise way in which hair actually interacts with the body 104 in use, and hence may allow for a more reliable determination of whether the object 354 is hair.

In the example described above with reference to Figures 1 to 5, the body 104 comprises a curved portion and the regions A, B, C are distributed so as to follow a curve 213 of the curved portion. Specifically, in this examples, the body 104 has the general shape of a cylinder, and the regions A - F are distributed around a circumference 213 of the cylinder. As mentioned, when the haircare appliance 102 is used to style hair in this example, hair may be engaged over or around the body 104, for example may wrap around the circumference 213 of the body 104, in order to be styled. Hair may be formed of numerous relatively flexible strands which may accordingly readily follow the curve 213 of the curved portion in use. Accordingly, having regions A-F for which the signals are output distributed so as to follow a curve 213 of the curved portion may allow for the wrapping motion of hair along the curve 213 to be encoded into the determination of whether the object 354 is hair. This may improve the reliability of the determination of whether the object is hair 354. In this example, the curved portion 213 has the shape of a cylinder or cone and the regions A- F are distributed around the circumference 213 of the cylinder or cone. This may allow for the degree to which an object 354 is wrapped, or whether an object 354 is fully wrapped, around the body 104 to be encoded into the determination of whether the object 354 is hair. This may improve the reliability of the determination.

In some examples, the control unit 122 may be configured to control an operating mode of the haircare appliance 102 in response to the determination of whether the object 354 is hair. This may allow the haircare appliance 102 to operate more precisely with respect to whether hair is engaging the body 104 of the haircare appliance 102. For example, this may allow for improved styling or other functionality, improved energy saving, and/or improved product safety. For example, controlling the haircare appliance 102 to operate in a styling mode (which may e.g. involve heating the heater 126 to a certain temperature and/or an airflow being generated by the airflow generator 124 at a certain flow rate) precisely when hair is engaged with the body 104 may allow for the more precise styling of hair. As another example, operating the appliance 102 in an idle mode when it is not determined that the object is hair and operating the appliance 102 in a styling mode when it is determined that the object is hair, may allow for power consumption to be reduced as compared to the appliance 102 being in the styling mode even when not engaging hair. As another example, operating the heater 126 at a lower temperature when it is determined the object is not hair and operating the heater 126 at a higher temperature when it is determined the object is hair, may allow for the reduction of risk of a user accidently burning themselves or other objects e.g. when the appliance is not actively being used to style hair. As another example, operating the airflow generator 124 to generate an airflow having a lower flow rate when it is determined the object is not hair and operating the airflow generator 124 to generate an airflow having a higher flow rate when it is determined the object is hair, may allow for the reduction of risk of a user inadvertently directing airflow at an unintended object.

In some examples, the control unit 122 may comprise a controller that is configured to both determine whether the object is hair and, in response, control the operating mode of the haircare appliance. In other examples, the control unit may comprise a first controller (not shown) configured to determine whether the object 354 is hair, and a second controller (not shown) configured to control the operating mode of the haircare appliance 102. In this latter case, the first controller (not shown) may be configured to output, for example to the second controller (not shown), a control signal indicative of the result of the determination of whether the object is hair.

As mentioned, the haircare appliance 102 expels an airflow, and the control unit 122 may be operable to control one or more of a flow rate and a temperature of the airflow in response to the determination. In some examples, the control unit 122 is configured to: operate the haircare appliance 102 in a first mode in response to determining that the object is not hair; and operate the haircare appliance 102 in a second mode in response to determining that the object is hair, wherein operation in the first mode consumes a lower electrical power than operation in the second mode. For example, the control 122 unit may be configured to operate the heater 126 at a first temperature in the first mode and to operate the heater 126 at a second temperature in the second mode, the second temperature being greater than the first temperature. As another example, the control unit 122 may be alternatively or additionally configured to operate the airflow generator 124 at a first flow rate in the first mode and to operate the airflow generator 124 at a second flow rate in the second mode, the second flow rate being greater than the first flow rate. Similar to that mentioned above, this may allow for improved styling or other functionality, improved energy efficiency, and/or improved product safety. Improving energy efficiency (e.g. reducing overall energy consumption) may be particularly important in battery operated appliances, which have a limited energy storage capacity. As such these features may allow for an improved run-time of the device, and/or for a smaller battery to be used, which may reduce the weight of the appliance.

In the examples described above with reference to Figures 1 to 5, each region A-F corresponds to one section or fin of the body 104, and there is accordingly one sensor 114, 116, 118 associated with each fin. However, it will be appreciated that this need not necessarily be the case, and that in some examples each fin may comprise multiple, e.g. 2, regions (not shown) for each of which the sensor arrangement 128 may be configured to output a respective signal. Accordingly, in some examples, each fin may comprise multiple, e.g. 2 sensors (not shown). Nonetheless, in a manner similar to as described above, the control unit 122 may determine whether the object is hair based on temporal differences between the signals.

