Oral care device

Abstract

An oral care device includes a head for caring for a user's oral cavity, the oral cavity including a plurality of oral regions, and an inertial measurement unit (IMU) operable to output signals that depend on the position and / or movement of the head. The oral care device includes a controller configured to receive from the IMU signals indicative of the position and / or movement of the head relative to the oral cavity, and to process the received signals using a trained non-linear classification algorithm to obtain classification data. The classification algorithm is trained to identify the oral region in which the head of the oral care device is located from the plurality of oral regions. The controller is configured to use the obtained classification data to control the oral care device to perform an action.

Description

Technical Field

[0001] This invention relates to an oral care device. Specifically, but not exclusively, this disclosure relates to measures for operating an oral care device, including methods, apparatus, and computer programs. Background Technology

[0002] Oral care devices are used to provide care to a user's mouth. Examples of such devices include toothbrushes (which can be manual or electric), oral irrigators, interdental cleaning devices, dental floss devices, etc.

[0003] In some known cases, oral care devices (also known as "oral hygiene devices" or "oral care appliances") may provide flossing functionality in addition to functions such as brushing. For example, a fluid delivery system may be incorporated into an electric toothbrush and may be used to deliver a jet of working fluid for interdental (or interproximal) cleaning. Such a fluid delivery system may include nozzles disposed on the head of the device for spraying working fluid into the interproximal spaces between teeth, for example, to remove food matter from the spaces; and a fluid reservoir for storing the working fluid on the device.

[0004] However, the flexibility and / or versatility of known oral care devices are limited. This, in turn, may limit the ability of known devices to deliver treatment in the best possible way. For example, known oral care devices often rely on the user's correct use of the device, and this may not always be the case.

[0005] For example, in cases where oral care equipment includes an onboard fluid reservoir with a fixed capacity, the efficient use of the working fluid can be a particular consideration. Using and / or wasting more working fluid necessitates more frequent replenishment of the fluid reservoir. In some cases, effective care cannot be achieved even with repeated attempts.

[0006] Therefore, it is desirable to provide an improved oral care device and / or an improved method for operating the oral care device. Summary of the Invention

[0007] According to one aspect of this disclosure, an oral care device is provided, comprising: a head for caring for a user's oral cavity, the oral cavity including a plurality of oral regions; an inertial measurement unit (IMU) operable to output signals depending on the position and / or motion of the head of the oral care device; and a controller configured to: receive signals from the IMU indicating the position and / or motion of the head of the oral care device relative to the user's oral cavity; process the received signals using a trained nonlinear classification algorithm to obtain classification data, wherein the classification algorithm is trained to identify the oral region in which the head of the oral care device is located from the plurality of oral regions, wherein the obtained classification data indicates the oral region in which the head of the oral care device is located; and control the oral care device to perform actions using the classification data.

[0008] In embodiments, multiple oral regions include more than two oral regions. Different oral regions may correspond to different areas of the oral cavity. For example, different oral regions may correspond to different rows, quadrants, or sextants of the oral cavity, and / or different teeth and / or tooth surfaces. In embodiments, multiple oral regions include more than four oral regions. In embodiments, multiple oral regions include 12 oral regions. The 12 oral regions may consist of 4 oral quadrants multiplied by 3 tooth surfaces. In embodiments, multiple oral regions include 18 oral regions. In some such embodiments, the 18 oral regions consist of 6 oral sextants multiplied by 3 tooth surfaces. That is, each oral region may indicate one of a given sextant and one of a given tooth surface. In alternative embodiments, a different number of oral regions may be used.

[0009] By using IMU signals as input to a trained nonlinear classification algorithm, the location of the head in the oral cavity can be identified without user input. Therefore, the oral care device can autonomously recognize how the user uses it and adjust accordingly. This allows for more intelligent control of the device. For example, one or more operational settings can be controlled based on the identified oral cavity area. Furthermore, this allows users to be notified of the head's position within the mouth, the time spent in each area, etc. This information can also be used to determine whether the oral cavity area where the head is located has been visited during the current oral care phase. In addition to providing direct user feedback, such information can facilitate the generation of behavioral profiles instructing the user on how they intend to use the device, based on factors such as the time spent in each oral cavity area and whether any areas were missed. Moreover, using a trained algorithm results in more accurate and / or more reliable head positioning compared to not using the trained algorithm. That is, the spatial resolution of head positioning is improved by using a trained algorithm. Furthermore, the nonlinear classification algorithm can be used to distinguish factors that cannot be linearly separable, which is the case when the user moves the device during use. Therefore, using a nonlinear classification algorithm to obtain classification data leads to more accurate and / or more reliable determination of the classification data.

[0010] As discussed, in the embodiments, a given oral region among multiple oral regions is indicated by: a quadrant or sextant of the user's oral cavity; and a surface selected from a list including the buccal, lingual, and occlusal surfaces. Therefore, there can be 18 distinct oral regions, corresponding to six oral sextants, each sextant having three associated surfaces. The ability to distinguish 18 (or more) distinct oral regions is achieved by using IMU signals and a trained nonlinear classification algorithm. This allows for increased spatial resolution of head localization compared to known methods.

[0011] In this embodiment, the classification algorithm includes a machine learning algorithm. Such a machine learning algorithm can be improved through experience and / or training (e.g., to improve the accuracy and / or reliability of the classification).

[0012] In one embodiment, the oral care device includes a machine learning agent that incorporates a classification algorithm. Thus, the classification algorithm can reside on the oral care device. Performing oral region identification on the device reduces latency compared to a scenario where the classification algorithm is not located on the device, as it eliminates the need to send and / or receive data from another device. This enables faster identification of oral regions, thereby reducing the time spent taking any corrective actions and / or providing output via a user interface.

[0013] In this embodiment, the controller is configured to control the oral care device to deliver care to the user's mouth based on classification data. For example, depending on which oral region the head is located in, the device can be controlled to deliver care to an identified interproximal space between adjacent teeth.

[0014] In embodiments, the oral care device includes a fluid delivery system for delivering a working fluid to a user's mouth. In some such embodiments, a controller is configured to output control signals to the fluid delivery system based on classification data to control the delivery of the working fluid. For example, the identified oral cavity area can be used to determine whether to trigger the jetting of the working fluid. This improves the efficiency and / or accuracy of the fluid delivery system, for example by taking into account the determined intraoral position of the device head during delivery (or non-delivery) of care. In embodiments, the control signals are operable to block the delivery of the working fluid based on classification data.

[0015] In one embodiment, the controller is configured to cause the user interface to provide output based on classification data. In another embodiment, the output provided by the user interface includes audio, visual, and / or tactile output. For example, such output may include a notification informing the user to spend more time in a specific oral region to improve the device's usability in delivering care.

[0016] In this embodiment, the controller is configured to enable the user interface to provide output during the use of the oral care device to care for a user's mouth. By providing output through the user interface during device use, rather than after the oral care process is complete, feedback can be provided more rapidly. For example, the user interface can provide output virtually in real time. This allows users to adjust their behavior during device use, such as taking corrective actions, thereby improving the effectiveness of care delivery.

[0017] In this embodiment, the controller is configured to provide output through the user interface after the user has finished using the oral care device. Providing output after device use allows for a more detailed level of feedback compared to providing output during use. For example, device use and / or movement can be analyzed throughout the oral care phase, and the user can then be provided with detailed feedback about the entire phase, such as by providing information like “Try spending more time in zone 12.” This feedback encourages the user to adjust their behavior in subsequent phases to improve device use.

[0018] In one embodiment, the user interface is included in a remote device, and the controller is configured to signal to the remote device to enable the user interface to provide output. Such a user interface on a remote device may be more versatile than the user interface on the oral care device itself.

[0019] In this embodiment, the oral care device includes a user interface. By providing a user interface on the oral care device, users can generate and receive output more quickly compared to situations where the oral care device does not have a user interface, because the need for communication between different devices is avoided. Furthermore, providing a user interface on the oral care device increases the likelihood that the user will receive feedback quickly. For example, while using the oral care device, the user may not be in the same location as the remote device, and therefore the user may not immediately see / hear notifications on the remote device.

[0020] In this embodiment, the controller is configured to enable the user interface to provide output, including a notification to the user that the head of the oral care device is positioned within a predetermined oral cavity area. Such a notification could, for example, be provided at the start of an oral care phase. By providing this notification to the user, the nonlinear classification algorithm learns the initial position of the head, such as the oral cavity area in which the head is located at the start of the phase. This increases the accuracy and / or reliability of the algorithm. That is, when the initial position is known, the confidence in subsequently identified intraoral positions increases compared to a situation where the initial position is unknown and must be estimated.

[0021] In this embodiment, the controller is configured to modify the classification algorithm using signals received from the IMU. That is, the classification algorithm can be trained, retrained, and / or further trained using signals generated by the IMU. Modifying the classification algorithm allows for improvements in accuracy and / or reliability through experience and / or the use of more training data. In other words, the confidence level in identifying oral cavity regions can be increased. Furthermore, modifying the classification algorithm allows it to be tailored to the user. For example, an initial classification algorithm may be provided on the oral care device, but this initial algorithm may not take into account the specific behavior of a given user. For instance, a user may move the device in a manner different from that of other users. By using the generated IMU signals as training data for dynamically retraining the classification algorithm, the algorithm can more reliably identify the oral cavity region where the device's head is located.

[0022] In one embodiment, the controller is configured to store categorized data in memory. This allows the data to be used at a later time, such as for post-processing analysis and / or for generating behavioral profiles of the user's device usage. In another embodiment, the controller is configured to output categorized data for transmission to a remote device.

[0023] In this embodiment, the controller is configured to receive training data from a remote device and modify the classification algorithm using the received training data. Using training data from a remote device to modify the classification algorithm can improve the accuracy and / or reliability of the classification algorithm compared to not using such training data.

[0024] In one embodiment, the oral care device includes a toothbrush.

[0025] According to one aspect of this disclosure, a method is provided for operating an oral care device for caring for a user's oral cavity, the oral care device comprising: a head for caring for a user's oral cavity, the oral cavity including a plurality of oral regions; an inertial measurement unit (IMU) operable to output signals depending on the position and / or motion of the head of the oral care device; and a controller. The method includes, at the controller: receiving from the IMU signals indicating the position and / or motion of the head of the oral care device relative to the user's oral cavity; processing the received signals using a trained nonlinear classification algorithm to obtain classification data, wherein the classification algorithm is trained to identify the oral region in which the head of the oral care device is located from the plurality of oral regions, wherein the obtained classification data indicates the oral region in which the head of the oral care device is located; and controlling the oral care device to perform actions using the classification data.

