Brushing detection

Abstract

A toothbrush monitoring device for monitoring brushing activity of a toothbrush is disclosed The toothbrush monitoring device comprises an acceleration sensor (22) arranged to produce acceleration data from motion of the toothbrush, and a brushing detection unit (34) arranged to determine whether brushing is taking place. The brushing detection unit (34) comprises a gravity filter (40) arranged to filter the acceleration data to produce a linear acceleration component, a non- brushing motion filter (42) arranged to filter the linear acceleration component to produce a brushing-related linear acceleration component, and means (50) for outputting a brushing signal indicating whether brushing is taking place in dependence on the brushing-related linear acceleration component. This may help to ensure that brushing data is only collected when brushing is taking place.

Description

[0001] BRUSHING DETECTION

[0002] The present invention relates to a toothbrush monitoring device for monitoring brushing activity of a toothbrush, and in particular a device which is able to determine when teeth are being brushed.

[0003] A toothbrush is an oral hygiene instrument used to clean the teeth and gums. It consists of a head of tightly clustered bristles mounted on a handle. In the case of a manual toothbrush, the brushing motion is produced by the user. In the case of an electric toothbrush, the toothbrush causes vibrations of the bristles in the brush head in order to clean the teeth and gums.

[0004] In order for a user to maintain good oral health it is important that they brush their teeth correctly. To help a user brush their teeth, devices have been developed which monitor how the user brushes their teeth and relay this information back to the user. The monitoring device may be integral with the toothbrush, or attachable to the toothbrush. Data from the monitoring device may be sent to an application (app) or computer program, which is run on an external device such as a mobile phone, tablet or other portable device. The app or program then provides feedback to the user about how they have brushed their teeth.

[0005] WO 2017 / 029469, the subject matter of which is incorporated herein by reference, discloses a manual toothbrush system which has an accelerometer fitted to a toothbrush holder. A processor is configured to determine the orientation of the toothbrush. The determination of the orientation may be used as inputs to control a game on an electronic computing device.

[0006] WO 2019 / 034854, the subject matter of which is incorporated herein by reference, discloses a device for providing an indication of brushing activity of a toothbrush. The device comprises an accelerometer configured to produce acceleration data from motion of the toothbrush. The acceleration data are processed to determine an area which is being brushed. Feedback can be provided to a user based on the determination of brushing area. N0 2019 / 224555, the subject matter of which is incorporated herein by reference, discloses an electric toothbrush device with motion detection and Bluetooth Low Energy (BLE) connectivity. When operating in an online mode, acceleration data is analysed and forwarded to a mobile device. An application running on the mobile device uses this data as a control input for various types of games or teaching / coaching programs. When operating in an offline mode, brushing statistics and sensor data are saved to on board non-volatile memory for later retrieval and analysis by the mobile device application. This can allow brushing statistics and recommendations to be delivered to the user, as well as incentives to brush longer and to brush all parts of the teeth.

[0007] Some known toothbrush monitoring devices start and stop collecting brushing data when power for the toothbrush device is turned on or off. For example, in the case of an electric toothbrush, brushing data may be collected whenever the toothbrush is switched on. As a consequence, brushing data may be collected even when the teeth are not being brushed.

[0008] In the case of a manual toothbrush, the toothbrush monitoring device (which is either integrated with the toothbrush or attachable to the toothbrush) may start / stop collecting brushing data when the device is turned on / off. However, since manual toothbrushes are not themselves powered on or off, the user must remember to turn on the device when they wish to collect brushing data. Therefore, there is a risk that the user may use the toothbrush with the power turned off, and data may not be collected. On the other hand, when brushing has finished, the user must remember to turn the device off. There is therefore also a risk that data may be collected when brushing is not taking place.

[0009] In order to address the above problems, it is known to collect brushing data only when motion is detected. However, it has been found that, in this case, data may still be collected even when the toothbrush is not being used to brush the teeth, such as when carrying the toothbrush to the bathroom, using a washstand, or when moving the toothbrush when going out. This can cause problems such as an accumulation of unintended data other than brushing data, and the logged data not matching actual conditions. It would therefore be desirable to provide a toothbrush monitoring device that can detect actual brushing motion and store only brushing data corresponding to actual brushing. It would also be desirable to provide brushing detection techniques that can minimise processing and memory resources and / or use existing components, such as an existing accelerometer and / or microcontroller.

[0010] According to one aspect of the present invention there is provided a toothbrush monitoring device for monitoring brushing activity of a toothbrush, the toothbrush monitoring device comprising: an acceleration sensor arranged to produce acceleration data from motion of the toothbrush; and a brushing detection unit arranged to determine whether brushing is taking place, the brushing detection unit comprising: a gravity filter arranged to filter the acceleration data to produce a linear acceleration component; a non-brushing motion filter arranged to filter the linear acceleration component to produce a brushing-related linear acceleration component; and means for outputting a brushing signal indicating whether brushing is taking place in dependence on the brushing-related linear acceleration component.

[0011] The present invention may provide the advantage that, by providing a nonbrushing motion filter arranged to produce a brushing-related linear acceleration component, and outputting a brushing signal in dependence thereon, it may be possible to avoid the collection of data which does not correspond to actual toothbrushing and / or to ensure that data is collected when brushing is taking place. Furthermore, the brushing detection may be implemented using low processing and memory resources and / or using existing components, such as an existing accelerometer and / or microcontroller.

[0012] The gravity filter may be arranged to remove a gravity component from the acceleration data. For example, the acceleration data may typically comprise a linear acceleration component and a gravity component, and the gravity filter may remove the gravity component. This may be achieved, for example, using a high pass filter. The high pass filter is preferably arranged to supress acceleration due to gravity and pass acceleration due to movement. In some embodiments, the high pass filter may be implemented by providing a low pass filter to isolate the gravity component, and then subtracting the gravity component from the acceleration data.