In the examples described above with reference to Figures 1 to 5, the body 104 of the haircare appliance 102 was in the form of a cylinder or cone and the regions were distributed around the circumference of the cylinder 213. However, it will be appreciated that this need not necessarily be the case, and that in other examples, other forms of the body and other distributions of the regions of the body may be used. For example, referring to Figures 6a and 6b, there is illustrated a body 604 according to another example. The body 604 of Figures 6a and 6b may be used in place of the body 104 described above with reference to Figures 1 to 5. It will be appreciated that in other examples, other bodies may be used instead of the illustrated examples.

The body 604 illustrated in Figures 6a and 6b may have the same or similar features and functionality to the body 104 described above with reference to Figures 1 to 5, the main difference being that in this example the body 604 is a brush. The brush 604 comprises brushing zone 622 incorporating bristles 633. As best seen in Figure 6b (where the bristles 633 are not shown), the brushing zone 632 is separated into a plurality of regions A’, B’, C’, D’, and E’. The body 604 comprises a sensor arrangement 628 configured to output a plurality of signals, each signal being indicative of a presence of an object at a respective region A’-E’ of the body. Specifically, the sensor arrangement 628 comprises five sensors 646, 644, 638, 650, 652 which are located respectively at the regions A’, B’, C’, D’, and E’. The regions A’-E’ are distributed on the brushing zone 622 in three adjacent columns, the left most column having regions A’ and B’ stacked on top of one another, the middle row having region C’ located in a central portion of the brushing zone 632, and the right most row having regions D’ and E’ stacked on top of one another. This distribution may allow that there are regions A’-E’ located relative to one another across the brushing zone 632 from one side to the other (e.g. B’ and D’; A’ and E’); regions A’-E’ located relative to one another across the brushing zone 632 from the top of the brushing zone 632 to the bottom (e.g. regions B’ and A’; and D’ and E’); and regions A’-E’ located relative to one another diagonally across the brushing zone 632 (e.g. regions B’, C’, E’; and regions A’, C’, and D’). The brushing zone 632 is curved in one plane. Accordingly, some of the regions are distributed so as to follow a curve 605 of the body 604 (e.g. regions B’ and D’). However, other regions are distributed so as to follow a non-curved part of the body 304 (e.g. regions D’ and E’ relative to one another). The region distribution may allow that, regardless of the direction in which the brush 604 is moved relative to hair in use, a determination of whether an object is hair may nonetheless be made on the basis of temporal differences between a plurality of the signals. In other words, this region distribution may account for the different paths that hair may follow over the brushing zone 632 when the brush 604 is in use.

Similar to that described above, the control unit 122 may be configured to determine whether the an object is hair based on temporal differences between (two or more of) the signals output by the sensor arrangement 328. In some examples, the control unit 128 may first determine which of the bodies 104, 604 is attached to the main part 106, and the determination of whether the object is hair may be based additionally on this determination. This may allow the control unit 122 to determine which algorithm, for example which trained machine learning model (e.g. one which has been trained based on training data gathered from the cylindrical body 104 or one which has been trained based on training data gathered from the brush body 604) to apply to the plurality of signals in order to determine whether the object is hair.

In the examples described above with reference to Figures 1 to 6, the body 104, 604 is attachable to the main part 106 of the haircare appliance, but it will be appreciated that this need not necessarily be the case and that in some examples the body 104, 604 may be integral to the haircare appliance 102.

In the examples described above with reference to Figures 1 to 6, the haircare appliance 102 included a heater 126 and an airflow generator 124 but it will be appreciated that this need not necessarily be the case and that in some examples the haircare appliance 102 may not include one or either of these. For example, the hair care appliance may, in some examples, be a styling wand or hair straighteners or another haircare appliance which does not necessarily include an airflow generator. As another example, the haircare appliance may not necessarily include a heater or an airflow generator but may, for example, comprise a body which dispenses a hair product or treatment or other medium onto the hair. The reliable determination of whether an object is hair may in these examples allow for a reliable dispensing of the medium onto the hair, which may improve styling performance, medium use efficiency and/or product safety.

In the examples described above with reference to Figures 1 to 5 there were 6 regions A-F and in the example described above with reference to Figure 6 there were 5 regions A’-E’ however it will be appreciated that this need not necessarily be the case and that in some examples any number of regions (i.e. 2 or more regions, i.e. a plurality of regions) may be used.

