BR112019006426B1 - METHOD FOR MONITORING TOOTHBRUSHING AND SYSTEM FOR TRAINING A SMART TOOTHBRUSH - Google Patents

Abstract

The present invention relates to a method for monitoring toothbrushing, comprising: a training phase in which: a position sensor detects position information of a toothbrush during a first instance of free brushing by the user; one or more additional sensors record toothbrush movement information during the first instance of free brushing; a user-specific statistical model is generated, which maps positional information onto movement information; and a monitoring phase in which: one or more additional sensors record toothbrush movement information during a second instance of free brushing; and the toothbrush compares the motion information received during the second free brushing occurrence with the user-specific statistical model to calculate the positional information.

Description

FIELD OF THE INVENTION

[001] The present invention relates to a method for monitoring toothbrushing, more especially, to a method comprising a training phase and a monitoring phase; both phases involving free brushing by the toothbrush user.

BACKGROUND OF THE INVENTION

[002]The practice of brushing teeth is well established, and for many people it has been part of their morning and evening routines for longer than they can remember. However, there is growing evidence that the success of dental care depends not only on whether an individual brushes their teeth or not, but also on their toothbrushing technique.

[003] High-resolution brush tracking in dental surgery is known (Oral-Insights, US patent 2012/0310593 A1), but it uses complex magnetic fields and extensive hardware, which is time consuming and difficult to use. Furthermore, the user must go out of his way to visit a dental surgery clinic with the necessary facilities. There is a need for more user-friendly handling systems, especially those that enable the user to evaluate their toothbrushing technique in an everyday setting at home, without the presence of a dentist.

[004] Home-based technologies exist to monitor toothbrushing. Such technologies enable mobile evaluation and feedback of brushing performance using a standalone electronic brush or a brush in combination with a mobile device system. Most of these systems are significantly inaccurate when compared to the accuracy that can be achieved by the Oral Insights system.

[005] The efficiency of toothbrushing depends not only on the regions of the mouth visited, but also on the path taken between these regions, the order in which they are visited and the time spent in each region. These traits together define the course of a toothbrushing session. Often, users will unwittingly follow a course through force of habit or routine, with no specific goal in mind. This can cause some areas of the mouth to receive better or worse treatment.

[006] Devices that provide toothbrush positional data are known. However, existing toothbrush monitoring devices treat the regions of the mouth in isolation, ignoring the temporal order in which these regions are visited and/or the brushing path taken. Since these existing devices do not provide information related to the time course (i.e., the order or path) of the brushed areas, therefore, they cannot provide the user with any information related to the efficiency of their brushing technique.

[007] As described above, toothbrushes with sensors to determine and/or track the position in the user's mouth are known. However, there is a balance between accuracy and user inconvenience. It is believed that magnetic fields and magnetometers can be used to determine precise toothbrush positions during brushing in a laboratory or dental surgery clinic. There is a need for a system that is capable of accurately measuring the actual position of a toothbrush in the user's mouth while brushing in a home environment.

[008] Methods for tracking and evaluating brushing activity can be affected by strong noise and variability. A significant part of the noise can be removed by accurately detecting the beginning of the brushing action, ie the contact of the bristles with a tooth surface or gum. For manual toothbrushes, this can be achieved by a combination of activity and sound level measurement (US patent 2013/0,166,220 A1).

DESCRIPTION OF THE INVENTION

[009] Consequently, the present invention aims to solve the above problems, providing, according to a first aspect, a method for monitoring toothbrushing comprising: - a training phase in which, - a position sensor detects the position information of a toothbrush during a first instance of free brushing by the user; - one or more additional sensors record toothbrush movement information during the first instance of free brushing; - a user-specific statistical model is generated, which maps positional information into movement information; and - a monitoring phase in which, - one or more additional sensors record toothbrush movement information during a second instance of free brushing; and - the toothbrush compares the movement information received during the second free brushing occurrence with the user specific statistical model to calculate the positional information.

[010] In this way, the method provides two separate phases: a training phase and a monitoring phase. By producing an adapted statistical model during the training phase and using it during the monitoring phase, it is possible to carry out the monitoring phase at home, but still benefit from more accurate monitoring, generally restricted to systems in the dentist's office. and/or hygienist. Additionally, both steps can be performed during a user's free brushing. Not only does this result in an easier-to-handle device, but it also eliminates the misreading that can arise from the user following “guide” type instructions.

[011] This is a significant improvement over alternative calibration methods in which the user must follow predefined trajectories for brushing certain regions, while sensor data is used to adapt the prediction model. Any predefined trajectories/regions of such calibration methods are often extremely different from the user's natural brushing habit. Not only does this make training difficult, but it can also negatively affect the performance of prediction models for free brushing feedback.

[012] The proposed technology helps customers to brush their teeth better, improving the quality and user experience during the training phase and, therefore, the value of evaluation and feedback of free brushing.

[013] The optional traits of the present invention will be established at the time. These are applicable alone or in any combination with any aspect of the present invention.

[014] Optionally, the training phase comprises the steps: - providing a smart toothbrush, the smart toothbrush comprises at least one position sensor and at least one accelerometer; - supplying an external position sensor; - detecting the position information of a toothbrush during a first instance of free brushing by the user using the relative position of the position sensor on the smart toothbrush and the external position sensor; - the recording of toothbrush movement information during the first occurrence of free brushing using the accelerometer; and - generating a user-specific statistical model that maps positional information to motion information.

[015] The step of detecting the toothbrush position information may include recording accelerometer data from an accelerometer located on or inside the toothbrush and also recording positional data from the external position sensor. Each of the toothbrushes and the external sensor can send their data separately to an external computer that processes the received information and correlates the toothbrush acceleration measurements with the positional information from the external sensor. For example, in some embodiments, a specific point on the timeline (timestamp) created after turning on the toothbrush or in response to any specific stimulus on the toothbrush provides a reference point for comparing and combining the two datasets. . In some embodiments, the external computer takes the form of a mobile device.

[016] The step of generating a user-specific statistical model from the combined data can take the form of multivariate classification models that can be trained for each user. In some embodiments, a multivariate normal approximation may be applied in addition to a Mahalanobis distance or multimodal probability in order to select the most likely position or assign weight (probability) to specific positions (which may correspond to specific segments in the user interface). )).

[017] Optionally, the monitoring phase comprises the steps: - provision of a mobile device; - recording toothbrush movement information during a second occurrence of free brushing using the accelerometer; and - comparing the motion information received during the second instance of free brushing with the user-specific statistical model to provide the positional information; - displaying positional information to the user on the mobile device.

[018] It should be understood that “free brushing” is simply referring to the user brushing their teeth normally without instructions. The opposite of free brushing would be following instructions, for example, “brush the inner surface of the upper teeth”.

[019] Optionally, the training phase includes an alternative training model in which the user follows an instruction guide on a mobile device, where the user-specific statistical model generated by the alternative training model maps to the positional information displayed on the device mobile for movement information received simultaneously from one or more additional sensors.

[020] In this way, the device can still be used without requiring a positional input on the toothbrush. It can be considered that this “guide mode” may be less accurate than the “free brushing” training mode; however, providing both modes in one system makes for a more flexible device.

[021] Optionally, the position sensor includes an external sensor mounted on the head.

[022] In some embodiments, the transmitter produces a magnetic field in the jaw reference frame. The brush position sensor samples the field and the data generated at a given sampling rate is sent back to the base station. The communication between the external position sensor, the toothbrush and the external computer is preferably wireless.

[023] Optionally, the position sensor includes an external wall-mountable sensor.

[024] Optionally, the position sensor is located inside a wall mountable mirror.

[025] Optionally, the position sensor is a magnetic field generator and a corresponding magnetic field sensor, the magnetic field sensor is located on the toothbrush.

[026] Optionally, the magnetic generator is usable by the user.

[027] Optionally, the magnetic generator is mounted on the wall. For example, as part of or attached to a mirror.

[028] The magnetic field generator can take the form of a DC magnetic field, such as the DC switching magnetic field technology of Asencion Technology Corporation. However, those skilled in the art will appreciate that other commercial magnetic field generators are available.

[029] According to a second aspect of the present invention, a system for training a smart toothbrush is provided, the system comprises: - a position sensor that detects position information of a toothbrush during a first occurrence of free brushing by the user; - one or more additional sensors located on the toothbrush that record toothbrush movement information during the first instance of free brushing; and - a computer comprising memory and a processor, the processor programmed to generate a user-specific statistical model by mapping positional information from the position sensor to motion information from one or more additional sensors to create a table of query stored in memory.

[030] Any of the optional traits discussed above regarding the first aspect could also be applied to the second aspect.

[031] According to a third aspect of the present invention, there is provided a smart toothbrush comprising: - a toothbrush body comprising a brushing head and a handle; - a sensor to detect the position of the toothbrush in the mouth at different points during a toothbrushing session; - a timer to record the time each detected position occurs; and - a computing module with a memory, the computing module configured for: - recording the position detected at various points during a toothbrushing session; - the record of the time in which each detected position was detected; and - the production of a map of the route taken by the toothbrush during the toothbrushing session using the recorded position and time information.