[0013] The non-brushing motion filter may be arranged to remove non-brushing specific frequencies from the linear acceleration component. For example, the linear acceleration data may comprise brushing specific frequencies (frequencies corresponding to brushing motion) and non-brushing specific frequencies (frequencies corresponding to non-brushing motion) and the non-brushing motion filter may remove the non-brushing specific frequencies.

[0014] In general, the non-brushing motion filter may have a pass band which is chosen so as to pass frequencies which correspond to brushing motions and to suppress frequencies which correspond to non-brushing motions.

[0015] Tests carried out by the present applicant have revealed that, for a typical user, the frequency of brushing movements is usually around 3-6Hz. On the other hand, the frequency of other movements such as when carrying or transporting the toothbrush is typically 0-2Hz. Thus, in a preferred embodiment, the nonbrushing motion filter is a high pass filter or a band pass filter. For example, the non-brushing motion filter may be arranged to pass frequencies above 1.5 Hz, 2Hz, 2.5Hz, 3Hz or 3.5Hz, although other values are also possible. The nonbrushing motion filter may also be arranged to supress or attenuate frequencies below 1 .5 Hz, 2Hz, 2.5Hz, 3Hz or 3.5Hz, although other values are also possible. For example, frequencies below any of these values may be supressed by at least 3dB, 4dB, 5dB or 6dB, although other values could be used instead.

[0016] The non-brushing motion filter may be implemented, for example, as a direct form discrete filter. This may facilitate implementation using low processing and / or memory resources such as on an (existing) microcontroller.

[0017] It has been found that, in order to accurately isolate brushing frequencies, it may be desirable for the non-brushing motion filter to have a higher order than the gravity filter. For example, the gravity filter may be a first order filter and the nonbrushing motion filter may be a second, third, fourth, fifth or higher order filter (although in both cases other orders are possible). Thus, the non-brushing motion filter may be an Nth order filter where N is 2 or more (for example, 2, 3, 4, 5, 6 or more). This may allow a more fine-grained control of the stop band attenuation and the width of the area between pass and stop bands than would be achievable with a lower order filter used for example in the preparation of the acceleration data for clustering. Thus, the non-brushing motion filter may have a more accurate stop band compared to, for example, a first order filter used for filtering gravity.

[0018] In one embodiment, the non-brushing motion filter is a finite impulse response (FIR) filter. However, other types of filter, such as an infinite impulse response (HR) filter, could be used instead.

[0019] Optionally, the brushing detection unit may comprise a low pass filter arranged to smooth the brushing-related linear acceleration component before further processing. This may help to produce stable results.

[0020] The brushing detection unit may comprise a magnitude calculation unit arranged to calculate a magnitude of the brushing-related linear acceleration component to produce a signal representing brushing-related dynamics. In this case, the signal representing brushing-related dynamics may be a scalar value. This may help to reduce the processing and / or memory resources needed for brushing detection.

[0021] For example, the acceleration sensor may be arranged to produce acceleration data in two or more (typically three) orthogonal directions, in which case the linear acceleration component may be in two or more orthogonal directions and the brushing-related linear acceleration component may be in two or more orthogonal directions. The magnitude calculation unit may then be arranged to calculate a magnitude of the brushing-related linear acceleration component in the two or more orthogonal directions. For example, the magnitude calculation unit may calculate a square root of the sum of the squares of the brushing-related linear acceleration component in the two or more (for example, three) orthogonal directions. However, any other magnitude calculation technique may be used instead.

[0022] Optionally, the brushing detection unit may comprise a low pass filter arranged to smooth the signal representing brushing-related dynamics before further processing. This may help to produce stable results.

[0023] The brushing detection unit may comprise a comparison unit arranged to compare the signal representing brushing-related dynamics to a threshold value, and to output a brushing signal indicating whether brushing is taking place in dependence on a result of the comparison. For example, if the signal representing brushing-related dynamics is above the threshold value, then the comparison unit may output a signal indicating that brushing is taking place. On the other hand, if the signal representing brushing-related dynamics is below the threshold value, then the comparison unit may output a signal indicating that brushing is not taking place. In either case, the comparison unit may be arranged to change the value of the brushing signal only when the signal representing brushing-related dynamics is above or below the threshold value for a predetermined amount of time. This may facilitate brushing detection using relatively low processing and / or memory resources.

[0024] The toothbrush monitoring device may further comprise a data processing unit arranged to process acceleration data from the acceleration sensor to produce brushing data. For example, the data processing unit may be arranged to extract a gravitational component and a linear acceleration component from the acceleration data. In this case, the data processing unit may use the gravitational component and the linear acceleration component to produce brushing data.

[0025] The data processing unit may be arranged to determine an area of the mouth being brushed. For example, the gravitational component and the linear acceleration component may be used in a clustering process such as that disclosed in WO 2019 / 034854. This may allow the user to be provided with information regarding an area of the mouth which is being or has been brushed. The data processing unit may be arranged to receive the brushing signal from the brushing detection unit. In this case, the data processing unit may be arranged to determine that a brushing session has started or ended in dependence on the brushing signal. This may help to ensure that brushing data is only collected while brushing is taking place. For example, the data processing unit may be arranged to determine that a brushing session has started when the brushing signal changes from “no brushing” to “brushing” (and optionally remains as “brushing” for a predetermined period of time). Likewise, the data processing unit may be arranged to determine that a brushing session has ended when the brushing signal changes from “brushing” to “no brushing” (and optionally remains as “no brushing” for a predetermined period of time). The data processing unit is preferably arranged to discard brushing data or not to produce brushing data when the brushing signal indicates that brushing is not taking place.

[0026] The data processing unit may be arranged to produce a brushing report when it is determined that a brushing session has ended. The brushing report may contain a summary of brushing activity, such as an amount of time spent brushing different parts of the mouth. This may reduce processing and storage requirements, allow a larger number of brushing sessions to be stored on the device and / or reduce the amount of data to be transmitted to an external device.