[0026] According to one aspect of this disclosure, a computer program including a set of instructions is provided, when executed by a computerized device, to cause the computerized device to perform a method of operating an oral care device for caring for a user's oral cavity, the oral care device including a head for caring for the user's oral cavity, the oral cavity including a plurality of oral cavity regions, and an inertial measurement unit (IMU) operable to output signals depending on the position and / or movement of the head of the oral care device, the method comprising: receiving from the IMU signals indicating the position and / or movement of the head of the oral care device relative to the user's oral cavity; processing the received signals using a trained nonlinear classification algorithm to obtain classification data, wherein the classification algorithm is trained to identify the oral cavity region in which the head of the oral care device is located from the plurality of oral cavity regions, wherein the obtained classification data indicates the oral cavity region in which the head of the oral care device is located; and controlling the oral care device to perform actions using the classification data.

[0027] It is understood, of course, that features described with respect to one aspect of the invention can be incorporated into other aspects of the invention. For example, the method of the invention can be combined with any features described with reference to the apparatus of the invention, and vice versa. Attached Figure Description

[0028] Embodiments of this disclosure will now be described by way of example only with reference to the accompanying drawings, in which:

[0029] Figure 1A and 1B This is a perspective view of the oral care device according to an embodiment;

[0030] Figure 1C This is a plan view of the oral care device according to an embodiment;

[0031] Figure 2 This is a schematic diagram of an oral care device according to an embodiment;

[0032] Figure 3 This is a flowchart illustrating a method of operating an oral care device according to an embodiment;

[0033] Figure 4 This is a flowchart illustrating a method of operating an oral care device according to an embodiment;

[0034] Figure 5 This is a flowchart illustrating a method of operating an oral care device according to an embodiment;

[0035] Figure 6 This is a flowchart illustrating a method of operating an oral care device according to an embodiment;

[0036] Figure 7 This is a flowchart illustrating a method of operating an oral care device according to an embodiment;

[0037] Figure 8 This is a flowchart illustrating a method of operating an oral care device according to an embodiment;

[0038] Figure 9 This is a flowchart illustrating a method of operating an oral care device according to an embodiment; and

[0039] Figure 10 This is a flowchart illustrating a method of operating an oral care device according to an embodiment. Detailed Implementation

[0040] Figure 1A and 1B A perspective view of an oral treatment device 100 according to an embodiment is shown. Figure 1C A plan view of an oral care device 100 is shown. The oral care device 100 and / or its components can be used to implement the methods described herein. Figure 1A-1C In the illustrated embodiment, the oral care device 100 includes a toothbrush. In another embodiment, the oral care device 100 includes an electric toothbrush. In yet another embodiment, the device 100 includes an ultrasonic toothbrush. In alternative embodiments, the oral care device 100 may include other types of devices. For example, the device 100 may include a dental flossing device, a mouth irrigator, an interproximal cleaning device, an oral health monitoring device, or any combination thereof. The oral health monitoring device is configured to monitor the user's oral health and provide feedback to the user accordingly.

[0041] The oral care device 100 includes a handle 110 and a head 120. The handle 110 forms the main body of the device 100 and can be held by the user during use of the device 100. Figure 1A-1CIn the illustrated embodiment, the handle 110 includes a user interface 112. The user interface 112 includes a user-operable button configured to be pressed by the user when the user holds the handle 110. In some embodiments, the handle 110 includes a display (not shown) that can be positioned to be visible to the user during use of the oral care device 100.

[0042] exist Figure 1A-1C In the illustrated embodiment, the head 120 includes a plurality of bristles 122 for performing brushing functions. In alternative embodiments, the head 120 does not include bristles. For example, in some other embodiments, the oral care device 100 includes dedicated fluid delivery devices, such as for cleaning the gaps between adjacent teeth, and / or for delivering cleaning or whitening media to the user's teeth. Figure 1A-1C In the illustrated embodiment, the oral care device 100 includes a rod 130 connecting a handle 110 to a head 120. The rod 130 is elongated in shape and serves to space the head 120 from the handle 110 to facilitate user operability of the oral care device 100. The head 120 and / or the rod 130 can be detached from the handle 110.

[0043] Oral care device 100 includes a dental care system for delivering oral care (treatment) to a user. Figure 1A-1C In the illustrated embodiment, the dental care system includes a fluid delivery system; it should be understood that other types of dental and / or oral care systems may be used in other embodiments. The fluid delivery system is arranged to deliver a jet of working fluid to the oral cavity. In this embodiment, the working fluid includes a liquid, such as water. In an alternative embodiment, the working fluid includes a gas and / or powder. The working fluid may be delivered to the interproximal space between adjacent teeth to remove obstructions located in the space, such as food matter, such as smoked ham or other cured meats. The interproximal space is a space or gap between two adjacent teeth, and / or may be the area surrounding the contact point of the adjacent teeth. The interproximal space may be defined as the area defined by a plane tangent to the lingual surfaces of two adjacent teeth and the area between the teeth.

[0044] Additionally or alternatively, the working fluid may be delivered to the user's gum line, for example, to treat inflammation or infection of the gums. In an alternative embodiment, the dental care system is configured to deliver whitening fluid and / or remove plaque from the user's teeth.

[0045] exist Figure 1A-1CIn the illustrated embodiment, the oral care device 100 includes a fluid reservoir 114 for storing working fluid. The fluid reservoir 114 is disposed in the handle 110 of the oral care device 100. The fluid reservoir 114 forms part of the fluid delivery system of the device 100. In this embodiment, the fluid reservoir 114 can be detached from the handle 110, for example, to facilitate replenishment of working fluid.

[0046] In one embodiment, the oral care device 100 also includes a nozzle 124. This is as follows: Figure 1C As shown. Nozzle 124 forms part of the fluid delivery system of device 100. Nozzle 124 is disposed on the head 120 of device 100. Nozzle 124 is configured to deliver working fluid to the user's mouth during use of oral care device 100. Figure 1A-1C In the illustrated embodiment, the bristles 122 are arranged at least partially around the nozzle 124. The nozzle 124 extends along the nozzle axis A, as shown... Figure 1C As shown. The nozzle axis A is substantially perpendicular to the longitudinal axis Z of the handle 110.

[0047] Nozzle 124 is arranged to receive working fluid from fluid reservoir 114 and deliver a jet of working fluid to the user's oral cavity during use of device 100. In an embodiment, the tip of nozzle 124 includes a fluid outlet through which the jet of working fluid is delivered to the oral cavity. Each jet of working fluid may have a volume of less than 1 ml, and in some cases less than 0.5 ml. Nozzle 124 may also include a fluid inlet for receiving working fluid from fluid reservoir 114.

[0048] In one embodiment, the fluid delivery system includes a pump assembly (not shown) for drawing working fluid from a fluid reservoir 114 to a nozzle 124. The pump assembly may be disposed within a handle 110. The pump assembly may include a pump (e.g., a positive displacement pump) and a driver for driving the pump. In one embodiment, the driver includes a pump motor. The pump motor may be powered by a battery (e.g., a rechargeable battery).

[0049] In one embodiment, the fluid delivery system includes control circuitry (not shown) for controlling the actuation of a pump motor, and thus the control circuitry and the pump motor provide a driver for driving the pump. The control circuitry may include a motor controller that supplies power to the pump motor. The control circuitry of the fluid delivery system may receive signals from a controller of the oral care device 100, as will be described in more detail below.

[0050] Figure 2 A schematic block diagram of an oral care device 100 according to an embodiment is shown.

[0051] The oral care device 100 includes a controller 210. The controller 210 is operable to perform various data processing and / or control functions according to embodiments, which will be described in more detail below. The controller 210 may include one or more components. These components may be implemented in hardware and / or software. The one or more components may be co-located within the oral care device 100 or may be located remotely from each other. The controller 210 may be implemented as one or more software functions and / or hardware modules. In an embodiment, the controller 210 includes one or more processors 210a configured to process instructions and / or data. Operations performed by the one or more processors 210a may be performed by hardware and / or software. The controller 210 may be used to implement the methods described herein. In an embodiment, the controller 210 is operable to output control signals for controlling one or more components of the oral care device 100.

[0052] In one embodiment, the oral care device 100 includes a fluid delivery system 220. The fluid delivery system 220 is operable to deliver a working fluid to the user's oral cavity, as referenced above. Figure 1A-1C In one embodiment, the fluid delivery system 200 includes a nozzle for spraying working fluid and a fluid reservoir for storing the working fluid in an oral care device, such as the nozzle 124 and fluid reservoir 114 described above. The fluid delivery system 220 is operable to receive a control signal from a controller 210, thereby allowing the controller 210 to control the delivery of the working fluid by the fluid delivery system 220. For example, the controller 210 may output a control signal received by the control circuitry of the fluid delivery system 220, which causes the control circuitry of the fluid delivery system 220 to actuate a pump motor, which in turn causes the working fluid to be pumped from the fluid reservoir to the nozzle, where it is sprayed into the user's mouth. Additionally or alternatively, the controller 210 may output a control signal received by the control circuitry of the fluid delivery system 220, which causes the control circuitry of the fluid delivery system 220 to prevent the working fluid from being delivered via the nozzle. In an alternative embodiment, the oral care device 100 does not include a fluid reservoir. In other words, the working fluid can be delivered from outside the oral care device 100 (e.g., via a dedicated fluid delivery channel) to be sprayed through a nozzle, rather than being stored in the oral care device 100.

[0053] In an embodiment, the oral care device 100 includes an image sensor device 230. The image sensor device 230 includes one or more image sensors. Examples of such image sensors include, but are not limited to, charge-coupled devices, CCDs, and active pixel sensors such as complementary metal-oxide-semiconductor (CMOS) sensors. In an embodiment, the image sensor device includes an intraoral image sensor device. For example, the image sensor device may include an intraoral camera. The intraoral image sensor device (e.g., an intraoral camera) is operable to be used at least partially within a user's oral cavity to generate image data representing the user's oral cavity. For example, the image sensor device 230 may be at least partially disposed on a head 120 of the oral care device 100, the head 120 being arranged for insertion into a user's oral cavity. In an embodiment, the image sensor device 230 includes one or more processors. A controller 210 is operable to receive image data from the image sensor device 230. The image data output from the sensor device 230 may be used to control the oral care device 100. In an embodiment, the controller 210 is operable to control the image sensor device 230.