[032] In this way, enhanced information regarding the efficiency of a user's toothbrushing technique is provided to the user. The efficiency of toothbrushing depends on the path taken by the toothbrush during toothbrushing. The present invention provides information related to the position of the brush at various times and its use to follow the time course (i.e., the order) of the brushed areas, as well as the transitions from one brushed area to another.

[033] The term “route map” should be understood as the space-time trajectory traveled by the toothbrush is produced from the recorded data. In this way, it is possible to generate much more useful data than could be generated simply by recording the individual positions. Recording the temporal order in which different regions of the mouth are brushed makes it possible to provide more meaningful and personalized feedback and recommendations.

[034] For example, by recording an entire “path” or “path” of the toothbrush around the mouth, it is possible to determine whether parts of the mouth are being neglected. Where the recorded trajectory shows that a given user tends to end the brushing session at a specific location in their mouth, it is likely that this area is not receiving the same levels of attention to detail as the areas of the mouth that are directed at the beginning of the brushing path. It is therefore useful for the user to be alerted to this.

[035] Similarly, the record of the journey may indicate that certain areas of the mouth are completely forgotten or very rarely visited. This type of neglect can lead to an increase in plaque and staining and, potentially, a deterioration in the appearance of teeth and/or gum disease.

[036] When alerted to this type of supervision, the user can adapt his brushing path accordingly, to discover a more ideal trajectory, with ideal transitions from one area of the mouth to another. In this way, it is possible for the user to minimize any adverse effect on oral health caused by accidental negligence and/or poor brushing technique.

[037] Optionally, the computing module is programmed to use a street vendor machine learning algorithm to process the recorded position and time information and produce a map of an ideal trajectory to be traveled by the toothbrush during the toothbrush session. teeth brushing.

[038] It will be understood that a street vendor approach to finding the optimal route is an example of possible route / trajectory location algorithms that may be applicable to determine an ideal trajectory to be traveled by the toothbrush during a toothbrushing session teeth.

[039] A street vendor machine learning algorithm can take the form of any algorithm that solves “the street vendor problem”. In other words, the algorithm is given a number of data points (a “transition matrix”); in this case, the data points may correspond to a plurality of mouth positions and associated timings. This information is converted into a cost function for each possible transition between data points. The algorithm then determines the least cost route between the different data points. Along the route, each of the positions in the mouth can be “visited” by the toothbrush more than once. In other words, the route might include brushing one or more of the positions in the mouth more than once.

[040] In this way, an example method of path optimization for a given individual is provided. This can take into account the user's specific issues, such as sensitivity, missing or misaligned teeth and other problem areas. By inverting the transition matrix, a less ideal trajectory could be calculated.

[041] Optionally, the toothbrush body further comprises: - a reservoir for an active ingredient, the reservoir in fluid communication with the head portion; and - a dispenser for dispensing the active ingredient from the reservoir via the head upon receipt of an activation signal.

[042] In this way, the “smart” toothbrush is able to dispense an active ingredient based on the information received by the toothbrush.

[043] Advantageously, this enables an active ingredient to be dispensed more precisely. This avoids many of the problems associated with regular toothbrushing where an active ingredient is pre-loaded on the brush head prior to the start of the brushing episode. One of these disadvantages is the fact that users often initiate a brushing episode at a specific location and follow an automatic brushing pattern or pathway, which means that certain areas of the mouth (usually those contacted at the beginning of the brushing episode) routinely receive more active ingredient than others. By selectively dispensing the active ingredient in response to sensor information, it is also possible to better control active ingredient waste (eg due to spitting or undissolved ingredients). It is also possible to avoid over-application of active ingredients, such as whiteners, which can be harmful to the user if applied in excess.

[044] Optionally, the activation signal is triggered in response to sensor information.

[045] Optionally, the information detected by the sensor includes: - the location within a predefined map of the user's mouth.

[046] The predefined map of the user's mouth can correspond to the 10 segments described herein.

[047] Optionally, the information detected by the sensor includes timing information. Timing initiation can be triggered by a single event, such as reaching sensor threshold, sensing a change in direction, sensing a change in acceleration. In other events, timing initiation can be triggered when two or more sensors simultaneously record a threshold value (for example, the microphone and accelerometer simultaneously recording sound and motion measurements).

[048] In some realizations, a specific point in the timeline (timestamp) can be performed for each record, starting when turning on the brush or starting brushing. Where specific points on the timeline (timestamp) (and the associated logged data) are recorded when the brush is turned on, an extra step of determining the start of brushing can also be incorporated. Suitable mechanisms for initiating brushing are described herein.

[049] Optionally, the smart toothbrush further comprises at least one (s) additional reservoir (s).

[050] In this way, more than one active ingredient can be applied to one or more regions of the mouth during the same brushing episode. For example, the active located within the additional reservoir can provide an additional step of care that complements a first active, such as toothpaste located within the first reservoir. An example of such an additional care step is the gum conditioning serum.

[051] The different assets can be dispensed at the same time, or at different times. As different assets are applied at different times, each asset will be triggered by a different sensor reading. For example, when the sensor detects that the toothbrush head is at a first predetermined location within the mouth, a first active can be dispensed from the first reservoir. When the sensor detects that the toothbrush head is at a second predetermined location within the mouth, a second active can be dispensed from the second reservoir.

[052] In other embodiments, a second asset may be dispensed from at least one additional reservoir simultaneously with the first asset dispensed from the first reservoir.

[053] The separate reservoirs allow the separate storage of assets that may be incompatible with each other.

[054] Optionally, the smart toothbrush also comprises a sound sensor to detect contact between the toothbrush head and the user's jaw.

[055] Optionally, the route map is displayed on a mobile device.

[056] In some embodiments, the raw data is processed in the brush, then the specific point on the timeline (timestamp) is sent via wireless communication methods to the external computer (which may take the form of a mobile device, such as a mobile phone or tablet, but can also take the form of a smart mirror or wall-mounted computer screen). In other embodiments, the raw data is streamed to the external computer and further processed on the external computer (again, this can take the form of a mobile device, such as a mobile phone or tablet). Wireless communication can take the form of Bluetooth, Wi-Fi or similar.

[057] According to a fourth aspect of the present invention, there is provided: a tracking system for recording the position of a toothbrush during toothbrushing, the system comprises: - a toothbrush, the toothbrush comprises : - a portion of the head; - a portion of cable; - an orientation sensor; - a sensor to detect contact between a toothbrush and a user's jaw; and - a magnetic sensor; and - a magnetic field generator; - where: - the magnetic sensor detects the absolute position of the toothbrush within the field created by the magnetic field generator.

[058] In this way, it is possible to provide accurate tracking of the position of the toothbrush in the mouth. Using a combination of inertial measurement sensors, sound and a custom magnetic field achieves high resolution tracking of the toothbrush. In particular, the magnetic field is generated by wearable magnets or field generators, enabling a low-cost design and easy-to-use system in dental or home practices.

[059] Optionally, the orientation sensor is an accelerometer or an inertial measurement unit to measure the rotational position of the toothbrush.

[060] Optionally, the sensor to detect contact between the toothbrush and the user's jaw is a sound sensor; and - wherein, upon detection by the sound sensor of contact between the toothbrush and the jaw, the position measurement within the magnetic field is restricted to a position measurement along a pre-calibrated, one-dimensional jaw line it's known.

[061] Optionally, the magnetic field generator is a wearable magnetic field generator; - in which the magnetic sensor detects the absolute position of the toothbrush within the field created by the magnetic field generator.

[062] Optionally, the magnetic field is adjusted to generate iso-surfaces of magnitude perpendicular to the jaw.

[063] In this way, small changes in position along the iso-surfaces around any of the teeth (for example, the variable distance between the brush head and the tooth surface) do not affect the measurement, leading to a system more robust.

[064] Optionally, the magnetic sensor comprises a processor that detects the absolute position of the toothbrush by measuring the field magnitude, M of the brush and the vertical field component Mz of the brush.

[065] The field magnitude M is provided by: M = (Mx2 + My2 + Mz2)1/2 where (Mx2 + My2 + Mz2) are the field components in the x, y and z directions, respectively. M, therefore, is invariant in device rotations.

[066] In some embodiments, an initial calibration step is performed to create a lookup table to correlate the measured magnetic field values with the position information. This calibration step is performed by initially moving a magnetometer probe in a controlled manner, tooth by tooth along predetermined points along the user's jaw, for example along the centers of the biting surfaces of each tooth. The resulting magnetometer readings are stored in the lookup table alongside the predetermined position points.

[067] In the real toothbrush, the magnetometer will have a known separation from the toothbrush head that comes into contact with the surface of the user's teeth. This separation can be adjusted using a predetermined model. Since the level of adjustment can depend on the brush orientation, the brush orientation can be obtained from accelerometer data and incorporated into the model.