[0027] The toothbrush monitoring device may further comprise a communications module for transmitting brushing data to an external device. The external device may be a processing device such as a mobile phone, a tablet, a laptop, a personal computer, or any other suitable device. The communications module may use any suitable wired or wireless transmission techniques, such a radio frequency transmission or optical transmission. This may allow the external device to be used to store and / or process the brushing data and / or to provide feedback to the user regarding their brushing.

[0028] The toothbrush monitoring device may be operable in a low power mode (such as a standby mode). For example, the brushing detection unit and / or data processing unit may be implemented using a processor (such as a microcontroller) and, in the low power mode, the processor may operate in a power saving mode such as a power down mode, idle mode or sleep mode. The toothbrush monitoring device may be arranged to enter the low power mode when no movement has been detected for a predetermined period of time. For example, the toothbrush monitoring device may be arranged to enter the low power mode when the brushing signal is below a threshold for a predetermined period of time. This may help to ensure that power is not wasted and / or data is not collected unnecessarily.

[0029] The toothbrush monitoring device may further comprise means for waking the toothbrush monitoring device from the low power mode when movement is detected. For example, the toothbrush monitoring device may comprise means for determining whether the acceleration data exceed a predetermined threshold, and means for waking the toothbrush monitoring device from the low power mode when it is determined that the acceleration data exceed the predetermined threshold (optionally for a predetermined period of time).

[0030] In one embodiment, the acceleration sensor (or other device) may be provided with some data processing capability. In this case, the acceleration sensor (or another device) may comprise means for determining whether the acceleration data exceed a predetermined threshold, and means for waking the toothbrush monitoring device from the low power mode when it is determined that the acceleration data exceed the predetermined threshold. This may allow the processor to enter a power saving mode in which data is not processed.

[0031] In one embodiment, the toothbrush monitoring device does not include an on / off switch. For example, the device may be arranged to enter a low power mode when no movement is detected and / or exit the low power mode when movement is detected. This may avoid the need for the user to turn the device on or off. This in turn may help to ensure that data is collected while the teeth are being brushed, and data is not collected while the teeth are not being brushed.

[0032] In any of the arrangements described above, the brushing detection unit and / or data processing unit may be implemented using a microcontroller, or any other suitable processing device such as a microprocessor, programmed with the appropriate computer code. The acceleration sensor may be a three-axis accelerometer arranged to produce acceleration data in three orthogonal directions.

[0033] In any of the arrangements described above, the toothbrush monitoring device may be for use with a manual toothbrush. For example, the toothbrush monitoring device may be an attachment for a manual toothbrush, or integrated with a manual toothbrush. However, if desired, the techniques disclosed herein could also be used with an electric toothbrush.

[0034] According to another aspect of the invention there is provided a toothbrush system comprising a toothbrush and a toothbrush monitoring device according to any of the preceding claims.

[0035] Corresponding methods may also be provided. Thus, according to another aspect of the invention, there is provided a method of monitoring brushing activity of a toothbrush, the method comprising: producing acceleration data from motion of the toothbrush using an acceleration sensor; filtering the acceleration data to produce a linear acceleration component; filtering the linear acceleration component to produce a brushing-related linear acceleration component; and producing a brushing signal indicating whether brushing is taking place in dependence on the brushing-related linear acceleration component.

[0036] Features of one aspect of the invention may be used with any other aspect. Any of the apparatus features may be provided as method features and vice versa.

[0037] Preferred features of the present invention will now be described, purely by way of example, with reference to the accompanying drawings, in which:

[0038] Figure 1 shows a toothbrushing system;

[0039] Figure 2 shows some physical components of a toothbrush monitoring device;

[0040] Figure 3 shows parts of a toothbrush monitoring device in one embodiment of the invention; Figure 4 shows parts of a brushing detection unit;

[0041] Figure 5 shows parts of a data processing unit;

[0042] Figures 6A to 6C show data obtained while using the toothbrush monitoring device for various different activities;

[0043] Figure 7 shows the frequency response of an exemplary non-brushing motion filter;

[0044] Figures 8 to 10 illustrate operation of a non-brushing motion filter on various types of test data;

[0045] Figure 11 shows steps carried out by a toothbrush monitoring device as part of a power saving routine;

[0046] Figure 12 shows steps carried out by a brushing detection unit; and Figure 13 shows steps carried out by a data processing unit.

[0047] Overview

[0048] Figure 1 shows a toothbrushing system in one embodiment of the invention. In this embodiment, the toothbrushing system 2 comprises a manual toothbrush 4 and a toothbrush attachment 10. The toothbrush 4 comprises a toothbrush handle 5 and a toothbrush head 6 with bristles 8. The toothbrush handle 5 is inserted into the toothbrush attachment 10. The toothbrush attachment 10 comprises a base 12 at one end and a neck 14 at the other end. The neck 14 is hollow, and has internal dimensions which are chosen such that the toothbrush handle 5 can be inserted into the neck 14 and, once inserted, there will be a snug fit between the neck and the toothbrush. A marker 16 is provided on the outer surface of the toothbrush attachment 10 to help the user insert the toothbrush correctly. The base 12 of the toothbrush attachment extends further in a radial direction than the neck 14. This provides a wide base on which the toothbrush attachment can stand. The toothbrush attachment 10 has an external wall 18 and a generally frustoconical shape. The toothbrush attachment 10 may be, for example, in the form disclosed in WO 2017 / 029469 A1 , the subject matter of which is incorporated herein by reference.

[0049] In the arrangement of Figure 1 , the toothbrush attachment 10 comprises a toothbrush monitoring device 20. The toothbrush monitoring device 20 comprises a sensor such as an accelerometer, a processor such as a microcontroller, memory, and a communications module such as a Bluetooth module. The toothbrush monitoring device is arranged to collect brushing data while the teeth are being brushed. Brushing data are then transferred to an application running on an external device such as a mobile phone or tablet. This can allow feedback regarding brushing activity to be provided to the user. The toothbrush holder itself may also be able to provide feedback to the user, for example using lights or a display.