[0054] exist Figure 2 In the illustrated embodiment, the oral care device 100 includes an inertial measurement unit (IMU) 240. In such an embodiment, a controller 210 is operable to receive signals from the IMU 240 indicative of the position and / or motion of the oral care device 100. In this embodiment, the IMU 240 includes an accelerometer, a gyroscope, and a magnetometer. Each of the accelerometer, gyroscope, and magnetometer has three axes, or degrees of freedom (x, y, z). Thus, the IMU 240 can include a 9-axis IMU. In an alternative embodiment, the IMU 240 includes an accelerometer and a gyroscope, but not a magnetometer. In such an embodiment, the IMU 240 includes a 6-axis IMU. Due to the increased degrees of freedom, a 9-axis IMU may produce more accurate measurements than a 6-axis IMU. However, in some cases, a 6-axis IMU may be superior to a 9-axis IMU. For example, some oral care devices may experience and / or encounter magnetic interference during use. Heating, magnetism, and / or magnetic induction and / or other magnetic interference on the device can affect the behavior of the magnetometer. Therefore, in some cases, a 6-axis IMU is more reliable and / or more accurate than a 9-axis IMU. IMU 240 is configured to output data indicating accelerometer and gyroscope signals (and in some embodiments, magnetometer signals). In one embodiment, IMU 240 is disposed in the head 120 of the oral care device 100. In an alternative embodiment, IMU 240 is disposed in the handle 110 of the oral care device 100. In one embodiment, the oral care device 100 includes a plurality of IMUs 140. For example, a first IMU 240 may be disposed in the head 120, and a second IMU 240 may be disposed in the handle 110.

[0055] In one embodiment, the oral care device 100 includes a contact member 245. The contact member 245 is operable to contact a user's teeth during use of the oral care device 100, as will be described in more detail below. The contact member 245 is disposed on the head 120 of the oral care device 100. For example, the contact member 245 may include a nozzle of a fluid delivery system 220, such as those referenced above. Figure 1A-1C The nozzle 124 is described.

[0056] In one embodiment, the oral care device 100 includes a user interface 250. The user interface 250 may be similar to the one referenced above. Figure 1A-1C User interface 112 is described. For example, user interface 250 may include audio and / or visual interfaces. In an embodiment, user interface 250 includes a display (e.g., a touchscreen display). In an embodiment, user interface 250 includes an audio output device, such as a speaker. In an embodiment, user interface 250 includes a haptic feedback generator configured to provide haptic feedback to a user. Controller 210 is operable to control user interface 250, for example, to cause user interface 250 to provide output to a user. In some embodiments, controller 210 is operable to receive data via user interface 250, for example, based on user input. For example, user interface 250 may include one or more buttons and / or touch sensors.

[0057] The oral care device 100 also includes a memory 260. According to an embodiment, the memory 260 is operable to store various types of data. The memory may include at least one volatile memory, at least one non-volatile memory, and / or at least one data storage unit. The volatile memory, non-volatile memory, and / or data storage unit may be configured to store computer-readable information and / or instructions used / executed by the controller 210.

[0058] In alternative embodiments, the oral care device 100 may include more, fewer, and / or different components. In particular, in some embodiments, Figure 1A-1C and / or Figure 2 At least some components of the oral care device 100 shown may be omitted (e.g., may be unnecessary). For example, in some embodiments, at least one of the fluid delivery system 220, image sensor device 230, IMU 240, user interface 250, and memory 260 may be omitted. In embodiments, the oral care device 100 includes additional components not shown, such as a power source, such as a battery.

[0059] Figure 3 A method 300 for operating an oral care device according to an embodiment is shown. Method 300 can be used to operate the device described above. Figure 1A , 1B and Figure 2 The oral care device 100 is described. Figure 3 In one embodiment, the oral care device 100 includes an IMU 240 and a contact member 245 operable to contact a user's teeth during use of the oral care device 100. In another embodiment, method 300 is performed at least in part by a controller 210.

[0060] In step 310, a signal indicative of the vibration characteristics of the oral care device 100 during use is received from the IMU 240. The vibration characteristics depend on the contact between the contact member 245 and the teeth. Therefore, the vibration characteristics can be different (or can have different values) depending on whether the contact member 245 is in contact with the teeth.

[0061] In step 320, the signal is processed to detect the interproximal space between adjacent teeth in the user's oral cavity.

[0062] In step 330, during the use of the oral care device, the oral care device is controlled to deliver care to the detected interproximal spaces.

[0063] Therefore, during user use of device 100, interproximal gaps can be automatically detected using contact member 245 and IMU 240, and care delivery can be controlled accordingly. Thus, the user does not need to determine when device 100 is in a suitable position for care delivery, e.g., adjacent or within the interproximal gap. Instead, this determination is made automatically by monitoring the vibration characteristics of device 100, which vary according to the contact between contact member 245 and the teeth. By automatically detecting interproximal gaps and / or the position of device 100 relative to the interproximal gaps during use, and using such information to control care delivery at that time (i.e., during the same period of use of device 100), care delivery becomes more accurate.

[0064] Vibration characteristics are the properties of the vibration of device 100 during use. For example, vibration characteristics may involve the frequency and / or amplitude of the vibration. When contact member 245 is in contact with a tooth, compared to when contact member 245 is not in contact with a tooth, such as when contact member 245 is in or at the interproximal space between adjacent teeth, the vibration of device 100 is damped more due to contact. By analyzing the IMU signal to determine how the vibration of device 100 is damped, it can be inferred whether contact member 245 is currently in or at the interproximal space.

[0065] In embodiments, for example, the head 120 of an oral care device 100 includes a plurality of bristles 122, with a contact member 245 separate from the bristles 122. Thus, both the bristles 122 and the individual contact member 245 can come into contact with the user's teeth during use of the device 100. The contact member 245 may include, for example, a member with higher rigidity than the bristles 122. By using the individual contact member 245, the characteristics of the contact member 245 can be selected and / or adjusted to optimize interproximal gap detection. For example, it may be desirable to use a contact member 245 with relatively high rigidity (e.g., rigidity above a predetermined threshold) so that a detectable change is produced in the measured vibration characteristics as the contact member 245 moves into or out of the interproximal gap. In some embodiments, the bristles themselves may not be rigid enough to produce such a detectable change, and increasing the rigidity of the bristles to achieve this effect may hinder the brushing function of the bristles.

[0066] In an embodiment, for example, an oral care device includes a fluid delivery system 220, which includes a nozzle through which working fluid can be delivered to the user's mouth. The contact component includes the nozzle, as shown in the reference above. Figure 1A-1C The nozzle 124 is described. Therefore, the nozzle can be used both as a device through which working fluid can be injected toward the adjacent gap and as a contact member for automatically detecting the adjacent gap (and thereby triggering injection).

[0067] In this embodiment, the IMU 240 is included in the handle 110 of the device 100. By placing the IMU 240 in the handle 110 of the device 100, rather than in the head 120 of the device 100, space on the device can be managed more efficiently. That is, the head 120 of the device 100 may be relatively small compared to the handle 110, and including the IMU in the head 120 may require undesirable architectural and / or structural changes to accommodate the IMU 240. Furthermore, in this embodiment, the head 120 of the device 100 may be detachable from the handle 110 and is disposable, and the user may wish to replace the head periodically after use. Therefore, placing the IMU 240 in the handle 110 instead of the head 120 reduces the cost of replacing parts.

[0068] In this embodiment, the IMU 240 is included in the head 120 of the device 100. Arranging the IMU 240 in the head 120 of the device 100 can produce a signal that is easier to detect (and therefore more accurate and / or reliable gap detection) compared to the case where the IMU 240 is arranged in the handle 110, because the IMU 240 is arranged closer to the contact member 245.

[0069] In embodiments, such as oral care device 100 including a fluid delivery system 220, a control signal is output to the fluid delivery system 220 to control the delivery of working fluid in response to the detection of an inter-adjacent gap. Thus, the delivery of working fluid is controlled during use of device 100 in response to the automatic detection of the inter-adjacent gap using contact member 245 and IMU 240 (during the same period of use of device 100). This allows for more accurate and / or reliable use of the fluid delivery system 220. By improving the accuracy and / or reliability of the fluid delivery system 220, the use of working fluid is reduced, and more efficient processing is achieved more quickly. In one embodiment, a control signal is output to the fluid delivery system 220 to cause the fluid delivery system to deliver working fluid to the inter-adjacent gap. Therefore, the ejection of working fluid can be directly triggered in response to inter-adjacent gap detection performed using IMU 240 and contact member 245. This improves the accuracy of fluid ejection; for example, the likelihood that working fluid is actually ejected into the inter-adjacent gap relative to other locations is increased.

[0070] In this embodiment, the vibration characteristics indicate ultrasonic vibrations generated by the oral care device 100. These ultrasonic vibrations may be generated as part of the brushing and / or plaque removal functions of the device 100. In other examples, the vibration characteristics indicate acoustic vibrations generated by the device 100, such as acoustic vibrations generated by a motor configured to drive movement of the head 120 of the device 100 relative to the handle 110 of the device 100. Therefore, automated interproximal gap detection is provided using the existing functionality of the device 100, and a separate vibration generating device is not required.

[0071] In one embodiment, the received signal is processed to detect changes in the vibration characteristics of the oral care device 100. Based on the detected changes, it is determined that the contact member 245 has moved into or out of the adjacent gap. Based on this determination, the control device 100 performs an action.

[0072] In an embodiment, the received signal includes accelerometer data. In an embodiment, the vibration characteristics include one or more of the following: the vibration amplitude and frequency of the oral care device. In an embodiment, one or more frequency filters are used to process the received signal to obtain a filtered signal. In an embodiment, one or more frequency filters include low-pass frequency filters. Such low-pass frequency filters can be used to reduce noise from the received IMU signal. For example, such noise can be due to device vibration, defects in IMU manufacturing (e.g., variations between different IMUs), etc. For example, by improving the signal-to-noise ratio, using one or more frequency filters to reduce noise increases the reliability and / or accuracy of gap detection. In an embodiment, a moving average is applied to the received IMU signal so that signals corresponding to repetitive and / or regular rapid movements (e.g., corresponding to the device's "scrubbing motion") can be removed, thereby enabling adjacent gap detection to be performed even when the device moves rapidly back and forth. In an embodiment, one or more amplitude thresholds are applied to the filtered signal to detect adjacent gaps. Such filters and / or thresholds are selected to increase the reliability and / or accuracy of gap detection, for example, by improving the signal-to-noise ratio compared to the "raw" signal received from IMU 240. The filter and / or threshold may be predetermined, and / or may be modified or calculated during the use of the device 100 in order to improve the accuracy of gap detection.