[068] The vertical field component Mz can be obtained by measuring the field and accelerations of an arbitrary rotating device, since Mz = ax x mx + ay x my + az x mz, where mx, my and mz are the measured fields of the arbitrary device, and ax, ay, az correspond to the measured (normalized) accelerations of the arbitrary rotary device. Acceleration values, such as acceleration due to gravity, are desired to obtain information regarding brush orientation (rather than information regarding brush kinetic acceleration) and can be obtained by applying low-pass filtering to the overall output obtained from the accelerometer, the global output containing the gravitational acceleration contributions as well as the kinetic acceleration contributions.

[069] Optionally, the toothbrush comprises: - an electric motor and/or vibrator to provide movement and/or rotation of the toothbrush head; - and - a sound receiver to detect changes in the frequency of the electric motor and/or vibrator when the toothbrush is in contact with a tooth.

[070] In this way, it is possible to provide an electronic or sonic toothbrush capable of measuring the positional information of the toothbrush when the toothbrush is in contact with the teeth. In particular, how to accomplish this without requiring substantial computational resources.

[071] Optionally, the toothbrush comprises a data logger for recording data from the magnetic sensor and/or the orientation sensor; - where the datalogger is activated only when the sound receiver detects a value that meets a predetermined threshold criteria.

[072] Optionally, the data logger comprises a memory for recording the detected orientation information and a processor programmed to convert this orientation information into positional information. In some embodiments, the processor is configured to perform multivariate sorting which typically involves a trained search of clustering parameters used to sort the new data.

[073] Optionally, the sound receiver includes a frequency filter to detect changes in the frequency of the electric motor and/or vibrator when the toothbrush is in contact with a tooth; and - where the datalogger is activated only when the sound receiver detects a value that meets a predetermined threshold criteria.

[074] Optionally, the sensor to detect contact between the toothbrush and the jaw of a user is: - a pressure sensor; or - an accelerometer.

[075] The pressure sensor may take the form of a piezoelectric material that generates a voltage when pressure applied to the toothbrush head is referred to the piezoelectric material. In some embodiments, the toothbrush bristles can directly transfer pressure from the interaction between the user's jaw and the toothbrush head to the piezoelectric material. In other embodiments, pressure may be applied to the piezoelectric material through a flexible portion of the toothbrush body, typically its neck.

[076] According to a fifth aspect of the present invention, there is provided a toothbrush comprising: - a body including: a head portion and a handle portion; - the body further comprises: - at least a sensor and a reservoir for an active ingredient, the reservoir in fluid communication with the head portion; - a dispenser for dispensing the active ingredient from the reservoir via the head upon receipt of an activation signal; - where the activation signal is triggered in response to information from at least one sensor.

[077] According to a sixth aspect of the present invention, there is provided a toothbrush comprising: - a body having a head portion and a handle portion; - an electric motor and/or vibrator to provide movement and/or rotation of the toothbrush head; - one or more sensors to detect toothbrush movement information when in use; - a data logger to record the detected motion information; and - a sound receiver to detect changes in the frequency of the electric motor and/or vibrator when the toothbrush comes into contact with a tooth; - where the datalogger is activated when one or more sensors or sound receivers detect a value that meets a predetermined threshold criteria.

[078] Other optional features of the present invention are shown below.

BRIEF DESCRIPTION OF THE DRAWINGS

[079] The embodiments of the present invention will be described at the moment by way of example with reference to the attached drawings in which: - Figure 1 shows an example of a smart toothbrush, according to any of the embodiments described herein; - Figure 2 shows a schematic diagram of a smart toothbrush, according to any one of the embodiments described herein; - Figure 3 shows additional schematic diagrams of a smart toothbrush, according to any one of the embodiments described herein. Figure 3a shows an overview of the smart toothbrush, including the location of a printed circuit board (PCB) within the body of the toothbrush, - Figure 3b shows a top view of the PCB and Figure 3c shows a bottom view of the PCB; - Figure 4 shows a schematic diagram of an exemplary system capable of performing a method for monitoring toothbrushing, according to the present invention; - Figure 5 shows an example of an external device, such as a mobile device, for use with the method for monitoring toothbrushing and/or for communicating with any of the toothbrushes described herein; - Figure 6 shows an example of an enhanced interactive screen provided to the user on a mobile device; - Figure 7 shows another example of an improved interactive screen provided to the user on a mobile device; - Figure 8 shows an example of an additional enhanced interactive screen provided to the user on a mobile device; - Figure 9 shows a flow diagram describing the example steps in the method for monitoring toothbrushing; - Figure 10 shows an additional example of an interactive screen provided to the user on a mobile device; - Figure 11 shows an additional example of an interactive screen provided to the user on a mobile device; - Figure 12a shows an additional example of an interactive screen provided to the user on a mobile device before brushing; - Figure 12b shows an example of the same screen viewed during or after brushing; - Figure 12c shows an example of the steps taken to provide feedback in the form of user screens to the user during and after brushing; - Figure 12d shows an example of the steps provided when the toothbrush is unable to connect with the external device; - Figure 12e shows the connections between the external device and an external database; - Figure 13a shows a map of the path taken by the toothbrush during a toothbrushing session using the recorded position and session time information; - Figure 13b shows the same data, divided into each stage of the route; - Figure 13c is a key explaining which parts of the jaw and in particular which tooth surfaces correspond to the numbers 1-10 used throughout this application to label the sections of the jaw corresponding to the 10 segments on the user's screen on the outside . From the device; - Figure 13d shows an example of a multivariate analysis used to match the toothbrush position detected by one or more sensors to a relevant segment on the screen shown to the user on the external device; - Figure 13e shows a map of an ideal trajectory created using a street vendor machine learning algorithm; - Figure 14 shows examples of steps taken to track the path (that is, the trajectory) of the toothbrush during a brushing session, in order to provide feedback to the user; - Each of Figures 15a, 15b, 15c, 15d and 15e shows respective embodiments of a smart toothbrush, according to the present invention; - Figure 16 shows an example of the steps taken to track the path (that is, the trajectory) of the toothbrush during a brushing session, in order to provide the user with dosing triggers and/or dosing control; - Figure 17 shows an example of a tracking system, according to an embodiment of the present invention; - Figure 18 shows an additional example of a tracking system, according to an embodiment of the present invention; - Figure 19 shows an example of processes followed by a smart brush with a magnetic sensor, according to an embodiment of the present invention; - Figure 20 shows an example of data taken using the system of Figure 17; - Figures 21a and 21b show examples of data from calibration measurements performed through a tracking system to record the position of a toothbrush during toothbrushing; - Figures 22a and 22b show examples of additional calibration to correct the arbitrary orientation of the device performed through a tracking system to record the position of a toothbrush during toothbrushing, according to the present invention; and - Figures 23a and 23b show examples of an output from a toothbrush sound receiver, in accordance with or for use with the present invention.

DESCRIPTION OF EMBODIMENTS OF THE INVENTION TOOTHBRUSH

[080] A smart toothbrush according to the present invention is described below in relation to Figures 1 to 3. The smart toothbrush (1) comprises a toothbrush body, which consists of a head (2 ) to contact a user's teeth and a cable (3) to contact a user's hand.

[081] The head includes a series of bristles (21) that come into contact with the user's teeth and gums during toothbrushing to clean plaque and debris. The series of bristles (21) is normally mounted on a neck piece (22) that connects the head to the handle (3) of the toothbrush body.

[082] The body of the toothbrush is hollow, with an outer casing that defines one or more cavities, within which intelligent components are located, such as sensors, a power source, a screen and the means of communication. Examples of components located within the cavity include: a screen (41); sensors (42) (including one or more of the following: an accelerometer, a gyroscope and a magnetometer (42)); a microphone (43); a power supply (such as a rechargeable battery), a computing module including a processor and a communication module.

[083] By incorporating a plurality of sensors in the same device, the smart toothbrush is able to determine a number of parameters, including: orientation (by means of an accelerometer and/or gyroscope); average sound level (through a microphone); axis correlations (by means of a magnetometer); phase velocity (via accelerometer).

[084] The handle has a curved outer part with ergonomic curves, including an outer convex portion (31) that acts as a thumb rest, but which also provides a corresponding cavity for larger components, such as the screen (41).

[085] The compute module typically includes a memory and a processor, the compute module processor configured to perform one or more desired functions.

[086] For example, in one or more embodiments, the processor is programmed to record the position of the toothbrush as detected by one or more of the sensors, at various points during a toothbrushing session. This record can occur at repeated time intervals throughout the use of the toothbrush by the user and the processor can also be programmed to record the time (in memory) in which each detected position was detected.

[087] In some embodiments, the processor is also programmed to produce a map of the path taken by the toothbrush during the toothbrushing session using the recorded position and time information.