[0050] In the arrangement of Figure 1 , the toothbrush monitoring device 20 is part of an attachment for a manual toothbrush. However, in other embodiments, the toothbrush monitoring device is integrated (or partially integrated) with a manual or electric toothbrush.

[0051] Figure 2 shows some physical components of the toothbrush monitoring device in one embodiment. Referring to Figure 2, the toothbrush monitoring device 20 comprises a printed circuit board on which are mounted an accelerometer 22, a microcontroller 24, memory 26 and a communications module 28. In this embodiment, the accelerometer is a three-axis accelerometer which produces acceleration data in three orthogonal directions. The accelerometer may also have some limited data processing capability. The output of the accelerometer is fed to the microcontroller 24. The microcontroller contains computer programs for processing the acceleration data using the techniques disclosed herein.

[0052] Processed data may be stored in the memory 26 and / or transferred to an external device using the communications module 28. The communications module 28 may use any suitable wired or wireless communications protocol. For example, the communications module 28 may use an RF (radio frequency) transmission protocol such as Bluetooth, ZigBee, LoRa or WiFi, or an optical transmission protocol, or any other suitable protocol to communicate with an external device. In some embodiments, the communications module 28 and / or memory 26 may be integrated with the microprocessor 24. Furthermore, other components, such as a charging IC, may also be provided.

[0053] When the toothbrush monitoring device 20 is at rest, it enters a low power or standby mode. For example, if no acceleration data has been produced by the accelerometer 22 for a predetermined period of time, the microcontroller 24 may determine that the device is at rest, and enter a power saving mode, such as a power down mode, idle mode or sleep mode. When the device is subsequently moved, acceleration is detected by the accelerometer 22. The accelerometer compares the sensed acceleration to a threshold. When the sensed acceleration exceeds the threshold, the accelerometer 22 sends a signal to the microcontroller 24 causing it to wake up (i.e. exit the low power mode). The microcontroller 24 then starts to process the acceleration data.

[0054] In the arrangement described above, the toothbrush monitoring device 20 is able to turn itself on automatically by detecting movement when the toothbrush is held by the user. This can avoid the need for an on / off switch that needs to be manually operated by the user. Thus, this arrangement may help to avoid the situation where data is not collected because the user has not turned the device on, and where unwanted data is collected (and unnecessary power consumed) because the user has not turned the device off.

[0055] However, it has been found that the power may be turned on and brushing data collected even when the toothbrush is not being used for brushing. For example, it has been found that brushing data may be collected when the user is making movements such as walking to the bathroom with the brush in their hand, or when travelling with the brush in their suitcase, or carrying the brush in a backpack. This can cause problems such as accumulation of unintended data other than brushing and the log data not matching actual conditions.

[0056] Toothbrush monitoring device

[0057] Figure 3 shows parts of a toothbrush monitoring device 20 in one embodiment of the invention. Referring to Figure 3, the toothbrush monitoring device comprises accelerometer 22, memory 26, communications unit 28, data processing unit 30, timer 32, and brushing detection unit 34. The accelerometer 22 may be, for example, the accelerometer 22 shown in Figure 2. The data processing unit 30 and brushing detection unit 34 (and optionally the memory 26, communications unit 28 and / or timer 32) may be implemented on the microcontroller 24 shown in Figure 2.

[0058] In operation, as the user brushes their teeth, the accelerometer 22 produces acceleration data caused by movement of the toothbrush. The data processing unit 30 processes the acceleration data in order to produce brushing data, such as the part of the mouth being brushed and / or other parameters such as brushing pressure, brushing dynamics, or quality of brushing. The data processing unit 24 may for example perform a process such as that disclosed in WO 2019 / 034854, WO 2019 / 224555 or WO 2021 / 044129, the subject matter of each of which is incorporated herein by reference. Brushing data produced by the data processing unit 30 are stored in the memory 26. The timer 32 is used to time a brushing session. Once a brushing session is complete, the communications unit 28 is used to transmit brushing data from the toothbrush monitoring device 20 to the mobile device 36. An application running on the mobile device is used to extract useful information and to present it to the user.

[0059] In the arrangement of Figure 3, the toothbrush monitoring device 20 includes a brushing detection unit 34. The brushing detection unit 34 receives acceleration data from the accelerometer 22 and processes the acceleration data to determine whether or not the acceleration data correspond to actual brushing of the user’s teeth. The brushing detection unit 34 outputs a brushing signal, indicating whether or not brushing is determined to be taking place, to the data processing unit 30. The data processing unit 30 uses this brushing signal to determine whether or not a brushing session is taking place.

[0060] Brushing detection

[0061] Figure 4 shows parts of the brushing detection unit in one embodiment. Referring to Figure 4, the brushing detection unit 34 comprises gravity filter 40, nonbrushing motion filter 42, optional low pass filter 44, magnitude calculation unit 46, optional low pass filter 48, comparison unit 50 and threshold unit 52.

[0062] In operation, the brushing detection unit 34 receives raw acceleration data from the accelerometer 22. In this embodiment the accelerometer 22 is a three-axis accelerometer which produces acceleration data in three orthogonal directions x, y and z. The raw acceleration comprises two components, namely, a gravity component (acceleration due to gravity) and a linear acceleration component (acceleration due to movement of the accelerometer). The raw acceleration data is received by the gravity filter 40. The gravity filter 40 is a high pass filter which removes the gravity component of the acceleration data. This may be achieved for example by implementing a high pass filter directly, for example, as a discrete filter on the microcontroller. Alternatively, the gravity filter 40 could isolate the gravity component by low pass filtering the raw acceleration data, and then subtract the gravity component from the raw acceleration data to produce the linear acceleration data. This may be done, for example, in the manner disclosed in WO 2019 / 034854. In either case, the gravity filter 40 may be a relatively low order filter, such as a first or second order filter. The output of the gravity filter 40 is three-dimensional linear acceleration data, indicating acceleration of the toothbrush monitoring device 20 in the three orthogonal directions x, y and z.