[0073] Figure 4 A method 400 for operating an oral care device according to an embodiment is shown. Method 400 can be used to operate the device described above. Figure 1A , 1B and Figure 2 The oral care device 100 is described. Figure 4 In some embodiments, the oral care device 100 includes an image sensor device 230. In these embodiments, the image sensor device 230 includes an intraoral image sensor device. In some embodiments, the method 400 is performed at least in part by the controller 210.

[0074] In step 410, the intraoral image sensor device 230 generates image data representing at least a portion of the user's oral cavity during the user's use of the oral care device 100.

[0075] In this embodiment, the intraoral image sensor device 230 is at least partially included in the head 120 of the oral care device 100. Since the head 120 of the device 100 is used to deliver care procedures within the user's mouth, arranging the intraoral image sensor device 230 at least partially within the head 120 allows for imaging of the oral cavity without requiring a separately mounted intraoral camera (i.e., a camera mounted separately from the head 120).

[0076] In this embodiment, the intraoral image sensor device 230 is at least partially included in the handle 110 of the oral care device 100. Therefore, even though a portion of the image sensor device 230 (e.g., the image sensor) is arranged to remain outside the user's mouth, the image sensor device 230 can still be referred to as an "intraoral image sensor device." By arranging the image sensor device 230 at least partially in the handle 110 of the device 100, space on the device can be managed more efficiently. That is, the head 120 of the device 100 can be relatively small compared to the handle 110, and including the image sensor device 230 in the head 120 may require architectural and / or structural changes to the head 120, which can be relatively complex and / or expensive. Furthermore, in this embodiment, the head 120 of the device 100 can be detachable from the handle and is disposable, and the user may wish to replace the head 120 periodically after use. Arranging the image sensor device 230 at least partially in the handle 110, rather than entirely in the head 120, reduces the cost of replacement parts.

[0077] In one embodiment, the intraoral image sensor device 230 includes a sensor and an aperture for receiving and transmitting light to the sensor. This aperture is included in the head 120 of the oral care device 100. For example, if the head 120 of the device 100 includes a set of bristles 122, the aperture may be arranged behind the bristles 122, such that the bristles 122 do not obstruct the aperture (i.e., block light from the aperture), for example, to perform a brushing function. In another embodiment, the image sensor device 230 includes a guide channel for guiding light from the aperture to the image sensor. For example, if the oral care device 100 includes a head 120, a handle 110, and a rod 130 connecting the head 120 and the handle 110, the guide channel may extend from the aperture along the rod 130 (e.g., within the rod 130) to the sensor. For example, the guide channel may include an optical fiber cable. In an alternative embodiment, the rod 130 is hollow and arranged to cover the image sensor, which is located behind the head 120 of the device 100. This reduces the distance between the hole and the sensor, while ensuring that the sensor is not included in the (disposable) head 120.

[0078] In this embodiment, the image data includes red, green, and blue RGB image data. Other types of image data (e.g., black and white image data) may be used in alternative embodiments.

[0079] In step 420, the generated image data is processed to determine location data indicating the location of interdental spaces between adjacent teeth in the user's mouth. A trained classification algorithm, configured to identify interdental spaces, is used to process the generated image data. The trained classification algorithm is trained prior to the use of the oral care device.

[0080] In step 430, during the use of the oral care device 100, the oral care device 100 is controlled to deliver care to the detected interproximal spaces.

[0081] Therefore, during user use of device 100, interoral gaps can be automatically detected using intraoral image sensor device 230 and a trained classification algorithm, and care delivery can be controlled accordingly without user input. For example, the user does not need to determine when device 100 is in a suitable position for care delivery, such as near or within an interoral gap. Instead, this determination is made automatically based on intraoral image data and can be performed substantially in real time. Using a trained classification algorithm to process intraoral image data increases the accuracy and / or reliability of interoral gap detection and / or location compared to not using such a trained algorithm to process intraoral image data. By more accurately detecting interoral gaps and / or the position of device 100 relative to interoral gaps during use, and using such information to control care delivery at that time (i.e., during the same period of device use), care delivery becomes more accurate. Furthermore, the use of image data allows not only gap detection but also gap location. Gap location allows for more accurate and / or reliable care delivery compared to a gap that is not located.

[0082] In embodiments of the oral care device 100 that include a fluid delivery system 220 for delivering working fluid to a user's oral cavity, control signals are output to the fluid delivery system 220 to control the delivery of working fluid based on location data. Therefore, in response to automatic localization of interproximal spaces using an intraoral camera 250 and a trained classification algorithm (during the same period of use of the device 100), the delivery of working fluid during use of the device 100 is controlled. This allows for more accurate and / or reliable use of the fluid delivery system 220. In particular, this increases the accuracy of fluid jetting, i.e., the likelihood that the working fluid is actually jetted into the interproximal spaces relative to other areas is increased. By improving the accuracy and / or reliability of the fluid delivery system 220, the use of working fluid is reduced, and faster care is achieved.

[0083] In this embodiment, a sliding window is used to process the generated image data. In such an embodiment, positional data is determined by detecting the presence of gaps between adjacent elements within the sliding window. In other words, the sliding window traverses the image, defines sub-regions of the image, and determines whether gaps exist within each sub-region. This will be described in more detail below.

[0084] In this embodiment, the generated image data is processed by extracting one or more image features from the image data and using the extracted one or more image features to determine location data. For example, image features may include texture-based image features. Since an image is composed of pixels that are highly correlated with each other, image feature extraction is used to obtain the most representative and informative (i.e., non-redundant) information about the image in order to reduce dimensionality and / or facilitate the learning of classification algorithms.

[0085] In this embodiment, discrete wavelet transform is used to extract one or more image features. Discrete wavelet transform can simultaneously capture frequency and location information in an image. Image frequencies in gap regions are typically higher than those in tooth or gum regions. This allows discrete wavelet transform to generate a frequency map of the image that can be used to detect inter-gap gaps. In this embodiment, the Haar wavelet is used, which has relatively low computational complexity and low memory usage compared to other wavelets. The coefficients of the wavelet transform (or approximations thereof) can be used as the extracted image features. For example, the output of feature extraction based on a Haar wavelet applied to an image of size a×a may include a horizontal wave h (a / 4×a / 4), a vertical wave v (a / 4×a / 4), and a diagonal wave d (a / 4×a / 4). Other wavelets may be used in alternative embodiments.

[0086] The extracted features can be applied to a sliding window of the image. For example, in a subregion of the image defined by the sliding window, a 2×2 pooling can be performed on each of h, v, and d before h, v, and d are vectorized and combined into a vector of size 1×10⁸. This can be normalized together with the training data (e.g., trained mean and variance values) from a trained classification algorithm. A Support Vector Machine (SVM) can be used as a nonprobabilistic, nonlinear binary classifier with a Gaussian radial basis function kernel, receiving normalized data from the previous step. A trained SVM consists of support vectors with trained coefficients and biases, determined during previous training phases. For example, given a set of images and ground truth labels, a classification algorithm can be trained to assign new examples to one class (e.g., gaps) or another class (e.g., non-gap).

[0087] In this embodiment, at least one of an edge detector, a corner detector, and a blob extractor is used to extract one or more image features. Compared to other methods, using this method to extract image features can provide more accurate detection and / or localization of neighbor gaps.

[0088] In embodiments, for example, the oral care device 100 includes a user interface that provides location-dependent output. For example, the output may include notifications to the user that an inter-interval has been located, indications of the location of the inter-interval, notifications to the user that a care delivery has been performed on the inter-interval, and / or notifications instructing the user to adjust the position and / or orientation of the device to allow for more precise care delivery (e.g., jetting of working fluid). The provided output may include, for example, visual, audio, and / or tactile output.

[0089] In embodiments, such as when the oral care device 100 includes a memory 260, one or more features of adjacent gaps are stored in the memory 260 for subsequent processing and / or control of the oral care device 100. For example, one or more stored features may be used to compare adjacent gaps with subsequently identified adjacent gaps. In other cases, one or more stored features are used to track adjacent gaps over time.

[0090] Figure 5 A method 500 for operating an oral care device according to an embodiment is shown. Method 500 can be used to operate the device described above. Figure 1A , 1B and Figure 2 The oral care device 100 is described. Figure 5 In one embodiment, the oral care device 100 includes an image sensor device 240. In another embodiment, the method 500 is performed at least in part by the controller 210.

[0091] In step 510, image data is generated by image sensor device 240. The image data indicates a sequence of images representing at least a portion of the user's oral cavity. Therefore, images of portions of the oral cavity can be captured at multiple different times.

[0092] In step 520, the image data is processed to determine motion parameters. These motion parameters indicate the movement of the oral care device 100 relative to the interproximal spaces between adjacent teeth in the user's mouth.

[0093] In step 530, the oral care device 100 is controlled to perform actions based on the determined motion parameters.

[0094] By determining motion parameters that indicate the movement of the oral care device relative to the inter-interval spaces, more precise and / or intelligent control of the device 100 is achieved. In particular, by taking into account the movement of the device 100 relative to the inter-interval spaces (or vice versa), care can be delivered to the inter-intervals more accurately and / or effectively.

[0095] In one embodiment, the oral care device is controlled to deliver care to the inter-internal space based on determined motion parameters. Therefore, the action performed in step 530 may include delivering care to the inter-internal space.

[0096] In one embodiment, the delivery of care from the oral care device 100 is prevented based on determined motion parameters. Therefore, the action performed in step 530 may include preventing care delivery to adjacent spaces.

[0097] In this embodiment, the determined motion parameters indicate the predicted position of the adjacent gap relative to the oral care device 100 at a predetermined future time. The predetermined future time can be the earliest time when care delivery can be initiated. By predicting the position of the gap at this predetermined future time, the probability of successfully (e.g., accurately) delivering care to the gap can be determined. If this probability is determined to be high, for example above a predetermined threshold, care delivery can be allowed. However, if this probability is determined to be low, for example below a predetermined threshold, care delivery can be prevented. This allows for more efficient use of the device 100, as care delivery is triggered only when the probability of the gap being accurately and / or effectively addressed is sufficiently high based on the motion parameters.

[0098] In an embodiment, the determined motion parameters indicate a predicted future time at which the interproximal gap will have a predetermined position relative to the oral care device 100. For example, the predetermined position could be a location within the jet path of the working fluid from the fluid delivery system. Therefore, the delivery of care can be controlled (e.g., delayed) based on the determined motion parameters to increase the likelihood of successful and accurate care of the interproximal gap. This enables more efficient use of the oral care device 100.