[088] The toothbrush includes an on/off switch (not shown), usually in the form of a capacitive switch. The processor can be programmed to initiate an automatic shutdown after the timer detects a period of inactivity that extends beyond a certain threshold. The prolonged period of inactivity can be measured against a specific sensor, for example when no activity is detected by the accelerometer for the given threshold time. In other cases, the period of inactivity may require that two or more sensors show no activity in the same time frame. The timer (which may be a part of the computing module) may also include a trace to provide an indication to the user once a predetermined period of activity has been measured. For example, the indication can provide a signal to the user once a continuous record of activity has been measured by one sensor or by two or more sensors simultaneously for a predetermined brushing time (a sensible value for which would be “2” minutes ).

[089] The communication module can take the form of a wireless communication module, such as a Bluetooth module, from which data can be transmitted and/or received. In addition to providing a mechanism for communicating with external components such as external sensors and/or computers (including mobile devices and smart mirrors) during normal use, the communication module also provides an interface through which automatic downloads of data can be performed after periods when the brush was not connected to the application.

[090] The electrical components can be mounted on a single PCB 45, an example of which is represented in Figures 3a, 3b (upper part of the PCB) and 3c (lower part of the PCB), in which the following reference numbers indicate the following components: - U3: microphone or sound receiver; - U7: communication module, such as a Bluetooth module, specifically Bluetooth Low Energy (BTLE); - U2: temperature sensor and/or relative humidity sensor (ie a thermometer and/or hygrometer); - U12: temperature sensor (ie a thermometer); - D1: LED (light emitting diode). This can take the form of a tricolor LED and can be used as a warning indicator and/or as a status indicator. Warning indications may be related to brushing technique or they may be related to toothbrush operation. For example, the LED can provide a visual indication of when charging is taking place or when the power source requires recharging; - P2: Curvature sensor connector, normally to measure the bend in the neck (22) of the smart toothbrush. The bending sensor can take the form of a piezoelectric bending sensor. In this way, it is possible to detect when the user is applying too much force to the teeth / gums through the toothbrush head. The processor can be configured to detect when a predetermined “curvature limit” is reached and issue a warning to the user. The warning can take the form of a visual indication (for example, lighting or flashing of the LED) or an audio warning (through a loudspeaker); - P1: loudspeaker connector, for sending signals to the loudspeaker, the loudspeaker is also housed inside the housing of the toothbrush body; - U4: magnetometer; - U5: combined accelerometer gyroscope, although these components, alternatively, can be supplied separately; - U1: processor, more specifically a microprocessor; - U9: memory in the form of a pen drive. Combined with the processor, this memory forms the “compute module”. The memory can function as a “data logger”, which records the information received from one or more of the sensors; - U11: voltage controller; and - U13: voltage controller.

DOSAGE

[091] Each of Figures 15a, 15b, 15c, 15d and 15e shows respective embodiments of a smart toothbrush, according to the present invention, in which the toothbrush includes one or more reservoirs for the (s) active ingredient(s). The reservoirs and associated dosing mechanisms described below in relation to Figures 15a to 15e can be applied to the smart toothbrush described above in relation to Figures 1 to 3.

[092] Active ingredients are typically liquid, but may take other forms (eg, gas, gel, foam, or other gas/liquid mixture). Examples of active ingredients include a serum or a hardener. The active material can include antimicrobial properties or cosmetic properties such as teeth whitening. In some embodiments, the active ingredient is a solid ingredient and a reservoir which is in fluid communication with the solid ingredient contains a solvent. When the solvent comes into contact with a portion of the solid ingredient, it dissolves an amount of the solid ingredient which can then be conveyed to the toothbrush head as the active ingredient to be dispensed. An advantage of such an embodiment is the fact that the frequency at which the solid ingredient needs to be replaced is less than the frequency with which a liquid or gaseous ingredient would need to be replaced. If the solvent stored in the reservoir is water, it will be easily available to the user.

[093] The reservoir and dosing mechanism allow adverse ingredients to be kept separate (for example, an active component that would interact negatively with toothpaste can only be dispensed when the toothpaste has been washed). It can also provide a mechanism for adding extra ingredients that will interact positively with other ingredients, such as toothpaste.

[094] As shown in Figures 15a to 15d, some embodiments comprise a reservoir (1506) for the active ingredient. The reservoir (1506) is in fluid communication with the toothbrush head through a fluid channel (1506b). In some embodiments, such as those in Figure 15a-c, the release of an active ingredient is achieved through a biomechanical pumping system, triggered by manual actuation by the user. For example, at least a portion of the reservoir can be formed of a flexible material that the user pushes or squeezes to release the active material. The toothbrush can be set to sound an alert, usually an audio alert to indicate to the user that it is time for them to engage with the brush (e.g. to squeeze a portion of the brush) in order to release the active ingredient. .

[095] In other embodiments, such as those shown in Figure 15d and 15e, the reservoir includes an electronically controlled actuator (1507), (1508), such as a pumping system or a valve, which is directly controlled by the computing module on the toothbrush. The pumping system can be one or more of the following: microfluidic; piezoelectric (similar to an inkjet printer).

[096] In the embodiment of Figure 15d, the reservoir (1506) for the active ingredient and the electronic control (and pump) (1507) are located inside the toothbrush handle. In the embodiment shown in Figure 15e, the electronics, pump and active ingredient are all located in a removable module (1508) located within the head of the toothbrush body. Advantageously, this removable module can be easily relocated to a new toothbrush when the bristles of the old toothbrush wear out.

[097] In the realization of a smart toothbrush (1501) shown in Figure 15a, the active ingredient is delivered from the reservoir (1506) to the user through openings located at the base of the bristles.

[098] In the embodiment of Figure 15b, the toothbrush head (1502) comprises the bristles and one or more ingredient delivery structures (1510) located within the bristles. Instead of delivering the ingredient at the base of the bristles, the ingredient delivery structures (1510) transport the ingredient in a direction parallel to the longitudinal axis of the bristles, before releasing the active ingredient. In this way, the user can more precisely target specific areas of the mouth to deliver the dose of the active ingredient. The ingredient delivery structure(s) (1510) can take the form of hollow bristles, hollow sheets or microtubes wherein the hollow sheets or microtubes can be formed from a material such as a material based on rubber which is different from the material of the bristles. In other embodiments, the ingredient delivery structure(s) may take the form of a sponge.

[099] In the embodiment of Figure 15c, the toothbrush head (1503) does not contain conventional bristles. Rather, they only comprise the ingredient supply structures (1510), such as the hollow bristles and/or blades.

[0100] While the heads of Figures 15a, 15b and 15c, and more especially the bristle options, are shown in combination with a manually operated toothbrush, they can equally be applied to the toothbrush bodies of Figures 15d and 15e . Similarly, although the smart toothbrush “smart strokes” are not shown in the schematic diagrams of Figures 15a through 15e, each of these dosing toothbrushes will contain the smart strokes described elsewhere in this application (including a or more sensors), the computing module, and the like.).

[0101] The reservoir and associated dosing mechanism allow adverse ingredients to be kept separate (for example, an active component that would negatively interact with the toothpaste can only be dispensed when the toothpaste has been washed). It can also provide a mechanism for adding extra ingredients that will interact positively with other ingredients, such as toothpaste.

[0102] As will be discussed in more detail below, the smart toothbrush may include an electric motor and/or a vibrator to provide movement and/or rotation of the toothbrush head.

[0103] In such embodiments, the sound receiver can be used to measure the frequency of the electric motor and/or vibrator. A program executed by the processor records this frequency over time and detects changes in the frequency of the electric motor and/or vibrator that occur when the toothbrush is in contact with a tooth. This detection of contact between the head bristles and the tooth can be used as a trigger for other events (eg dosing, measuring, activating sensors).

SYSTEM

[0104] Figure 4 shows a schematic diagram of an exemplary system capable of performing a method for monitoring toothbrushing, according to the present invention;

[0105] The system comprises the toothbrush (1) and a mobile device (20), on which an application (2) can be stored and executed, the mobile device is communicably connected to the toothbrush. The mobile device can be connected to one or more computers via a network (40). Each mobile device and toothbrush can wirelessly communicate with additional items in the system, such as external sensors. For example, an external position sensor or a magnetic field generator. This could be a one-to-one communication channel such as Bluetooth or it could be providing access to additional network items (40). According to some embodiments, the mobile device can be replaced by a different type of external computer, such as a smart mirror or wall mounted computer.

[0106] The wireless communications (4a) between the toothbrush (1) and the mobile device (20) enable the flow of information between them. This flow of information could be a flow of data from the toothbrush to the application running on the mobile device, such as the raw data from one or more of the sensors on the toothbrush or the processed data that has been recorded by one or more of the sensors on the toothbrush. sensors on the toothbrush and then processed by the toothbrush processor before being routed through the toothbrush communication module to the mobile device.

[0107] The information passed between the toothbrush communication module and one or more mobile device interfaces may include toothbrush parameter updates.

[0108] Wireless communications (4b) between the mobile device (20) and the network (40) may also include data flow. This is usually processed by the toothbrush or the app (2) on the mobile device, but it can also take the form of raw data. Brush parameter updates and software updates for the app (2) can also be sent from the network (40) to the mobile device (20).