[0063] The linear acceleration data from the gravity filter 40 are received by the nonbrushing motion filter 42. The non-brushing motion filter 42 filters the linear acceleration data to isolate brushing specific frequencies. The non-brushing motion filter 42 in this embodiment is a finite impulse response (FIR) high pass filter. Further details of the non-brushing motion filter 42 are given later.

[0064] The output of the non-brushing motion filter 42 is brushing-related acceleration data. This is three-dimensional linear acceleration data in which non-brushing specific frequencies have been removed. This data is optionally smoothed using low pass filter 44. The (smoothed) brushing-related acceleration data are fed to the magnitude calculation unit 46.

[0065] The magnitude calculation unit 46 produces an absolute value of the brushing- related linear acceleration data. In one embodiment this is achieved by calculating the square root of the sum of the squares of the x, y and z components of the brushing-related linear acceleration data. The output of the magnitude calculation unit 46 is a scalar value representing brushing-related dynamics. The output of the magnitude calculation unit 46 is optionally smoothed using low pass filter 48. The output of the low pass filter 48 is fed to the comparison unit 50. The comparison unit 50 receives the (smoothed) brushing-related dynamics from the low pass filter 48 and a threshold value from the threshold unit 52. The threshold value is set to be a value which the brushing-related dynamics will exceed when brushing is taking place (but not when brushing is not taking place). The threshold value may be a predetermined value which is set in advance, and / or may be adjustable by the toothbrush monitoring device, for example based on brushing history. The comparison unit 50 compares the brushing-related dynamics to the threshold value. If the brushing-related dynamics do not exceed the threshold value, then the comparison unit 50 outputs a brushing signal indicating that brushing is not taking place (“no brushing”). On the other hand, if the brushing-related dynamics exceed the threshold value, then the comparison unit 50 outputs a brushing signal indicating that brushing is taking place (“brushing”). Optionally, before changing the value of the brushing signal, the comparison unit 50 may wait for the brushing-related dynamics to be above or below the threshold value for a predetermined period of time. The brushing signal is fed to the data processing unit 30.

[0066] Data processing

[0067] Figure 5 shows in more detail parts of the data processing unit 30. Referring to Figure 5, the data processing unit 30 comprises low pass filter 54, subtractor 56, magnitude calculation unit 58, low pass filter 60, low pass filter 62, clustering unit 64, and control unit 66.

[0068] In operation, the data processing unit 30 receives raw acceleration data from the accelerometer 22. The acceleration data are then divided into two branches. In a first branch, the acceleration data are passed through low pass filter 54. The cut-off frequency of the low pass filter 54 is such that acceleration due to gravity is passed, while acceleration due to manual movement of the toothbrush is not. The thus filtered data are then subtracted from the acceleration data in subtractor 56. Thus, this operation removes acceleration due to gravity from the acceleration data, leaving a linear acceleration component. The combination of the low pass filter 54 and subtractor 56 thus function as a high pass filter. The x, y and z components of the acceleration data are filtered separately. The filtered x, y and z linear acceleration components are then passed to magnitude calculation module 58. The magnitude calculation module 58 calculates the absolute value of the linear acceleration from the square root of the sum of the squares of the x, y, and z components.

[0069] The absolute value of the linear acceleration data is then passed to the low pass filter 60. The cut-off frequency of the low pass filter 60 is set such that it passes the linear acceleration data, but removes higher frequency data. Thus, the low pass filter 60 is used to reduce noise present in the data. The output of the low pass filter 60 is a signal D providing an estimate of brushing dynamics. The signal D provides an indication of how strong or fast or vigorously the user is brushing their teeth.

[0070] In a second branch of the filtering process, the raw acceleration data are passed through the low pass filter 62. The cut-off frequency of the low pass filter 62 is such that it passes the gravity component of the raw acceleration data, but not the acceleration component due to manual movement. The x, y, and z components of the raw sensor data 52 are filtered separately to yield separate x, y and z gravitational components. The output of the low pass filter 62 is a gravity signal G representing a gravity component of the acceleration data.

[0071] The brushing dynamics D and gravity signal G are fed to the clustering unit 64. The clustering unit 64 performs a clustering process on the gravity signal G and the dynamics estimation D. The clustering process produces clustering results which can be compared with subsequent acceleration data to indicate which area of the mouth the user is brushing at any given time. The output of the clustering unit 64 is an orientation signal O which provides an indication of which area of the mouth the user is brushing. The orientation signal O is passed to the control unit 66. The clustering process may be, for example, as disclosed in WO 2019 / 034854, WO 2019 / 224555 or WO 2021 / 044129, the subject matter of each of which is incorporated herein by reference.

[0072] The control unit 66 receives the orientation signal O from the clustering unit 64 as well as the brushing signal from the brushing detection unit 34. When the brushing signal changes from “no brushing” to “brushing”, the control unit 66 determines that a brushing session has started. The control unit may check that the brushing signal remains as “brushing” for a short period of time before determining that a brushing session has started, to avoid a brushing session being triggered by spurious signals. When it is determined that a brushing session has started, the control unit 66 receives a timing value from the timer 32, and timestamps the start of a brushing session. When the brushing signal changes from “brushing” to “no brushing” (and remains as “no brushing” for a predetermined period of time), the control unit 66 determines that a brushing session has ended. At the end of a brushing session the control unit 66 receives a timing value from the timer 32 and timestamps the end of a brushing session. The timer 32 provides timing values to the control unit 66, to enable it to time parts of a brushing session.