[0099] In this embodiment, the determined motion parameters indicate the velocity and / or acceleration of the oral care device 100 relative to the inter-particle gap. The determined velocity and / or acceleration can be used to track the trajectory of the gap relative to the device 100, thereby improving the accuracy of care delivery.

[0100] In embodiments of the oral care device 100 that include a fluid delivery system 220 for delivering working fluid to a user's mouth, control signals are output to the fluid delivery system 220 to control the delivery of the working fluid based on determined motion parameters. Therefore, actions performed in item 530 may include control of the fluid delivery system 220. Thus, the delivery of the working fluid is controlled during device use based on determined motion of the device (during the same period of device use) relative to the gap. This allows for more accurate and / or reliable use of the fluid delivery system. In particular, this increases the accuracy of fluid jetting, i.e., the likelihood that the working fluid is actually jetted into adjacent gaps relative to other locations is increased. For example, a given delay may exist between the time when an adjacent gap is detected and the time when the working fluid can be delivered to the gap. This delay may be due to data processing, signaling between different components and / or devices, operation of the fluid delivery system 220, etc. The delay means that by the time the working fluid is jetted from the fluid delivery system, the detected gap may no longer be in the path of the jetting fluid. However, by taking into account the motion of the device 100 relative to the gap, this motion can be corrected, thereby improving the accuracy of fluid jetting. For example, the injection can be delayed until the gap is in the path of the working fluid. By improving the accuracy and / or reliability of the fluid delivery system 220, the use of working fluid is reduced, and more efficient processing is achieved faster.

[0101] In one embodiment, the image sensor device 230 is at least partially included in the head 120 of the oral care device 100. Since the head 120 of the device 100 is used to deliver care into the user's mouth, arranging the image sensor device 230 at least partially in the head 120 allows imaging of the inside of the oral cavity without the need for a separately mounted camera (i.e., a camera mounted separately from the head 120).

[0102] In this embodiment, the image sensor device 230 is at least partially included in the handle 110 of the oral care device 100. As described above, by arranging the image sensor device 230 at least partially in the handle 110 of the device 100, space on the device can be managed more efficiently, and the cost of replacement parts (i.e., the head 120) can be reduced.

[0103] In one embodiment, the image sensor device 230 includes an intraoral camera. The intraoral camera can be used to capture digital images from inside a user's mouth. These images are then processed to track movement of the device relative to adjacent spaces, or vice versa. Thus, the inside of the user's mouth is imaged during use of the device 100. In some cases, the intraoral camera can be operated to generate video data.

[0104] In this embodiment, image data is processed to detect adjacent gaps. Therefore, image data is first processed to detect gaps, and then the trajectory of the gaps relative to device 100 is dynamically tracked. For example, gaps can be detected in the first image of an image sequence, and subsequent images in the image sequence can be used to track the movement of the gaps, for example, as indicated by motion parameters.

[0105] In this embodiment, inter-frame gaps are tracked by comparing the movement and / or displacement of image pixels between frames. For example, a pixel I(x, y, t) in the first frame of a sequence is compared with a pixel I(x+dx, y+dy, t+dt) in the second frame of a sequence to determine the movement between frames, i.e., the pixel moves (dx, dy) over time dt. The location of the gap can be predicted based on the displacement calculated from the first and second frames (i.e., the current frame and previous consecutive frames). Since teeth are rigid objects, the displacement of pixels in the gap region between two frames is similar to that of pixels in the tooth region. Therefore, gaps can be tracked even if the gap itself does not exist in one or more images. Optical flow methods are used to estimate the velocity of the gap relative to device 100 (in pixels per second), and the location of the gap at a predetermined future time can be predicted based on the velocity and the known time between frames.

[0106] In one embodiment, the adjacent gap is not present in at least one of the image sequences. In such an embodiment, the position of the adjacent gap in the at least one other image in the image sequence is estimated based on the position of the adjacent gap in at least one other image in the image sequence. Therefore, the trajectory of the gap can be traced even if the gap is not present in the image (i.e., visible). For example, in some images, the gap may be blurred by other objects. In one embodiment, an optical flow method is used to determine the velocity of pixels and / or objects between images in the sequence. The position of the gap in the first image, where the gap itself is not present, can then be estimated based on the calculated velocity, the position of the gap in the second image, and the time between the first and second images.

[0107] In this embodiment, motion parameters are determined based on signals output by the IMU. For example, if the oral care device 100 includes an IMU 240, the IMU 240 may be configured to output signals indicating the position and / or motion of the oral care device 100 relative to the user's mouth. For example, the IMU 240 may be used to determine the angular motion of the device 100 relative to a gap. Such signals may be used in conjunction with image data when determining motion parameters.

[0108] Figure 6 A method 600 for operating an oral care device according to an embodiment is shown. Method 600 can be used to operate the device described above. Figure 1A , 1B and Figure 2 The oral care device 100 is described. Figure 6 In one embodiment, the oral care device 100 includes an image sensor device 230. The image sensor device 230 is operable to generate image data representing at least a portion of a user's oral cavity. In another embodiment, method 600 is performed at least in part by a controller 210.

[0109] In step 610, the generated image data is processed to identify interproximal spaces between adjacent teeth in the user's oral cavity.

[0110] In step 620, at least one feature of the identified interproximal gap is compared with at least one feature of one or more previously identified interproximal gaps in the user's oral cavity. In embodiments, at least one feature of the identified gap includes features predicted to vary between different gaps, and / or features specific to the identified gap. Therefore, the at least one feature can be used to distinguish gaps. The at least one feature may include visual features. In embodiments, at least one feature of the identified interproximal gap indicates at least one of the following: the shape of the identified interproximal gap, the appearance of the identified interproximal gap, the location of the identified interproximal gap, or any salient feature of the identified interproximal gap. In embodiments, at least one feature of the identified gap indicates frequency features, such as wavelet transforms based on images applied to the identified gap.

[0111] In step 630, based on the comparison results, the oral care device 100 is controlled to perform actions.

[0112] The device 100 can be controlled in a smarter and / or more flexible manner by comparing the characteristics of the identified interproximal gaps with those of one or more previously identified interproximal gaps by the user. Specifically, it can be determined whether the identified gaps were previously identified during the current oral care phase (i.e., during the user's use of the device 100). Such determination can be performed substantially in real time, allowing for rapid and responsive control of the device 100. Thus, previously identified gaps can be re-identified even if imaging conditions have changed since the previous identification.

[0113] In this embodiment, newly identified gaps are handled differently than previously identified gaps. That is, if the identified gap is determined to be newly identified, the device 100 can be controlled in a first manner, and if the identified gap is determined to be (or similar to) a previously identified gap, the device 100 can be controlled in a different second manner. Depending on how the user operates the device 100, a given gap may be encountered once or multiple times during the oral care phase. By handling newly identified gaps in a different manner than previously identified gaps, the device 100 is thus able to adapt to the user's behavior.

[0114] In an embodiment, a similarity metric is calculated based on the results of a comparison. The similarity metric indicates the level of similarity between the identified adjacent gap and one or more previously identified adjacent gaps. In such an embodiment, the oral care device 100 is controlled based on the determined similarity metric. The similarity metric can indicate whether the identified gap is the same as or different from one or more previously identified gaps. That is, the similarity metric can indicate whether the identified gap is a newly identified gap or a previously identified gap. If it is determined that the gap has not been encountered before during the current oral care phase, the gap can be considered "newly identified." That is, the gap may have been identified in a previous oral care phase, but if it has not been encountered before in the current phase, it can still be designated as a newly identified gap. In an embodiment, the similarity metric is compared to a threshold. If the similarity metric is below the threshold, the gap is designated as a newly identified gap. If the similarity metric is above the threshold, the gap is designated as a previously identified gap.

[0115] In an embodiment, in response to a similarity metric indicating that the identified adjacent gap differs from one or more previously identified adjacent gaps, device 100 is controlled to deliver care to the identified adjacent gap. Therefore, actions performed in item 630 may include delivering care to the identified gap. Thus, if the identified gap is determined to be a newly identified gap, care delivery is triggered.

[0116] In an embodiment, in response to a similarity metric indicating that the identified adjacent gap differs from one or more previously identified adjacent gaps, image data representing the identified adjacent gap is stored in memory, for example, for subsequent identification and / or comparison of adjacent gaps. Thus, the gap can be compared with subsequently identified gaps to determine whether the subsequently identified gap was previously encountered. In an embodiment, the image data is stored in a library or database that includes image data and / or other representative data corresponding to previously identified user gaps. The image data may be stored on device 100 or may be output for transmission to a remote device for storage, such as via a network.

[0117] In one embodiment, in response to a similarity metric indicating that the identified adjacent gap is identical to at least one of one or more previously identified adjacent gaps, the oral care device 100 is controlled to prevent care delivery to the identified adjacent gap. Thus, the action performed in item 630 can include preventing care delivery. Therefore, repeated care of the same gap during a single oral care session can be reduced, and in some cases avoided entirely. In other words, each gap is cared for only once during a single oral care session. This allows for more efficient use of the oral care device 100. In examples where the process includes delivering working fluid via the fluid delivery system 220, for example, reducing repeated care of the same gap reduces the amount of working fluid used. In an alternative embodiment, in response to a similarity metric indicating that the identified gap is identical to at least one of previously identified gaps, care delivery is not prevented.

[0118] In one embodiment, in response to a similarity metric indicating that the identified adjacent gap is identical to at least one of one or more previously identified adjacent gaps, a time elapsed since the previous identification of at least one of one or more previously identified adjacent gaps is determined. The determined elapsed time is compared to a predetermined threshold. In such an embodiment, the oral care device 100 is controlled based on the comparison result of the determined elapsed time and the predetermined threshold. Therefore, the control of the device 100 can vary depending on how recently the gap was previously identified.

[0119] In one embodiment, in response to a determined elapsed time exceeding a predetermined threshold, the oral care device 100 is controlled to deliver care to the identified adjacent gap. Therefore, if a predetermined amount of time has elapsed since the previous care of the gap, repeated care of the gap can be performed. In another embodiment, in response to a determined elapsed time less than a predetermined threshold, the oral care device 100 is controlled to prevent care from being delivered to the identified adjacent gap. Therefore, if a predetermined amount of time has not elapsed since the previous care of the gap, repeated care of the gap is not performed. For example, if a user moves the device 100 back and forth during a "scrubbing" motion, two gaps may be encountered relatively quickly in succession. In this case, multiple caresses of the gap may be ineffective and / or inefficient. However, if the user returns the device 100 to a previously cared-for gap relatively late in the phase, it can be inferred that further care for that gap is desired, for example, if the previous care of the gap was unsuccessful.