[0109] The network may include the internet and/or one or more local area networks (LANs) or wide area networks (WANs).

[0110] One or more external computers (30), such as servers, may have connections (4c) to the network to communicate with the mobile device (20) over the network (40). One or more external computers include data storage and data processing. Data stored and processed on the external computer(s) is typically derived from a plurality of different users (via a plurality of mobile devices and smart toothbrushes) and may include personal data, although it may be anonymous. Accordingly, the external computer(s) provide(s) a platform for analysis of data obtained from all or at least a proportion of the total number of users who use their respective toothbrushes in their own houses. The communication channel between the company user (50) and the external computer(s) (30) therefore includes the flow of information from the external computer to the mining insights user of data from data analysis. It will also include the flow of settings and other user information from the company to the external computers. For example, software updates can originate from the company user (50) and reach the mobile device (20) via the external computer (30) and the network (40).

[0111] Data can be sent to the server upon completion of a toothbrushing session.

[0112] External parties, such as dentists, may have access to data stored in the external computer (30) through the network (40). Alternatively, the user himself can relay information from the toothbrush or mobile device to the dentist.

MOBILE DEVICE

[0113] Figure 5 shows an illustrative embodiment of a mobile device that is suitable for practicing the various aspects and embodiments of the present invention. In particular, the mobile device is suitable for use with the method for monitoring toothbrushing described herein and also for communicating with any of the toothbrushes described herein. The mobile device can include all of the components shown, but it can contain more or fewer components. It should be understood that, in embodiments where the mobile device is replaced by alternative external computers, such as a smart mirror or a wall-mounted computer, the alternative external computer will include the same traits as those described below in relation to the mobile device.

[0114] The mobile device (20) usually includes a digital imaging device (60), such as a digital camera, to record digital photographs. These photographs can then be stored in a data storage section of memory (22).

[0115] The mobile device (20) shown includes a central processing unit (CPU) (21) in communication with a memory (22) and various other components.

[0116] These other components of the mobile device (20) shown include a power supply (23), a network interface (24), a screen (25), an input / output interface (26), an audio interface (27), a light signal (28) and user controls (29).

[0117] The power supply (23) provides the energy used by the mobile interface and can take the form of a rechargeable battery and/or external power source.

[0118] The network interface (24) provides a mechanism for the mobile device to communicate, directly or indirectly, with any compatible smart device and includes circuits configured for use with one or more communication protocols and technologies, including but not limited to: GPRS; GSM; TDMA; transmission control protocol / Internet protocol (TCP/IP); CDMA; WCDMA; WiFi; 3G, 4G, Bluetooth or any other wireless communication protocol.

[0119] The screen (25) can be an LCD (liquid crystal display), a plasma screen or any other suitable electronic screen and can be touch sensitive, which can include a screen configured to receive a single digit entry human or a stylus.

[0120] The input/output interface(s) (26) may include one or more ports for outputting information, for example, audio information through headphones, but it may also be a gateway configured to receive signals, including remote control signals.

[0121] The audio interface (27) usually includes a speaker that allows the mobile device to emit signals and a microphone that allows the mobile device to receive audio signals including voice control inputs for use in audio control applications.

[0122] The mobile device (20) shown includes a light signal (28) that can be used in conjunction with the digital imaging device to illuminate an object of which a photograph is being taken.

[0123] The user controls (29) can take the form of external or sliding buttons that allow the user to control various functions of the mobile device.

[0124] An application saved on the device can be configured to interact with the various components of the device, so that when receiving input from one or more of the user's controls.

[0125] The computer program described herein may take the form of an application stored in memory (22).

[0126] The mobile device can be connected to an external computer (30) directly or via a network (40) so that computationally extensive calculations can be performed through a computational module in the external computer, the external computer is more powerful than the mobile device and therefore able to perform calculations faster.

[0127] The mobile device (20) can also be configured to exchange information with other computers through the network (40).

“APP” APPLICATION

[0128] Figures 6 to 8 show examples of interactive screens provided to the user in the application (2) of the mobile device (20).

[0129] The first example, shown in Figure 6, is a graphical user interface (GUI) (21) presented to the user by the application (2), the GUI including two “threads”. A first segment provides an indicator for brushing as measured by the app as occurring in the upper jaw, and the second segment provides an indicator for brushing as measured by the app as occurring in the lower jaw and upper jaw, respectively.

[0130] An improved example is shown in Figure 7, where 6 segments 6c, 6d, 6e, 6f, 6g and 6f correspond respectively to: - the upper bite surface (6c); - the lower bite surface (6d); - the upper left inner and upper right outer surfaces (6e); - the upper right inner and upper left outer surfaces (6f); - the lower left inner and lower right outer surfaces (6g); - the inner surfaces lower right and outer and lower left (6h).

[0131] An additional improved example is shown in Figure 8, where a total of 10 segments 6i, 6j, 6k, 6l, 6m, 6n, 6o, 6p, 6q and 6r correspond to: - the upper bite surface (6i ); - the lower bite surface (6j); - the upper right outer surface (6k); - the upper right inner surfaces (6l); - the upper left external surface (6m); - the upper left inner surface (6n); - the lower right external surface (6th); - the lower right inner surface (6p); - the lower left external surface (6q); - the lower left inner surfaces (6r);

[0132] The position of the segments mimics the position or the various surfaces around the mouth with the segment corresponding to the upper bite surface located in the upper part of the GUI and the segment corresponding to the lower bite surface located in the lower portion of the GUI. Similarly, segments for the “left” surfaces are located on the left side of the GUI and segments for the “right” surfaces are located on the right side of the GUI.

[0133] With the exception of the upper and lower bite surfaces, the segments of the remaining tooth surfaces are grouped in pairs. For example, the upper-right outer surface and the upper-right inner surface are located adjacent to each other as subsegments of a larger segment. This sketch of segments was specifically selected to add to the ergonomics of the screen on a mobile device. By refining the information display to be optimized for human use, the provided system is more user-friendly and intuitive to handle. This is especially important in the field of toothbrushing, as the requirement for a high level of attention to detail can drive users away.

[0134] It was found that the 6-segment system did not provide sufficient degrees of release to support a custom model. That is, the characteristics of an individual's brushing techniques were “lost” since the location could only be attributed to one of the six regions of the mouth. By dividing the jaws into 10 segments, the detail that can be measured is significantly greater and enables custom models to be supported. The ability to build personal models that map sensor data to a specific user underpins the ability to record measurements during “free brushing”, turning sensor data from the free brushing session into location information by accessing a lookup table that contains the calibration details for that specific user.

[0135] When the sensor information detected detects that the applied acceleration or pressure has exceeded a predefined threshold value, a warning can be displayed to the user to inform him that he is brushing too hard. This signal can take the form of a color change on the mobile device's visual display, especially a color change that overlays or highlights a graphic corresponding to the portion of the mouth in which brushing was taking place when the limit was exceeded. The visual warning may or may not be accompanied by an audio warning and/or a displayed message such as “brushing too hard”. Consumer studies have shown that audio prompts are especially effective in the field of toothbrushing.

[0136] Figure 9 shows a high-level flowchart, describing the example steps in the training phase of the method for monitoring toothbrushing.

[0137] After the toothbrush and mobile device are obtained and the application for the mobile device is downloaded, the user is ready to start (s1).

[0138] Initially, the user must open the application on the mobile device (s2) and ensure that the mobile device is connected to the toothbrush (s3) via Bluetooth or other wireless communication.

[0139] Figure 10 shows an additional example of an interactive screen provided to the user on a mobile device, especially an image that can be presented to the user during a guided mode. The image shows a schematic of the jaws, with a section of teeth highlighted, the highlighted section corresponding to a segment of the 10-segment display.

[0140] As shown in Figure 11, an interactive screen is provided to the user on a mobile device, providing them with the option (s4) to select one of two brushing modes: a training mode (111) or the brushing mode free (112).

[0141] Initially, the connection to the app's free brush function (s6c) is not actionable, appearing as grayed out text. Only when the training mode (s6a) has received and stored enough information to produce a personal model on the server (s6b) does the connection for free brushing become actionable.

[0142] During toothbrushing (in both modes), the data received by one or more toothbrush sensors are processed through the toothbrush computing module and/or external processors on the mobile device or on a computer external. This is described in more detail below with reference to Figures 12a to 12c.

[0143] Depending on the data received and the processing algorithms applied, various outputs can be produced and displayed to the user on the mobile device. For example, Figure 12a shows a user interface displaying live feedback to the user at the start of a toothbrushing session where all segments are empty (121). As the brushing starts (Figure 12b), the sensor data is processed and the user's performance displayed in the form of "obturation" of the segments (122); a complete segment (123) indicating that a pre-set brushing threshold (eg number of brushings) has been reached.

[0144] An example of the process followed by brushing teeth during brushing is shown in Figure 12c. These steps will be performed regardless of whether training mode (ie guide mode) or “free brushing” mode is selected. The difference between the two modes is that, in training mode (guide), the mobile device will provide a guide for the user to follow during brushing. The way data is processed and provided to the user will remain the same.