In examples described above with reference to Figures 1 to 6 at least some of the regions A- F were distributed along a curve 213, 605 of a curved portion of the body 104, 604, but it will be appreciated that this need not necessarily be the case and that in other examples the regions may be distributed so as to follow a non-curved portion of the body, for example the regions may all lie in a plane. For example, this may be the case where the body comprises heating elements of a hair straightener comprising planar heating plates. In the examples described above with reference to Figures 1 to 6, an example was given of determining that an object 354 is hair based on temporal differences between changes, specifically increases, in the plurality of signals. However, it will be appreciated that in some examples, the control unit 122 may, having determined that the object 354 is hair, determine that the hair 354 is no longer present at or engaging with the body 104, 604 of the haircare appliance 102. For example, this determination may be made when one or more or all of the plurality of signals indicate that that an object is no longer present at the respective regions of the body 104, 604, for example when one or more or all of the plurality of signals reduce to below a certain value or become logically low. In some examples, the control unit 122 may be configured to, responsive to a determination that the object determined as hair is no longer present at the body 104, 604, control an operating mode of the haircare appliance, for example control the haircare appliance to be in or return to the first operating mode as described above. This may help further improve the styling precision, energy efficiency, and/or product safety of the haircare appliance.

In the examples described above with reference to Figures 1 to 6, the control unit 122 was included in a haircare appliance 102 and specifically a main part 106 of the haircare appliance 102, and the haircare appliance 102 also included the sensor arrangement 128, 628 located in an attachment 104, 604 to the main part 106, but it will be appreciated that this need not necessarily be the case. For example, in some examples the body 104, 604, the sensor arrangement 128, 628 and the control unit 122 may be provided in an integrated haircare appliance 102. As another example, the body 104, 604, the sensor arrangement 128, 628 and the control unit 122 may all be provided in an attachment 104, 604 to a main part 106 of the haircare appliance 102. As another example, one of the sensor arrangement 128, 628 and the control unit 122 may be provided in an attachment 104, 604 to a main part 106 and the other of the sensor arrangement 128, 628 and the control unit 122 may be provided in the main part 106. It will be appreciated that other configurations may be used. Further, it will be appreciated that in some examples the control unit 122 may in principle be located anywhere and may be provided separately from other components of the haircare appliance 102. For example, there may be provided a control unit 122 for a haircare appliance 102, the control unit 122 being configured to: receive a plurality of signals sA-sF, each signal sA-sF being indicative of a presence of an object at a respective region of a body 104, 604 of the haircare appliance 102; and determine whether the object is hair based on temporal differences between the signals. In some examples the control unit 122 may be the same as described above with reference to Figures 1 to 6. In other examples, the control unit 122 may be remote from the haircare appliance 102. In these examples, the plurality of signals may, for example, be transmitted to and received by the control unit 122 over a wireless connection to the sensor arrangement 128, 628 and/or the result of the determination by the control unit 122 may be transmitted to and received by the haircare appliance 102 for example over a wireless connection, which may in turn, for example, control an operating mode on the basis of the determination.

Referring to Figure 7 there is illustrated a control unit 722 according to an example. The control unit 722 may have the same or similar feature as the control unit described above with reference to Figures 1 to 6. In this example, the control unit 722 comprises an input interface 723, an output interface 725, a processor 727 and a memory 729. The input interface 723 may, for example, receive a plurality of signals, each signal being indicative of a presence of an object at a respective region of a body of a haircare appliance, for example according to any of the examples described above. These signals may be received from a sensor arrangement 728 configured to output the plurality of signals. These signals may be received by wired or wireless means. The processor 727 may be configured to, in combination with the memory 729, determine whether the object is hair based on temporal differences between the signals, for example according to any of the examples described above. For example, the memory 729 may store a computer program which, when executed by the processor 729, causes the processor to receive the plurality of signals and determine whether the object is hair based on temporal differences between the signals, for example according to any of the examples above. The output interface 725 may be configured to output the determination as required, for example to a separate controller (not shown) configured to control an operating mode of the haircare appliance. In other examples, the control unit 722 may be configured to control an operating mode of the appliance response to the determination of whether the object is hair. In these examples, the output interface 725 may be configured to output control signals or instructions to components of the haircare appliance, such as a heater 724 and an airflow generator 726, in order to control an operating mode of the appliance (for example according to any of the examples described above). These control signals may be transmitted by wired or wireless means. Referring to Figure 8, there is illustrated a method of determining whether hair is present at a body of a haircare appliance. The method comprises, in step 880, receiving a plurality of signals, each signal being indicative of a presence of an object at a respective region of the body. For example, the plurality of signals may be according to any one of the examples described above with reference to Figures 1 to 7. The method comprises, in step 882, determining whether the object is hair based on temporal differences between the signals. For example, the determination may be according to any of the examples described above with reference to Figures 1 to 7. For example, the method may be performed by the control unit 122, 722 according to any one of the examples described above with reference to Figures 1 to 7. In some examples, the method may comprise steps corresponding to any of the functionality described above with reference to Figures 1 to 7, for example any of the functionality of the example control units 122, 722 described above with reference to Figures 1 to 7. Whilst particular examples have been described, it should be understood that these are illustrative examples only and that various modifications may be made without departing from the scope of the invention as defined by the claims.