[0120] In this embodiment, a trained classification algorithm is used to process the generated image data; this algorithm is configured to detect neighbor gaps. Using such a trained algorithm results in more accurate and / or more reliable gap detection compared to not using it. In this embodiment, the classification algorithm includes a machine learning algorithm. This machine learning algorithm can be improved through experience and / or training (e.g., to improve the accuracy and / or reliability of classification).

[0121] In one embodiment, the generated image data is processed to determine at least one feature of the identified neighbor gaps. In another embodiment, the generated image data is processed using a machine learning algorithm to determine at least one feature. The machine learning algorithm is trained to identify information used to distinguish neighbor gaps. This information includes features representing the gaps, i.e., non-redundant features, and / or features predicted to vary between gaps. The identified information may include at least one feature of the gap. In another embodiment, such a machine learning algorithm (or one or more different machine learning algorithms) is also used to determine at least one feature of one or more previously identified gaps, e.g., features representing previously identified gaps and / or features that can be used to distinguish gaps, and to compare previously identified gaps with currently identified gaps. In an alternative embodiment, gap features are not extracted from the raw image data using a machine learning algorithm.

[0122] In one embodiment, the image sensor device 230 includes an intraoral camera. In another embodiment, the image sensor device 230 is at least partially included in the head 120 of the oral care device 100. Since the head 120 of the device 110 is used to deliver care into the user's mouth, arranging the image sensor device 230 at least partially in the head 120 allows for imaging of the oral cavity without requiring a separately mounted camera.

[0123] In this embodiment, the image sensor device 230 is at least partially included in the handle 110 of the oral care device 100. As described above, by arranging the image sensor device 230 at least partially in the handle 110 of the device 100, space on the device can be managed more efficiently, and the cost of replacement parts (i.e., the head 120) can be reduced.

[0124] In embodiments where the oral care device includes a fluid delivery system 220 for delivering working fluid to a user's mouth, a control signal is output to the fluid delivery system 220 to control the delivery of the working fluid based on a determined comparison result. Therefore, actions performed at item 630 may include controlling the delivery of the working fluid (e.g., initiating and / or preventing the delivery of the working fluid). In embodiments, the fluid delivery system 220 includes a fluid reservoir for storing the working fluid in the oral care device 100. Therefore, by comparing the identified gap with previously identified gaps, the frequency of needing to replenish the fluid reservoir can be reduced, which decreases the repeated spraying of fluid into the same gap.

[0125] Figure 7 A method 700 for operating an oral care device according to an embodiment is shown. Method 700 can be used to operate the device described above. Figure 1A , 1B and Figure 2 The oral care device 100 is described. Figure 7 In some embodiments, the oral care device 100 includes an IMU 240. The IMU 240 is operable to output signals dependent on the position and / or movement of the oral care device 100. In these embodiments, the oral care device 100 also includes a fluid delivery system 220 for delivering working fluid to the user's oral cavity. In some embodiments, method 700 is performed at least in part by a controller 210.

[0126] In step 710, signals received from IMU 240 indicating the position and / or movement of the oral care device 100 relative to the user's mouth are processed.

[0127] In step 720, based on the processing in step 710, a control signal is output to the fluid delivery system 220 to control the delivery of the working fluid.

[0128] Therefore, the fluid delivery system 220 is controlled to deliver the working fluid based on IMU signals. Compared to controlling the fluid delivery system 220 without using IMU signals, this allows for increased accuracy in fluid delivery, such as the accuracy of the working fluid injection.

[0129] In one embodiment, the control signal is operable to prevent the fluid delivery system 220 from delivering working fluid. By selectively preventing the delivery of working fluid based on IMU signals, less working fluid is used compared to non-selectively preventing delivery. Therefore, the efficiency of the device 100 is improved.

[0130] In one embodiment, signals received from the IMU are processed to determine if the oral care device is moving according to a predetermined type of movement. In response to this determination, a control signal is output to the fluid delivery system 220 to prevent the delivery of working fluid. Thus, based on how the user moves the device 100, delivery of working fluid to the user's mouth is selectively prevented. This allows for more efficient use of the device 100 and / or more efficient handling, for example, preventing working fluid jetting when the device 100 is moving in a specific manner. For example, if the device 100 is moving according to a predetermined type of movement, the likelihood of the fluid delivery system 220 misfiring and / or being damaged by fluid jetting may increase. In another embodiment, a trained classification algorithm (e.g., a machine learning algorithm) is used to process signals received from the IMU 240, the classification algorithm being configured to determine whether the device 100 is moving according to a predetermined type of movement.

[0131] In this embodiment, the oral care device 100's movement according to a predetermined type of movement hinders its use in the user's mouth. Therefore, when the device 100 is used in a manner that hinders its use in the oral cavity, fluid delivery can be selectively prevented. If the device moves in this manner, the likelihood of successful care decreases, for example, due to reduced accuracy in the fluid delivery system 220 delivering the working fluid to the target. This means that the working fluid may be wasted, for example, by being sprayed by the fluid delivery system 220 without resulting in successful care. By selectively preventing fluid delivery when the device 100 moves according to a predetermined type of movement, the working fluid is used more efficiently.

[0132] In one embodiment, the predetermined motion type includes a scrubbing motion. If the device 100 is moving according to a scrubbing motion type, the accuracy with which the fluid delivery system 220 delivers the working fluid to the target (e.g., the gap between adjacent parts) decreases, and the likelihood of spray failure increases. This means that the working fluid is more likely to be wasted. Therefore, when the device 100 moves in a scrubbing motion, the working fluid is used more efficiently by selectively preventing fluid delivery. In an alternative embodiment, the predetermined motion type includes other motion types.

[0133] In this embodiment, signals received from IMU 240 are processed to determine the orientation of oral care device 100. Based on the determined orientation, control signals are output to fluid delivery system 220. Therefore, fluid delivery system 220 can be controlled based on the current orientation of device 100 as determined using the IMU signals. The likelihood of successful care provided by fluid delivery system 220 may depend on the orientation of device 100. For example, in the case of spraying working fluid into the interproximal space between adjacent teeth to remove obstructions, if device 100 is oriented such that the nozzle of fluid delivery system 220 extends substantially perpendicular to and faces the buccal or lingual surface of the teeth, success may be more likely (with fewer attempts). On the other hand, if device 100 is oriented such that the nozzle extends substantially perpendicular to and faces the occlusal surface of the teeth, the likelihood of successfully removing the obstruction is reduced. This means that working fluid is more likely to be wasted, for example, due to being sprayed from fluid delivery system 220 without resulting in successful care. By controlling fluid delivery based on the determined orientation of device 100, working fluid is used more efficiently.

[0134] In this embodiment, the orientation of device 100 is compared to a jet angle threshold. The jet angle threshold is a threshold used to determine whether the delivery of working fluid should be prevented or permitted based on the orientation of the head 120 of device 100. For example, fluid delivery may be permitted when the orientation of the head 120 is above the jet angle threshold, and fluid delivery may be prevented when the orientation of the head 120 is below the jet angle threshold. In this embodiment, the jet angle threshold may be determined for the user based on IMU signals. As the user moves device 100 along a row of teeth, i.e., since different users can orient and / or move device 100 differently along the channel, the jet angle threshold can be optimized for a specific user by analyzing the orientation of the head 120. As used herein, "channel" refers to the movement trajectory of the head 120 of device 100 along a row of teeth.

[0135] In an embodiment, signals received from IMU 240 are processed to determine changes in the orientation of oral care device 100 during use. Based on the determined changes in the orientation of oral care device 100, control signals are output to fluid delivery system 220. Therefore, fluid delivery can be controlled in response to changes in the orientation of device 100 during use. For example, device 100 can move from a first orientation with a relatively low probability of successful care to a second orientation with a relatively high probability of successful care, in which, for example, the nozzle is oriented substantially perpendicular to and facing the occlusal surface of the teeth, and in the second orientation, for example, the nozzle is oriented substantially perpendicular to and facing the lingual or buccal surface of the teeth. When device 100 is in the first orientation, fluid delivery can be blocked to reduce the use of working fluid by spraying working fluid when the probability of successful care is relatively low. When device 100 moves to the second orientation, the fluid delivery blocking can be stopped. Similarly, if device 100 moves from the second orientation to the first orientation, fluid delivery can be selectively blocked.

[0136] In one embodiment, the head 120 of the device 100 is operable to move along a row of teeth between a first end and a second end of a row, and a fluid delivery system 220 is at least partially included in the head 120. In another embodiment, signals received from the IMU 240 are processed to determine the trajectory of the head 120 of the oral care device 100 between the first and second ends of the row. Based on the determined trajectory, a control signal is output to the fluid delivery system 220. By controlling the fluid delivery system 220 based on the trajectory of the head 120 as it moves along a row of teeth, the device 100 can be controlled in a smarter and / or more flexible manner. In particular, fluid delivery can be prevented (thus preventing the waste of working fluid) when the trajectory indicates that successful care using the fluid delivery system 220 is relatively unlikely.

[0137] In one embodiment, signals received from the IMU 240 are processed to determine changes in the orientation of the head 120 of the oral care device 100 during movement between the first and second ends of a row of teeth. Based on the determined changes in the orientation of the head 120, a control signal is output to the fluid delivery system 220. Thus, fluid delivery can be controlled in response to changes in the orientation of the head 120 as the head 120 moves along a row of teeth. For example, the orientation of the head 120 may change as a user moves the device 100 along a row of teeth; for instance, the user may rotate the device 100 as it moves along the row of teeth. By taking into account such changes in orientation, the fluid delivery system 220 becomes more precise and / or efficient, for example, by delivering a jet of working fluid when a relatively high probability of successful treatment is determined based on the orientation, and preventing jetting when a relatively low probability of successful treatment is determined.

[0138] In one embodiment, the signal received from the IMU 240 is processed to determine that the movement of the oral care device 100 relative to the mouth has stopped. In response to this determination, a control signal is output to the fluid delivery system 220 to deliver working fluid. Thus, the user can move the device 100 along a row of teeth and pause when the device 100 approaches the interdental spaces the user wishes to treat. By detecting such pauses using the IMU signal and automatically triggering the fluid delivery system 220 accordingly, the need for user input to trigger the fluid delivery system 220 is reduced, thereby increasing the functionality of the device 100 and improving the user experience.