[0145] In a first step (s121), the toothbrush is turned on. This may be accomplished via a user-controlled switch or button, or it may be in response to motion or touch detection via one or more of the sensors.

[0146] When the toothbrush is turned on, the data from one or more sensors are pre-processed (s122) in the computing module processor. This pre-processed data can be stored in the memory of the toothbrush itself or can be sent to the mobile device and/or other device such as a smart mirror or another computer.

[0147] Data from one or more of the sensors are used to determine whether or not toothbrushing has started. For example, in some embodiments, toothbrushing is detected when the toothbrush receives a combined sound and motion detection via the microphone and accelerometer. Each of these values may need to exceed a predefined threshold to determine that toothbrushing has started. In other embodiments, a different combination of sensor triggers may be used to determine whether toothbrushing has started, such as a force sensor in combination with a motion sensor (e.g., accelerometer).

[0148] When no tooth brushing is detected, the smart toothbrush and all connected devices will be put into sleep mode (s124). After a preset period of time (“timeout”), the system, including the smart toothbrush, will turn off (s125).

[0149] If toothbrushing is detected, the statistical models will be applied to the pre-processed data (in the compute module of the brush or in the mobile device). Statistical models calculate one or more of the following parameters (s126): - brushing count; - brushing intensity; - duration of brushing; - which segment is being brushed; - time spent brushing one or more threads.

[0150] During brushing (as shown in Figure 12b), live feedback is presented to the user by the mobile device. This live feedback (s127) can include one or more of the following: - brush count; - warning message that the brushing intensity has exceeded a predefined limit; - a guide to be followed (for the training mode), in the form of highlighted sections of teeth, the highlighted section corresponding to a segment; - the live feedback of segment coverage (free brushing mode); - timer, generally monitoring the duration of tooth brushing.

[0151] After a predetermined period of time in which no activity has been measured by the sensors or in response to a manual switch, the toothbrush sends a signal to the mobile device to indicate that the brushing session is over and the mobile device (or another device, such as a screen or smart mirror) displays end-of-session feedback to the user and/or recommendations (s128).

[0152] Again, after a defined timeout, the system will shut down (s129).

[0153] In some embodiments, the toothbrush is configured to operate in a standalone mode, when no contact can be made with a mobile device (or other device). This is described in greater detail with reference to Figure 12d below.

[0154] In an initial step, the toothbrush is turned on (s131), via a switch or button operated by the user, or in response to motion detection or touch by one or more of the one or more sensors.

[0155] The toothbrush then tries to connect (s132) to an external device, such as a mobile device (20) or another device (for example, a smart mirror, a wall-mounted computer or a smart cup ). The connection is usually a wireless connection such as Bluetooth.

[0156] The moment no external device is found by the toothbrush, the toothbrush starts operating in a “data mode” (s133). In this data mode, the sensor data ID is pre-processed and saved in the memory of the toothbrush compute module. The toothbrush processor is programmed to provide basic feedback via visual or audio signals emitted from a light source or a speaker in the toothbrush, in response to the processor detecting that specific criteria have been met. . For example, audible or visual signals can be emitted in response to: - sensor data above a threshold indicating brushing is taking place; - sensor data detecting that a predefined duration of brushing has been recorded; and/or - sensor data that detects that the brushing intensity has been registered, which is beyond the preset limit.

[0157] After a predetermined amount of inactivity, the system will shut down (124).

[0158] If a successful connection has been achieved between the mobile device or another device, a data transfer will take place (s135). This will include synchronizing the data between the toothbrush and the device, as well as sending data from the toothbrush sensor to the device. The moment historical data has been stored in the brush but not transferred to the external device, this historical data will be transferred. The tooth brushing session will be carried out as usual (s136) in training mode or free brushing mode as described in relation to Figure 12c, steps s126 to s129 above.

[0159] As an additional step (s137), the statistical analysis of the historical data corresponding to the sessions performed when the toothbrush and the external device are disconnected will be performed.

[0160] In some embodiments, the device (for example, the mobile or other device) with which the toothbrush interacts is configured to connect with an external database, such as an external computer or server (30). As shown in Figure 12e, the device must be powered on (s141) and then it will attempt to form a database connection (s142). This connection can be performed via a network (40). If a connection between the device and the database is successful, the application (i.e. program) running on the device will trigger the data transfer (s143) between the device and the external computer on which the database is located. data is located and can also trigger the analysis to be performed by the external computer. For example, upon achieving a successful connection, the following steps can be taken: - historical data can be downloaded from the device to the database; - data can be synchronized between the database and the device; - statistical models performed by the device on toothbrush data can be updated; and - one or the modes in which the application can run can be updated. For example, the external computer, based on the database information, may enable the application to unlock certain modes, such as “free brushing”.

ROUTE

[0161] Figure 13a shows a map of the general path taken by the toothbrush during a toothbrushing session using the recorded position and session time information. Each step in the pathway is shown in Figure 13b, where the numbers in the sequence 5> 3> 2> 8> 1> 4> 6> 10> 9> 7 correspond to specific parts of the jaw as shown in Figure 13c. Each of these numbered parts of the jaw corresponds to a respective one of the 10 segments (121), (122), (123) displayed to the user by the mobile device during brushing, as shown in Figures 12a and 12b.

[0162] Figure 13d shows an example of a multivariate analysis used to match the detected position of the toothbrush through one or more sensors to a relevant segment on the screen shown to the user on the external device. In this example, the clusters (corresponding to the 10 segments) are shown in a trace space (projected onto a suitable 2D subspace). Quadratic discriminant analysis was used to estimate the normal approximation (circles around each cluster of points) for each segment cluster.

[0163] The path is produced through a smart toothbrush that includes at least one toothbrush body, comprising a head (2) for brushing and a handle (3) as well as at least one sensor to detect the position of the toothbrush in the mouth at various points during a toothbrushing session.

[0164] The smart toothbrush even includes a timer to record the time each detected position occurs; and a computing module having a memory, the computing module configured to (i.e., programmed to) record the detected position at various points during a toothbrushing session, along with recording the time each detected position was detected. From these recorded points, the processor of the computing module produces time series data that correspond to a map of the path taken by the toothbrush around the jaw during the toothbrushing session.

[0165] It will be considered that other methods for measuring or determining a trajectory taken by a toothbrush around the jaw during a toothbrushing session are also possible. What is important is the trajectory, rather than the method and sensors by which the trajectory is determined and/or measured.

[0166] Normally, the computing module is programmed to use a machine learning algorithm, for example, to solve a street vendor problem, process the recorded position and time information and produce a map of an ideal trajectory to be traveled by toothbrush during toothbrushing session.

[0167] One or more paths taken by the user's toothbrush can be registered in the external computer database (30). Newly recorded tracks can be checked against previously recorded tracks. If a deviation from a previously taken (and stored) route is detected, a processor in the mobile device can trigger a warning signal to indicate to the user that unusual behavior has been detected. This notice may take the form of a message displayed on the mobile device screen and may or may not be accompanied by an audio signal. The amount of deviation required before the warning signal is triggered is predefined, either as a standard predefined value built into the software running on the device, or through a predefined amount that is entered by the user or healthcare professional.

[0168] By analyzing the time series data that correspond to the path taken (i.e., the path taken) by the user around the jaw, a distance between these and other paths can be calculated to show how similar / different they are between yes. The distance can be the geometric distance or, for example, it can be a measure of the distance between the strings of symbols associated with the paths, for example, the Levenshtein distance. Using distance enables clustering to occur on brushing paths, to see how similar one brushing path is to another.

[0169] For example, distance metrics can be used to determine how close a recorded brushing path is to that recommended by a dentist, as well as to determine whether the user is consistent in their brushing habits. Typically, a user will be consistent in their brushing habits, therefore, a deviation from previously recorded “regular” courses can be an early indicator of a problem, such as tooth sensitivity or gum disease. By triggering a warning about such a deviation, the user can be made aware of potential problems before they are otherwise.

[0170] Figure 13e shows a map of an ideal trajectory created using a street vendor machine learning algorithm. A more efficient brushing technique can be implemented by training the user to follow this calculated optimized path. The path followed by the path was optimized by minimizing a suitable cost function related to the transition probabilities: the lower the probability of a transition, the higher the associated cost. Transition probabilities are a function of spatial distance and biomechanical constraints such as dexterity. In this case, it was verified that brushing the regions in the order of 5> 9> 1> 3> 10> 7> 8> 4> 2> 6 is more efficient than the path taken by the user in Figure 13a.

[0171] The steps taken in analyzing the smart toothbrush data and providing user-related feedback are described in more detail below in relation to Figure 14.

[0172] Once the toothbrushing session is finished (free or trained brushing) (s141), the position data from one or more sensors and the respective time information from the data are used to produce a time series (i.e. , a trajectory or path) for that toothbrushing session (s142).