[0073] During a brushing session, the control unit 66 continues to receive the orientation signal O from the clustering unit, as well as potentially other data such as the brushing dynamics D, gravity signal G and / or a brushing pressure signal. After each brushing session, the control unit 66 generates a brushing report which is stored in the memory 26 for later retrieval. The brushing report contains information relating to how the user brushed their teeth. For example, the brushing report might contain information such as the time the user spent brushing each part of the mouth, speed of brushing and / or for how long the user applied too much pressure, potentially also separated into each part of the mouth. Each brushing session is timestamped using the timer 32.

[0074] To improve the speed of transmission of brushing data and the amount of data that can be collected on the device, brushing session summarization can be used, which allows the brushing sessions to be summarized according to the position brushed. In this case, rather than storing the position of the brush at each interval, a brushing summary is stored with each direction / segment having a corresponding duration. As an example, in this format a brushing session can be summarized as [t, L, R, U, D] where: t = brushing time which is stored as an offset from a reference time; L = a value representing the amount of time spent brushing Left; R = a value representing the amount of time spent brushing Right; U = a value representing the amount of time spent brushing Up; and D = a value representing the amount of time spent brushing Down.

[0075] The brushing session summarization increases the speed of transfer and increases the number of brushing sessions that can be stored directly on the toothbrush.

[0076] In this example, a brushing report comprising approximately 20 bytes of data can be stored for each brushing session. However, it will be appreciated that this is given by way of example only, and other data, such as brushing dynamics and brushing pressure values, could be stored as well or instead. Furthermore, the mouth may be divided into different regions and more specific regions than those mentioned above. The size of the brushing report may vary accordingly.

[0077] After the toothbrush device has been used, there will be one or more timestamped brushing reports stored in the memory 26. When the user wishes to upload these brushing reports to the mobile device 36, they may initiate transmission, for example, by pushing and holding a button on the toothbrush monitoring device. Communication between the communications unit 28 and the mobile device may use for example radio frequency transmission such as Bluetooth, or optical wireless communication techniques such as those disclosed in WO 2022 / 013534, the subject matter of which is incorporated herein by reference, or any other appropriate means.

[0078] If desired, various parts of the data processing unit 30 and the brushing unit 34 could be provided in common. For example, the data processing unit 30 and the brushing unit 34 could share the same gravity filter. Furthermore, the output of the non-brushing motion filter 42 could be used in the clustering process. If desired, the brushing signal may also be fed to the clustering unit 64. In this case, the clustering unit may be arranged to only perform the clustering process while the brushing signal indicates “brushing”. Various other modifications will be apparent to the skilled person. Filter characteristics

[0079] As discussed above, the brushing detector 34 includes a non-brushing motion filter 42 which filters the linear acceleration data to isolate brushing specific frequencies.

[0080] In order to determine appropriate characteristics for the non-brushing motion filter, sample acceleration data was obtained while carrying out three different activities, namely, carrying the device in a backpack, carrying it by hand, and tooth brushing. A Fourier transformation was then performed on the three data sets.

[0081] Figure 6A shows acceleration data obtained while carrying the toothbrush monitoring device in a backpack, after Fourier transformation. It can be seen that peaks occur in the frequency response at around 1 Hz, 2Hz and 3Hz. However, these peaks diminish in intensity above about 2Hz.

[0082] Figure 6B shows acceleration data obtained while carrying the toothbrush monitoring device by hand, after Fourier transformation. It can be seen that a peak occurs in the frequency response at around 1 Hz. However, there are no significant peaks above about 2Hz

[0083] Figure 6C shows acceleration data obtained while brushing with the toothbrush monitoring device attached to a toothbrush, after Fourier transformation. It can be seen that peaks occur in the frequency response occurs between about 4Hz and 6Hz.

[0084] From Figures 6A to 6C it can be seen that the main frequency component of the tooth brushing motion is higher than it is for other movements. In particular, tests carried out by the present applicant have shown that the frequency of brushing movements is usually around 3-6Hz, while the frequency of other movements when carrying the brush is typically 0-2Hz.

[0085] Using the test data described above, a high pass filter was designed to separate brushing sessions from other motions. The high pass filter was implemented as a direct form discrete filter on the microcontroller. The coefficients were empirically selected to match the filter to the desired characteristics, and tested using the sample datasets. A suitable filter was found to be a fifth order discrete filter. This can allow a more fine-grained control of the stop band attenuation and the width of the area between pass and stop bands than would be the case with a lower order filter, such as a first order filter, used in the preparation of the acceleration data for clustering. Thus, the non-brushing motion filter may have a more accurate stop band compared to, for example, a first order filter used for filtering gravity.

[0086] In one embodiment, the non-brushing motion filter was implemented as a finite impulse response (FIR) filter with a cutoff frequency of around 2Hz. The frequency response of the filter is shown in Figure 7. In this example, the filter has the Fstop at 2Hz, Fpass at 4Hz and attenuation of 10dB in the stop band. However, it will be appreciated that other values could be used instead. Furthermore, different order filters (such as second, third, fourth, sixth or more), and different types of filter (such as an infinite impulse response filter) could be used.

[0087] Figures 8 to 10 illustrate operation of the non-brushing motion filter 42 on various types of test data.

[0088] Figure 8A shows test acceleration data obtained while carrying the toothbrush monitoring device in a backpack. The acceleration data is in three orthogonal directions, x, y and z. Figure 8B shows the linear acceleration data obtained after passing the acceleration data through the gravity filter 40. Figure 8C shows the brushing-related dynamics obtained after passing the linear acceleration data through the non-brushing motion filter 42 and the magnitude calculation unit 46. Also shown in Figure 8C is a threshold value which in this example is set at 12. It can be seen that in this case the brushing-related dynamics remain below the threshold. As a consequence, the comparison unit 50 sets the brushing signal to indicate “no brushing”.