[0139] In this embodiment, signals received from IMU 240 are processed to detect interproximal gaps between adjacent teeth in the user's oral cavity. In response to the detection of an interproximal gap, a control signal is output to fluid delivery system 220. In this embodiment, the control signal is output to fluid delivery system 220 to cause the fluid delivery system to deliver working fluid to the detected interproximal gap. Therefore, interproximal gaps can be detected substantially automatically in real time based on IMU signals during use of device 100, and working fluid can be delivered to the detected gaps during use of device 100. In some cases, the user may not be aware of the existence of a specific gap, which can still be detected by the device based on IMU signals. Furthermore, by specifically triggering the injection of working fluid when a gap is detected, the efficiency and / or accuracy of fluid delivery system 220 is improved.

[0140] In embodiments, velocity and / or position estimation algorithms are used to process IMU signals. For example, the velocity and / or position estimation algorithm can be configured to estimate the velocity of device 100 for detecting rapidly changing velocities in any direction (e.g., detecting wiping motion). In embodiments, the velocity and / or position estimation algorithm is configured to feed accelerometer and gyroscope signals from the IMU. These signals can be processed individually or fused into a single data stream for use by the algorithm. For example, the velocity and / or position estimation algorithm can be used to determine that the device is moving along a row of teeth, determine the device's position relative to the oral cavity, and / or determine the device's velocity. The velocity and / or position estimation algorithm can be implemented using software or hardware (e.g., application-specific integrated circuits (ASICs)), or a combination of hardware and software. The velocity and / or position estimation algorithm can be used in the various methods described herein.

[0141] The IMU may be affected by noise, bias, and / or drift, which can lead to inaccurate calculations unless properly corrected. For example, gyroscope signals may drift over time, accelerometers may be biased due to gravity, and both gyroscope and accelerometer signals may be affected by noise. In embodiments, filtering (e.g., high-pass and / or low-pass and / or median filters) is used to remove at least some of the noise from the IMU signal. In embodiments, filters are used to correct gyroscope drift and / or compensate for gravity, thereby allowing linear velocity to be obtained, which can then be integrated to obtain position and / or displacement. Velocity and / or position measurements may include individual measurements of all three axes, or the directional components may be combined to provide velocity magnitude and / or position magnitude.

[0142] In this embodiment, IMU signals are processed to generate a user behavior profile. This profile indicates how the user uses device 100, for example, based on routines such as motion, orientation, speed, etc. For instance, the user behavior profile can be used to provide customized suggestions to the user. The user behavior profile can be modified and / or updated when new IMU data is obtained.

[0143] In this embodiment, the IMU signal is combined with intraoral image data generated by an image sensor device (such as image sensor device 230 described above). By using the IMU signal and the intraoral image data to control the fluid delivery system 220, the accuracy of the fluid delivery system 220 can be further improved compared to the case where the intraoral image data is not used.

[0144] Figure 8 A method 800 for operating an oral care device according to an embodiment is shown. Method 800 can be used to operate the device described above. Figure 1A , 1B and Figure 2 The oral care device 100 is described. Figure 8In some embodiments, the oral care device 100 includes a head 120 for caring for a user's mouth. The mouth includes multiple oral regions. In these embodiments, the oral care device 100 includes an IMU 240. The IMU 240 is operable to output signals depending on the position and / or movement of the head 120 of the oral care device 100. In some embodiments, method 800 is performed at least in part by a controller 210.

[0145] In step 810, a signal indicative of the position and / or movement of the head 120 of the oral care device 100 relative to the user's mouth is received from the IMU 240.

[0146] In step 820, the received signal is processed using a trained nonlinear classification algorithm to obtain classification data. The classification algorithm is trained to identify the oral cavity region in which the head 120 of the oral care device 100 is located from multiple oral cavity regions. The obtained classification data indicates the oral cavity region in which the head 120 of the oral care device 100 is located.

[0147] In step 830, the classification data is used to control the oral care device 100 to perform actions.

[0148] In one embodiment, the plurality of oral cavity areas includes more than two oral cavity areas. In another embodiment, the plurality of oral cavity areas includes more than four oral cavity areas. In yet another embodiment, the plurality of oral cavity areas includes 12 oral cavity areas. In yet another embodiment, the plurality of oral cavity areas includes 18 oral cavity areas.

[0149] In one embodiment, a given oral region among multiple oral regions indicates: a quadrant or sextant of the user's oral cavity; and a selection of tooth surfaces from a list including buccal, lingual, and occlusal surfaces. Thus, there can be 18 distinct oral regions corresponding to six oral sextants, each sextant having three tooth surfaces. In an alternative embodiment, the multiple oral regions include more than 18 oral regions.

[0150] By using IMU signals as input to a trained nonlinear classification algorithm, the oral cavity region where the head 120 is located can be identified without user input. Therefore, the oral care device 100 can autonomously recognize how the user uses the device and adjust itself accordingly. For example, one or more operating settings of the device 100 can be controlled based on the identified oral cavity region. Furthermore, this allows the user to be notified of the position of the head 120 within the mouth, the time spent in each region, etc. This information can also be used to determine whether the oral cavity region where the head 120 is located has been visited in the current oral care phase. In addition to providing direct user feedback, such information can facilitate the generation of behavioral profiles instructing the user on how they intend to use the device 100, based on factors such as the time spent in each oral cavity region and whether any regions were missed. Moreover, using a trained algorithm results in more accurate and / or more reliable localization of the head 120 compared to not using the trained algorithm. That is, the spatial resolution of the head 120's localization is improved by using a trained algorithm. Furthermore, the nonlinear classification algorithm can be used to distinguish factors that cannot be linearly separable. Therefore, using nonlinear classification algorithms to obtain classification data leads to more accurate and / or more reliable determination of the classification data.

[0151] In this embodiment, the classification algorithm includes a machine learning algorithm. Such a machine learning algorithm can be improved through experience and / or training (e.g., to improve the accuracy and / or reliability of the classification).

[0152] In one embodiment, the oral care device includes a machine learning agent. The machine learning agent includes a classification algorithm. Thus, the classification algorithm can reside on the oral care device 100. Performing oral region identification on the device 100 reduces latency compared to a scenario where the classification algorithm is not located on the device 100, because it eliminates the need to send data to and / or receive data from another device. This allows for faster identification of oral regions, thereby reducing the time spent taking any corrective actions and / or providing output via a user interface. In an alternative embodiment, the classification algorithm resides on a remote device. For example, such a remote device may have more processing resources than the oral care device 100.

[0153] In one embodiment, the oral care device 100 is controlled to deliver care to the user's mouth based on classification data. Therefore, the action performed in item 830 may include delivering care to the user's mouth.

[0154] In embodiments where the oral care device includes a fluid delivery system 220 for delivering working fluid to a user's mouth, control signals may be output to the fluid delivery system 220 to control the delivery of the working fluid based on classification data. Therefore, actions performed in item 830 may include controlling the delivery of working fluid by the fluid delivery system 220. In embodiments, the control signals are operable to block the delivery of working fluid based on classification data. This improves the efficiency and / or accuracy of the fluid delivery system 220, i.e., by taking into account the determined intraoral position of the head 120 of the device 100 during delivery (or non-delivery) of care.

[0155] In this embodiment, the user interface 250 is configured to provide output that depends on the classification data. Therefore, actions performed in item 830 may include providing output via the user interface 250. For example, such output may include a notification informing the user to spend more time in a specific oral region to improve the use of device 100 in delivering care.

[0156] In this embodiment, the user interface 250 provides output during the use of the oral care device 100 to care for the user's mouth. By providing output during the use of the device 100, rather than after the oral care process is completed, feedback can be provided more rapidly. For example, the user interface 250 can provide output substantially in real time. This allows users to adjust their behavior during the use of the device 100, such as taking corrective actions, thereby improving the effectiveness of care delivery.

[0157] In this embodiment, the user interface 250 provides output after the user has used the oral care device 100 to care for their mouth. Providing output after using the device 100 allows for a more detailed level of feedback compared to providing output during use. For example, the use and / or movement of the device 100 can be analyzed throughout the oral care phase, and feedback can then be provided to the user about the entire phase, such as suggesting that the user spend more time on a given oral area. This feedback encourages the user to adjust their behavior in subsequent phases.

[0158] In this embodiment, the output provided by the user interface includes audio, visual, and / or tactile output. For example, the output may be provided via a display, a speaker, and / or a tactile actuator.

[0159] In this embodiment, the user interface is included in a remote device, and signals are output to the remote device to enable the user interface to provide output. Such a user interface on the remote device can be more versatile than the user interface on the oral care device 100 itself, which may be handheld and / or have limited user interface space.

[0160] In this embodiment, the oral care device 100 includes a user interface 250. By providing a user interface 250 on the oral care device 100, the user can generate and receive output more quickly compared to a situation where the oral care device 100 does not have a user interface, because the need for communication between different devices is avoided. Furthermore, providing a user interface 250 on the oral care device 100 increases the likelihood that the user will receive feedback quickly. For example, while using the oral care device 100, the user may not be in the same location as the remote device, and therefore the user may not immediately see / hear notifications on the remote device.

[0161] In an embodiment, the user interface (e.g., on device 100 or on a remote device) provides output including a notification to the user that the head 120 of the oral care device 100 is positioned in a predetermined oral region. This notification is provided at the start of an oral care phase. By providing such a notification to the user, a non-linear classification algorithm knows the initial position of the head 120, i.e., the oral region in which the head 120 is located at the start of the phase. This can then be used as a constraint on the classification algorithm, allowing for increased accuracy and / or reliability in determining the subsequent intraoral position of the head 120.

[0162] In this embodiment, signals received from IMU 240 are used to improve the classification algorithm. That is, signals generated by IMU 240 can be used to train and / or further train the classification algorithm. Modifying the classification algorithm allows for improvements in accuracy and / or reliability through experience and / or the use of more training data. Furthermore, modifying the classification algorithm allows it to be adapted to the user. By using the generated IMU signals as training data for dynamically retraining the classification algorithm, the algorithm can more reliably identify the oral cavity region where the head 120 of device 100 is located.

[0163] In this embodiment, the categorized data is stored in memory 260. This allows the data to be used at a later time, for example, for post-processing analysis and / or for generating behavioral profiles of the user using device 100. In this embodiment, the categorized data is output for transmission to remote devices, such as user devices, such as mobile phones, tablets, laptops, personal computers, etc.