[0173] The time series is sent from the user's device to a database, usually on an external computer, where it is analyzed (s143) and can be compared with previous journeys by the same user or by other users. The external computer is user accessible via the network (40). The database can also receive data from other users over the network (s144), therefore making it possible to analyze an entire population of users, rather than just a single user. Additional entries can also be received into the database over the network. This can include information entered by the user themselves, for example, whether they are right-handed or left-handed, whether they have any problem areas in their mouth that they are aware of, or extra information they may have received from their dentist, such as the need to focus more on a special area of the mouth when brushing teeth.

[0174] Once data has been accumulated in the database, data mining and statistical analysis (s146) of the data can be used to perform one or more specific functions. Examples of such functions include: - the calculated average path for a given user can be updated based on the most recently recorded path path; - the transition probabilities can be calculated, the transition probabilities is the probability of going to state Y, since the previous state was X; - Markov models can be applied (which use transition probabilities); - ideal trajectories can be calculated; - a change in route or anomaly in a route can be detected.

[0175]The above steps can be performed on the database, regardless of whether the device is still “online” and therefore connected to the database over the network.

[0176] If the device is online, the feedback that is presented to the user on his device (20) is updated based on the results of previous analyzes and statistics (s147). Feedback updates may include one or more of the following: - providing an optimal trajectory (such as that in Figure 13e), which can be more efficient and/or avoid difficult transitions; - sending a notice to notify the user of a detected change. The warning may signal the identified potential problem area to the user, for example by highlighting the jaw region corresponding to the relevant “segment” in a jaw image; - the suggestion of a different starting point, for example, deliberately starting from a region of the mandible that, according to the statistical results, the user tends to neglect; and - recommending products to the user based on observed behaviors (eg sensitive teeth products).

[0177] The ability to calculate and present a route to the user and the ability to analyze a user's time series data can be used in conjunction with the dosing mechanisms previously described in relation to Figures 15a to 15e. This is described in more detail below in relation to Figure 16.

[0178] First, a smart toothbrush with a dosing mechanism, such as any of those shown in Figures 15a to 15e, is supplied (s151) and turned on.

[0179] During toothbrushing, data is obtained from one or more sensors (s153). This data is processed (s153) either in the toothbrush computing module's internal processor or in the mobile device. This processing includes calculating the location of the toothbrush in real time. In other embodiments, tooth traits can be monitored in real time, such as plaque resistance or tooth whiteness, both of which can be detected by a camera on the toothbrush.

[0180] A dosing control algorithm is applied (s154) to the processed data, the algorithm including the adjusted conditions that need to be met for dosing to occur. These conditions can be set by the user through the device (eg mobile device) before brushing takes place. The dosing algorithm tracks the position of the toothbrush within the jaw and detects when a condition is met. For example, when the sensors' location data shows that the toothbrush head is in a specific location, which could correspond to one of 10 specific segments. Other sensors that may be used to provide the appropriate data to generate a trigger or activation signal to deliver one or more active ingredients from one or more reservoirs may include any of the following types: (i) light or camera based sensors to detect and dead (eg stained) plaque, tooth stain, tooth color, fluorescence, implants, dental filling, gloss, shine, blood or presence of toothpaste; (ii) ion electrodes selective for fluorine, zinc (Zn), calcium (Ca) or tin (Sn); (iii) sensors for dissolved gases; (iv) gas sensors for odors; (v) a voltmeter for the Redox potential; (vi) a sensor for hydrogen peroxide (H2O2); (vii) a viscosity sensor; (viii) a hormonal sensor; (ix) a temperature sensor; (x) a conductivity sensor. Therefore, dosing or dispensing of one or more active ingredients from one or more reservoirs can be performed in response to a detected level of one or more of the above detected parameters or combinations thereof listed in items (i) to (x) above. .

[0181] The dosing mechanism can be prepared ready for dosing before arriving at the place where the dosing should take place, in a predictive step. This would allow for an increase in the time or amount of effective dosing at the desired location.

[0182] The dosing control algorithm can also update a dosing history record; recording the positions and times at which the dosing occurred along the trajectory of a given path. These data can later be returned to a database on the external computer (30).

[0183]External input can be provided (s155) for the dosing algorithm. In some embodiments, this external input will include one or more: - an ideal trajectory to be followed during the journey; - recommended dose combinations or sites; - the specifications of the product that forms the active ingredient to be dosed; and - the product manufacturer's updated dosing instructions.

[0184] When the dosing control algorithm detects that a condition for dosing has been met, the processor in the toothbrush will control the release (s156) of the ingredient, initiating a trigger for dosing to occur. For toothbrushes with a biomechanical dispensing mechanism, this trigger could be in the form of a signal provided to the user (eg audio or visual signal) to alert the user that they need to actuate the biomechanical mechanism itself. In other embodiments, where the toothbrush includes an electronically controlled pump or valve, the driver may simply be an electrical signal that drives the pump or valve to eject the required dose from the reservoir through the brush head.

[0185] When and/or what is administered by the toothbrush can be influenced or driven by data that is fed to the toothbrush from an external source, rather than data that is measured by sensors on the toothbrush. For example, advice from a dentist, or user preferences (eg the taste of the dose) can be used as data to influence and/direct dosing. In addition, data from other diagnostic sensors, which may be internal or external to the toothbrush, can be used to provide data that can be used to influence or direct dosing.

[0186] Examples of a tracking system according to the present invention are described below with reference to Figures 17 and 18.

[0187] Figure 17 shows an example of a tracking system for recording the position of a toothbrush during toothbrushing, according to an embodiment of the present invention.

[0188] The tracking system (1701) includes a smart toothbrush (1702) that may contain one or more of the traits shown above, in particular those traits established in relation to the embodiments shown in Figures 1 to 3 and also in Figures from 15a to 15e.

[0189] In particular, the toothbrush includes a head portion (2) and a handle portion (3). The toothbrush body comprises one or more sensors, including at least one training sensor such as an accelerometer or a gyroscope.

[0190] In addition, the smart toothbrush (1702) of this embodiment includes a sensor to detect contact between the toothbrush and a user's jaw. This, for example, could take the form of a sound sensor.

[0191] The system (1701) includes one or more magnetic field generators, and the smart toothbrush also includes a magnetic sensor for detecting location within a magnetic field. The magnetic sensor detects the absolute position of the toothbrush within the field created by the magnetic field generator. In this embodiment, the magnetic field generator (1703) takes the form of a plurality of magnets located in a pair of glasses (1704). By incorporating the magnetic field generator into glazing and ensuring that all communication between the different elements within the system is wireless, the supplied system is suitable for domestic use. This is in contrast to prior art systems, such as that of US Patent 2012/0,310,593, which require specialized and cumbersome equipment and are therefore only suitable for use in combination with a visit to a healthcare professional or dentist.

[0192] The system further comprises an external device (1705) which in this embodiment takes the form of a mobile device containing the application described in relation to Figure 9. The toothbrush (1702) interacts with the mobile device (1705) in the same way manner as described in connection with previous embodiments, only with the added benefit of a magnetic sensor output that is registered to the toothbrush by the magnetic sensor and can be processed on the toothbrush itself, or sent to the mobile device for processing at in order to provide an output of the location of the toothbrush.

[0193] Unlike previous achievements, the presence of the magnetic field generator and the magnetic field sensor makes it possible to measure a real position of the toothbrush, instead of depending on the determination of the probable position based on motion and orientation sensors, such as accelerometers. In this way, it is possible to provide the user with much more accurate information about where the toothbrush is at any given moment.

[0194] The magnetic systems described herein can be used in two different ways. In the first of the two ways, toothbrushing always takes place in the presence of a magnetic field, the magnetic field provides a mechanism to increase the resolution of the system. In such situations, magnetic field measurements also remove the need for a training phase, as the actual position of the toothbrush can be measured in real time during free brushing.

[0195] In principle, the magnetic system can provide a sufficiently wide resolution to provide tooth-to-tooth tracking of the toothbrush. However, in reality, the size of the toothbrush head is generally larger than the size of a tooth and therefore limits the resolution of the measurements that can be obtained.

[0196] It is also envisaged that the system can be used in a second way in which the magnetic field is used in the training phase to provide a connection between the real measurements that can be detected by the magnetic sensors and the extrapolated measurements that are performed through evaluation of data obtained from the accelerometer data.

[0197] The values of M (Mx, My, Mz) are measured in each tooth and used to build the lookup table.

[0198] Alternatively, measurements can be taken only on a subset of teeth (for example, a front, a left rear, a right rear) + jaw use model (see publication WO 2008/116743A1) and model of field to extrapolate the calibration values to other teeth.