[0089] Figure 9A shows test acceleration data obtained while walking with the toothbrush monitoring device in a user’s hand. Figure 9B shows the linear acceleration data obtained after passing the acceleration data through the gravity filter 40. Figure 9C shows the brushing-related dynamics obtained after passing the linear acceleration data through the non-brushing motion filter 42 and the magnitude calculation unit 46. It can be seen that in this case the brushing- related dynamics remain below the threshold (which is set at 12). As a consequence, the comparison unit 50 sets the brushing signal to indicate “no brushing”.

[0090] Figure 10A shows test acceleration data obtained while brushing. Figure 10B shows the linear acceleration data obtained after passing the acceleration data through the gravity filter 40. Figure 10C shows the brushing-related dynamics obtained after passing the linear acceleration data through the non-brushing motion filter 42 and the magnitude calculation unit 46. It can be seen that in this case the brushing-related dynamics remain above the threshold (which is set at 12). As a consequence, the comparison unit 50 sets the brushing signal to indicate “brushing”.

[0091] Processes

[0092] Figure 11 shows steps carried out by a toothbrush monitoring device as part of a power saving process in one embodiment. Referring to Figure 11 , the toothbrush monitoring device is initially in a low power mode or standby (step 100). In this mode, the microcontroller 24 shown in Figure 2 is in a power saving mode (such as power down, idle or sleep mode). However, the accelerometer 22 continues to sense acceleration caused by movement of the device. The accelerometer is also provided with some limited data processing capability.

[0093] In step 102 the accelerometer 22 senses an acceleration value. In step 104, the accelerometer compares the sensed acceleration value to a threshold. If the sensed acceleration value is below the threshold, then processing returns to step 102. On the other hand, if the sensed acceleration value (in any one of the three orthogonal directions) exceeds the threshold, then processing proceeds to step 106. In step 106, the accelerometer sends a wake-up signal to the microcontroller 24. This causes the microcontroller to exit the power saving mode. The data processing unit 30 and the brushing detection unit 34 shown in Figure 3 then begin operation. In step 108, the accelerometer 22 continues sensing acceleration data. In step 110 the microcontroller performs brushing detection using the brushing detection unit 34. If brushing is detected, then the microcontroller collects brushing data using the data processing unit 30. In step 112 the microcontroller 24 determines whether the acceleration data have been below a predetermined threshold for a predetermined period of time. If the acceleration data have not been below the predetermined threshold for the predetermined period of time, then processing returns to step 108. On the other hand, if the acceleration data have been below the predetermined threshold for the predetermined period of time, then processing proceeds to step 114.

[0094] In step 114 the microprocessor is switched to a power saving mode (such as power down, idle or sleep mode). This causes the toothbrush monitoring device to return to the low power mode (step 100). In this mode, the data processing unit 30 and the brushing detection unit 34 shown in Figure 3 do not operate. However, the microprocessor continues to monitor a wake-up signal from the accelerometer which switches the microprocessor on when a sensed acceleration value exceeds the threshold, in step 104.

[0095] Figure 12 shows steps carried out by the brushing detection unit 34 in one embodiment. Referring to Figure 12, in step 120 the brushing detection unit receives acceleration data from the accelerometer 22. In step 122 the gravity component is removed from the acceleration data using the gravity filter 40. The result of this step is three-dimensional linear acceleration data, indicating acceleration of the toothbrush monitoring device in the three orthogonal directions x, y and z.

[0096] In step 124, non-brushing frequencies are removed from the linear acceleration data using the non-brushing motion filter 42. The result of this step is brushing- related acceleration data. This is three-dimensional linear acceleration data in which non-brushing specific frequencies have been removed. This data is optionally smoothed using low pass filter 44 in step 126.

[0097] In step 128, an absolute value of the brushing-related linear acceleration data is calculated using the magnitude calculation unit 46. This is achieved by calculating the square root of the sum of the squares of the x, y and z components of the brushing-related linear acceleration data. The result of this step is a scalar value representing brushing-related dynamics. This value is optionally smoothed using low pass filter 48 in step 130.

[0098] In step 132, it is determined whether the brushing-related dynamics exceed a threshold using the comparison unit 50. If the brushing-related dynamics do not exceed the threshold value, then in step 134 the brushing signal is set to indicate that brushing is not taking place. On the other hand, if the brushing-related dynamics do exceed the threshold value, then in step 136 the brushing signal is set to indicate that brushing is taking place. In step 138 the brushing signal is sent to the data processing unit 30. Processing then returns to step 120.

[0099] Figure 13 shows steps carried out by the data processing unit 30 in one embodiment. It is assumed that initially the brushing signal indicates “no brushing”. Referring to Figure 13, in step 150 the data processing unit receives acceleration data from the accelerometer 22. In step 152 the acceleration data is high pass filtered to remove gravity components and produce linear acceleration components. In step 154 a magnitude of the linear acceleration components is calculated to produce brushing dynamics D. This may be achieved by calculating the square root of the sum of the squares of the x, y and z components of the linear acceleration. In step 156 the acceleration data are low pass filtered to produce a gravity signal G. In step 158 a clustering process is performed on the brushing dynamics D and the gravity signal G to produce an orientation signal O. In step 160 the data processing unit receives a brushing signal from the brushing detection unit 34. In step 162 it is determined whether the brushing signal changes from “no brushing” to “brushing” (optionally for a predetermined period of time). If it is determined that the brushing signal has changed from “no brushing” to “brushing”, then in step 164 a brushing session is determined to have started. The start of the brushing session is time stamped using a timing value from the timer 32. Processing then proceeds to step 166. On the other hand, if in step 162 it is determined that the brushing signal does not change from “no brushing” to “brushing” (i.e. it remains “no brushing”) then processing returns to step 150. In step 166 the data processing unit collects brushing data produced during the brushing session. In step 168 it is determined whether the brushing signal has changed from “brushing” to “no brushing” (optionally for a predetermined period of time). If it is determined that the brushing signal has changed from “brushing” to “no brushing” then in step 170 the brushing session is determined to have ended. The end of the brushing session is time stamped using a timing value from the timer 32. Then in step 172 the data processing unit produces a brushing report summarising the brushing session and stores it in the memory 26 for later retrieval. Processing then returns to step 150.