[0199] Since measurements of the absolute position of an object within a magnetic field require that the x, y, and z components be measured, the measurements and calculation to determine the absolute position can be complex. For this reason, measurements of the position of the toothbrush within the magnetic field are recorded only when contact between the jaw and the head of the toothbrush is detected. In this way, the calculations that need to be performed to determine the position from the magnetic data will be simplified, since the toothbrush head must be in a position along the jaw line. A degree of release has therefore been removed from the calculation. It has been found that removing this degree of release can be important when relying solely on motion and orientation sensors such as accelerometers, even when supplemented by low resolution magnetic positioning systems, where relying on dependent accelerometer data. of time can result in a number of possible or misidentified brush positions consistent with the acquired data. Using jaw contact data can easily distinguish between misidentified and true brush position, even when using a magnetic field generator and a magnetic sensor of relatively low complexity and low accuracy. Using a sound sensor to detect contact between the toothbrush and the jaw was found to be an especially simple and effective way of removing the required degree of release.

[0200] Figure 18 shows an additional example of a tracking system, according to an embodiment of the present invention. This embodiment differs from that of Figure 17 only in that the external device is in the form of a mirror (660) and the magnetic field generator (116) is mounted or integrated in the mirror (660).

[0201] Figure 19 illustrates how the magnetic measurements and other sensor measurements taken are processed to arrive at a measurement of which tooth surface is being brushed.

[0202] One or more of the sensors on the toothbrush are used to detect contact between the toothbrush head and the user's jaw teeth (s1901). This makes it possible to determine that brushing is active (s1902). Measurements recorded by specific sensors such as the accelerometer or gyroscope (s1903) can be used to determine the brush orientation (1904), including offset and/or roll.

[0203] The magnetic sensor on the toothbrush is used to measure the x, y and z components of the magnetic field. The z component measurement (Mz, the vertical field component) (s1905) is used to determine whether the upper or lower jaw is being brushed (s1906) and also whether the left or right side of the mouth is being brushed (s1910 ). The absolute magnitude M of the magnetic field can be obtained (s1907) with or without looking up a look-up table (s1908) and makes it possible to determine the position of the toothbrush and therefore in combination with the determination of which part of the mouth is being brushed (s1910) and which jaw is being brushed (s1905), enables the processor to calculate which tooth or teeth are being brushed.

[0204] This information can be combined with the brush orientation determination (s1904) in order to determine which surface of the tooth or teeth are being brushed. Figure 20 shows an example of magnetic sensor data taken using the system of Figure 17. The magnetic sensor (located inside the toothbrush of the present invention) was moved along an artificial jaw in the presence of the field generated by the magnets. Each number in the lot corresponds to a special tooth; number 1, corresponding to the posterior molar, going clockwise to number 14, which corresponds to the right side of the posterior molar. The points for the different teeth are well separated, showing that each tooth has a unique Mz and |M| combination.

CALIBRATION OF MAGNETIC FIELDS

[0205] An initial calibration is normally performed to calibrate the magnetic readings. Magnetic readings are taken at at least three locations along the mandible.

[0206] Figures 21a and 21b provide a simple illustration of how magnetic field measurements, especially the vertical field component Mz, can be used to capture the location of the toothbrush with increased resolution.

[0207] In the experiment of Figure 21a, a magnetometric probe was moved along the mandible (in this case, an upper mandible). To assess variation around a given jaw, the measurement was repeated for the inner, center, and outer positions. As observed in the right batch, the magnitude M of the field makes it possible to estimate the position on the left or right side of the mandible (Figure 21a). Each number corresponds to a specific tooth in a mandible, where from 1 to 7 are located on the left side of the mandible and from 8 to 14 are located on the right side of the mandible.

[0208] As shown in Figure 21b, the vertical field component Mz breaks the left/right symmetry and its sign can be used to determine whether the device is on the left side (teeth 1 to 7) or the right side (teeth 8 to 14).

[0209] Figure 22 shows an example of additional calibration to correct the arbitrary orientation of the device. To demonstrate correction for arbitrary device orientation, the probe was held in different orientations for different teeth. The field magnitude is invariant, however, the measured Mz component is strongly affected (Figure 22a). Using the accelerometer data, the gravitational acceleration can be separated from the general acceleration data using a low pass filter. The acceleration due to gravity can be used as a reference point against which the coordinate system is updated to recover only the vertical field component (Figure 22b). This is an example of how combining multiple sensors can result in location measurements with improved accuracy. For example, when the sensor combination includes a sound sensor, a magnetometer, and an accelerometer, the magnetometer measures position. The sound sensor simplifies data interpretation as it can detect when contact is made between the toothbrush head and the jaw, so the measured location can only be located at one jaw position. The accelerometer allows the location data to be improved, since it can be used to correct the rotational position (orientation) of the toothbrush.

SOUND

[0210] Figure 23 shows an example of an output from a toothbrush sound receiver, in accordance with or for use with the present invention.

[0211]The toothbrush detects changes in the continuous sound spectrum generated by an electric or sonic toothbrush. The sound profile (pitch, magnitude) of an electric or sonic (ie vibrating) toothbrush changes when the brush head is in contact with a surface.

[0212] The sound is measured through the sound recorder in the toothbrush and recorded. The processor then applies a combination of simple filters and efficient classification techniques (eg decision tree) to detect brushing contact based on changes in the sound profile. In this way, resource-hungry sound processing can be avoided.

[0213] Figure 23a shows a sound frequency spectrum recorded through a toothbrush sound sensor during “free vibrations”, that is, the toothbrush head is not in contact with the jaw. When in contact with the tooth surface, as shown in Figure 23b, the additional voltage on the electric generator/vibrator causes changes in the emitted sound. In this case, from 137Hz to 120Hz. This change in frequency can be efficiently picked up by the toothbrush's computing module.

[0214] Although the present invention has been described in conjunction with the exemplary embodiments described above, many equivalent modifications and variations will be apparent to those skilled in the art when this embodiment is provided. Accordingly, the exemplary embodiments of the present invention set forth above are considered illustrative and not limiting. Various changes can be made to the described embodiments without departing from the scope of the present invention.

[0215] All references referred to above are incorporated herein by reference.

Claims (11)

1. METHOD FOR MONITORING TOOTHBRUSHING, characterized in that it comprises: - a training phase in which: - a position sensor (42) detects position information of a toothbrush (1) during a first occurrence of free brushing through a user; - one or more additional sensors (42, 43) record toothbrush movement information (1) during the first occurrence of free brushing; - a user specific statistical model is generated which maps the positional information into the movement information; and - a monitoring phase in which: - one or more additional sensors (42, 43) record toothbrush movement information during a second free brushing occurrence; and - the toothbrush (1) compares the movement information received during the second free brushing occurrence with the user-specific statistical model to calculate the positional information. 2. METHOD, according to claim 1, characterized in that the training phase comprises the steps of: - providing a smart toothbrush (1), the smart toothbrush (1) comprising at least one position sensor (42) and at least one accelerometer; - provision of an external position sensor; - detecting the position information of a toothbrush (1) during a first instance of free brushing by the user using the relative position of the position sensor (42) on the smart toothbrush (1) and the external position sensor; - record of toothbrush movement information (1) during the first occurrence of free brushing using the accelerometer; and - generation of a user-specific statistical model that maps positional information to motion information. 3. METHOD, according to any one of claims 1 to 2, characterized in that the monitoring phase comprises the steps of: - providing a mobile device (20); - record of toothbrush movement information (1) during a second occurrence of free brushing using the accelerometer; and - comparison of the movement information received during the second free brushing occurrence with the user specific statistical model to provide the positional information; - display of positional information to the user on the mobile device (20). 4. METHOD, according to any one of claims 1 to 3, characterized in that the training phase includes an alternative training model, in which the user follows an instruction guide on a mobile device (20), in which the specific statistical model The user feedback generated through the alternative training model maps the positional information displayed on the mobile device (20) against movement information received, simultaneously, from one or more additional sensors (42, 43). 5. METHOD, according to any one of claims 1 to 4, characterized in that the position sensor (42) includes an external sensor mounted on a head (2). 6. METHOD, according to any one of claims 1 to 4, characterized in that the position sensor (42) includes an external sensor mountable on a wall. 7. METHOD, according to claim 6, characterized in that the position sensor (42) is located inside a wall mountable mirror. 8. METHOD, according to any one of claims 1 to 7, characterized in that the position sensor (42) is a magnetic field generator (1703) and a corresponding magnetic field sensor, wherein the magnetic field sensor is located at the toothbrush (1). 9. METHOD, according to claim 8, characterized in that the magnetic generator (1703) is usable by the user. 10. METHOD according to claim 9, characterized in that the magnetic generator (1703) is mounted on the wall. 11. SYSTEM FOR TRAINING A INTELLIGENT TOOTHBRUSH (1), the system characterized in that it comprises: - a position sensor (42) that detects the position information of a toothbrush (1) during a first instance of brushing free through a user; - one or more additional sensors (42, 43) located on the toothbrush (1) which record the movement information of the toothbrush (1) during the first occurrence of free brushing; and - a computer (30) comprising a memory and a processor, the processor programmed to generate a user-specific statistical model, mapping the positional information of the position sensor (42) in relation to the movement information of one or more additional sensors (42, 43) to create a lookup table stored in memory.

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