[0100] The embodiments described above can allow the toothbrush monitoring device to determine if the acceleration data correspond to actual toothbrushing movements or something else (for example, carrying the device in a bag). Furthermore, such a determination can be made at least partially using existing components, such as an existing accelerometer and / or microcontroller. The disclosed embodiments can also be implemented using low CPU and memory resources (such as those available to a typical microcontroller).

[0101] Preferred features of the invention have been described above with reference to various embodiments. However, it will be appreciated that the invention is not limited to these embodiments, and variations in detail may be made within the scope of the appended claims.

Claims

CLAIMS1 . A toothbrush monitoring device for monitoring brushing activity of a toothbrush, the toothbrush monitoring device comprising: an acceleration sensor arranged to produce acceleration data from motion of the toothbrush; and a brushing detection unit arranged to determine whether brushing is taking place, the brushing detection unit comprising: a gravity filter arranged to filter the acceleration data to produce a linear acceleration component; a non-brushing motion filter arranged to filter the linear acceleration component to produce a brushing-related linear acceleration component; and means for outputting a brushing signal indicating whether brushing is taking place in dependence on the brushing-related linear acceleration component.

2. A toothbrush monitoring device according to claim 1 , wherein the gravity filter is arranged to remove a gravity component from the acceleration data.

3. A toothbrush monitoring device according to claim 1 or 2, wherein the nonbrushing motion filter is arranged to remove non-brushing specific frequencies from the linear acceleration component.

4. A toothbrush monitoring device according to any of the preceding claims, wherein the non-brushing motion filter is a high pass filter.

5. A toothbrush monitoring device according to any of the preceding claims, wherein the non-brushing motion filter is arranged to pass frequencies above 1 .5 Hz, 2Hz, 2.5Hz, 3Hz or 3.5Hz.

6. A toothbrush monitoring device according to any of the preceding claims, wherein the non-brushing motion filter has a higher order than the gravity filter.

7. A toothbrush monitoring device according to any of the preceding claims, wherein the brushing detection unit comprises a magnitude calculation unit arranged to calculate a magnitude of the brushing-related linear acceleration component to produce a signal representing brushing-related dynamics.

8. A toothbrush monitoring device according to claim 7, wherein the signal representing brushing-related dynamics is a scalar value.

9. A toothbrush monitoring device according to claim 7 or 8, wherein the acceleration sensor is arranged to produce acceleration data in two or more orthogonal directions, and the magnitude calculation unit is arranged to calculate a magnitude of the brushing-related linear acceleration component in the two or more orthogonal directions.

10. A toothbrush monitoring device according to any of claims 7 to 9, wherein the brushing detection unit comprises a comparison unit arranged to compare the signal representing brushing-related dynamics to a threshold value, and to output a signal indicating whether brushing is taking place in dependence on a result of the comparison.

11. A toothbrush monitoring device according to any of the preceding claims, further comprising a data processing unit arranged to process acceleration data from the acceleration sensor to produce brushing data.

12. A toothbrush monitoring device according to claim 11 , wherein the data processing unit is arranged to extract a gravitational component and a linear acceleration component from the acceleration data, and to use the gravitational component and the linear acceleration component to produce brushing data.

13. A toothbrush monitoring device according to claim 11 or 12, wherein the data processing unit is arranged to determine an area of the mouth being brushed.

14. A toothbrush monitoring device according to any of claims 11 to 13, wherein the data processing unit is arranged to receive the brushing signal fromthe brushing detection unit and to determine that a brushing session has started or ended in dependence on the brushing signal.

15. A toothbrush monitoring device according to any of claims 11 to 14, wherein the data processing unit is arranged to discard brushing data or not to produce brushing data when the brushing signal indicates that brushing is not taking place.

16. A toothbrush monitoring device according to any of claims 11 to 14, wherein the data processing unit is arranged to determine whether a brushing session has ended and to produce a brushing report when it is determined that a brushing session has ended.

17. A toothbrush monitoring device according to any of the preceding claims, further comprising a communications module for transmitting brushing data to an external device.

18. A toothbrush monitoring device according to any of the preceding claims, wherein the toothbrush monitoring device is operable in a low power mode, and the toothbrush monitoring device is arranged to enter the low power mode when no movement has been detected for a predetermined period of time.

19. A toothbrush monitoring device according to claim 18, wherein the toothbrush monitoring device is arranged to enter the low power mode when the brushing signal is below a threshold for a predetermined period of time.

20. A toothbrush monitoring device according to claim 18 or 19, further comprising means for determining whether the acceleration data exceed a predetermined threshold, and means for waking the toothbrush monitoring device from the low power mode when it is determined that the acceleration data exceed the predetermined threshold.21 . A toothbrush monitoring device according to any of claims 18 to 20, wherein the toothbrush monitoring device does not include an on / off switch.

22. A toothbrush monitoring device according to any of the preceding claims, wherein the brushing detection unit and / or data processing unit are implemented using a microcontroller.

23. A toothbrush monitoring device according to any of the preceding claims, wherein the device is for use with a manual toothbrush.

24. A toothbrush system comprising a toothbrush and a toothbrush monitoring device according to any of the preceding claims.

25. A method of monitoring brushing activity of a toothbrush, the method comprising: producing acceleration data from motion of the toothbrush using an acceleration sensor; filtering the acceleration data to produce a linear acceleration component; filtering the linear acceleration component to produce a brushing-related linear acceleration component; and producing a brushing signal indicating whether brushing is taking place in dependence on the brushing-related linear acceleration component.

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