[0164] In this embodiment, training data is received from a remote device. The training data can be received from a network, such as the "cloud." This training data may include IMU data and / or classification data associated with other users. For example, this training data may include crowdsourced data. In this embodiment, this training data is larger in quantity than the IMU data and / or classification data obtained directly using the oral care device 100. Using training data from a remote device to modify the classification algorithm can improve the accuracy and / or reliability of the classification algorithm compared to not using such training data.

[0165] Figure 9 A method 900 for operating an oral care device according to an embodiment is shown. Method 900 can be used to operate the device described above. Figure 1A , 1B and Figure 2 The oral care device 100 is described. Figure 9 In some embodiments, the oral care device 100 includes a head for caring for a user's mouth. In these embodiments, the oral care device 100 also includes an IMU 240 and an image sensor device 230. The image sensor device 230 includes... Figure 9 The intraoral image sensor device in the embodiment. In the embodiment, method 900 is performed at least in part by controller 210.

[0166] In step 910, the IMU 240 is used to generate signals based on the position and / or movement of the head of the oral care device 100 relative to the user's mouth.

[0167] In step 920, image data representing at least a portion of the user's oral cavity is generated using image sensor device 230. It should be understood that steps 910 and 920 may be performed substantially simultaneously, or sequentially in either order.

[0168] In step 930, a trained classification algorithm is used to process the generated signals and generated image data to determine the intraoral position of the head 120 of the oral care device 100.

[0169] In step 940, the oral care device 100 is controlled to perform actions based on the determined intraoral position.

[0170] By using IMU signals and image data as input to train a classification algorithm, the intraoral position of the head 120 of device 100 can be determined without user input. Therefore, the oral care device 100 can autonomously recognize how the user uses the device and adjust itself accordingly. This allows for more intelligent control of the oral care device 100. For example, one or more operating settings of the device 100 can be controlled based on the determined intraoral position. Furthermore, using image data in conjunction with IMU data provides a more accurate determination of the intraoral position of the head 120 compared to using neither image data nor IMU data. For example, the spatial resolution of the intraoral position determination is improved by combining image data and IMU data.

[0171] In one embodiment, the oral cavity includes multiple oral regions. In such an embodiment, generated signals and generated image data are processed to identify the oral region where head 120 is located from the multiple oral regions. The oral care device 100 is controlled to perform actions based on the identified oral regions. In one embodiment, a given oral region among the multiple oral regions is indicated by: a quadrant or sextant of the oral cavity; and a tooth surface selected from a list including buccal, lingual, and occlusal surfaces, as described above. This can allow, for example, notification to the user about the position of head 120 of device 100 within the oral cavity, how much time has been spent in each oral region, etc. This information can also be used to determine whether the oral region where head 120 is located has been visited in the current oral care phase. In addition to providing direct user feedback, such information can facilitate the generation of behavioral profiles instructing the user on how they would prefer to use device 100, based on, for example, the time spent in each oral region, whether any oral regions were missed, etc.

[0172] In this embodiment, the oral cavity includes multiple teeth, and the generated signals and image data are processed to identify teeth adjacent (e.g., closest) to the head 120 of the oral care device 100 from among the multiple teeth. Based on the identified teeth, the oral care device 100 is controlled to perform actions. Therefore, the intraoral position of the head 120 of the device 100 is determined at the level of each tooth. This can allow, for example, providing user feedback, informing the user which specific teeth require additional care, etc. Thus, a more granular and / or customized level of feedback (e.g., with higher spatial resolution) can be provided compared to a situation where teeth adjacent to the head 120 of the device 100 are not identified.

[0173] In this embodiment, the generated signals and generated image data are processed to identify interproximal gaps between adjacent teeth in the user's oral cavity. The oral care device 100 is controlled to perform actions based on the identified interproximal gaps. Therefore, interproximal gaps can be automatically detected based on IMU signals and image data during use of the device 100. In some cases, the user may not be aware of the existence of a particular gap, but this gap can still be detected by the device 100 based on IMU signals and image data. As a result of gap detection, the user can be informed of the gap's location, the device 100 can be controlled to deliver care to the gap, and so on. Therefore, the intraoral position of the head 120 of the device 100 is determined at each gap level. Thus, the method described herein has higher spatial resolution than other methods. In this embodiment, gap identification is a separate process for identifying the oral cavity area where the head 120 is located. For example, the gap between adjacent teeth can be identified first, and the head 120 can also be further identified as being located in a specific oral cavity area (i.e., region). This facilitates the localization of detected gaps.

[0174] In this embodiment, the classification algorithm includes a machine learning algorithm. Such a machine learning algorithm can be improved through experience and / or training (e.g., to improve the accuracy and / or reliability of the classification).

[0175] In one embodiment, the oral care device includes a machine learning agent that includes a classification algorithm. Thus, the classification algorithm can reside on the oral care device 100. Performing intraoral location determination on the device 100 reduces latency compared to a scenario where the classification algorithm is not located on the device 100, because there is no need to send data to and / or receive data from another device. This allows for faster determination of intraoral location, thereby reducing the time spent taking any corrective actions and / or providing output via a user interface. In an alternative embodiment, the classification algorithm resides on a remote device, such as a device with more processing resources than the oral care device 100.

[0176] In this embodiment, the generated signals and / or generated image data are used to improve the classification algorithm. That is, the generated signals and / or generated image data can be used to train and / or further train the classification algorithm. Modifying the classification algorithm allows for improvements in accuracy and / or reliability through experience and / or the use of more training data. In other words, the confidence level of the determined intraoral location can be increased. Furthermore, modifying the classification algorithm allows it to be adapted to the user. By using the generated signals and / or generated image data as training data for dynamically retraining the classification algorithm, the algorithm can more reliably determine the intraoral location of the head 120 of device 100.

[0177] In one embodiment, the oral care device 100 is controlled to deliver care to the user's mouth based on a determined intraoral location. Therefore, the actions performed in item 940 may include the delivery of care by the device 100.

[0178] In embodiments where the oral care device 100 includes a fluid delivery system 220 for delivering working fluid to a user's mouth, control signals are output to the fluid delivery system 220 to control the delivery of the working fluid based on a determined intraoral position. Therefore, actions performed in item 940 may include control of the fluid delivery system 220. For example, the intraoral position may be used to determine whether to trigger the ejection of the working fluid. This improves the efficiency and / or accuracy of the fluid delivery system 220 by taking into account the determined intraoral position of the head 120 of the device 100 when delivering (or not delivering) care.

[0179] In this embodiment, the user interface 250 provides output based on the determined intraoral location. Therefore, actions performed in item 940 may include providing output via the user interface 250. In this embodiment, the user interface 250 provides output during oral care of the user's mouth using the oral care device 100. By providing output during use of the device 100 using the user interface 250, rather than after the oral care process is completed, feedback can be provided more rapidly. For example, the user interface 250 may provide output substantially in real time. This allows users to adjust their behavior during use of the device 100, such as taking corrective actions, thereby improving the effectiveness of care delivery.

[0180] In this embodiment, the user interface 250 provides output after the user has used the oral care device 100 to care for their mouth. Providing output after using the device 100 allows for a more detailed level of feedback compared to providing output during use. For example, the use and / or movement of the device can be analyzed throughout the oral care phase, and feedback about the entire phase can then be provided to the user. In this embodiment, the user interface 250 provides output both during and after using the device 100.

[0181] In this embodiment, the output provided by the user interface includes audio, visual, and / or tactile output. For example, the output may be provided via a display, a speaker, and / or a tactile actuator.

[0182] In one embodiment, the user interface is included in a remote device, such as a user equipment like a mobile phone. In such an embodiment, signals are output to the remote device to cause the user interface to provide output. The user interface on this remote device may be more versatile than the user interface on the oral care device 100 itself.

[0183] In this embodiment, the oral care device 100 includes a user interface 250. By providing the user interface 250 on the oral care device 100, the user can generate and receive output more quickly compared to a case where the oral care device 100 does not have a user interface, because the need for communication between different devices is avoided. Furthermore, providing the user interface 250 on the oral care device 100 increases the likelihood that the user will receive feedback more quickly.

[0184] In one embodiment, data indicating the determined intraoral location is output to be stored in memory 260. This allows the data to be used at a later time, for example, for post-processing analysis and / or for generating a behavioral profile of the user using device 100. In another embodiment, the data indicating the determined intraoral location is output to be transmitted to a remote device, such as a user device.

[0185] In an embodiment, the determined intraoral position of the head 120 of the device 100 is used as part of the interoral space detection and care process, as referenced above. Figures 3 to 6 One or more methods are described. In an embodiment, a defined intraoral location of the head 120 is used in a dental plaque detection process, for example, using qualitative plaque fluorescence.

[0186] Figure 10 A method 1000 for operating an oral care device according to an embodiment is shown. Method 1000 can be used to operate the device described above. Figure 1A , 1B and Figure 2 The oral care device 100 is described. Figure 10 In one embodiment, the oral care device 100 includes an IMU 240. The IMU 240 is operable to output signals based on the motion of the oral care device 100. In another embodiment, method 1000 is performed at least in part by the controller 210.

[0187] In step 1010, a signal instructing the movement of the oral care device 100 relative to the user's mouth is received.

[0188] In step 1020, the received signal is processed using a trained classification algorithm to obtain classification data. The classification algorithm is configured (e.g., trained) to determine whether the oral care device 100 is moving according to a predetermined type of movement.

[0189] In step 1030, the classification data is used to control the oral care device 100 to perform actions.

[0190] By using signals from the IMU 240 as input to the classification algorithm, the current movement type of device 100 can be identified. Therefore, device 100 can autonomously recognize how the user moves the device and adjust itself accordingly. This allows for smarter control of the oral care device 100. For example, one or more operating settings of device 100 can be controlled based on the identified behavior. This allows the settings of device 100 to more closely correspond to how the user uses the device. Using a trained algorithm results in more accurate and / or more reliable movement type classification compared to not using a trained algorithm.

[0191] In an embodiment, the movement of the oral care device 100 according to a predetermined type of movement hinders its use in caring for a user's mouth. Therefore, it can be determined when the device 100 moves in a manner that reduces the likelihood of successful care delivered by the device 100. Based on such determination, the user can be alerted and / or the device 100 can be controlled accordingly. For example, in an embodiment, the predetermined type of movement includes a swishing motion. A swishing motion includes rapid back-and-forth movements. This type of movement hinders the effective delivery of some care, such as delivering working fluid to the interdental spaces between teeth. Therefore, by determining whether the device 100 is moving in this manner, corrective actions can be taken, either by the user when the device 100 notifies them that the type of movement hinders effective treatment, or by the device 100 itself, for example, by controlling the delivery of care.

[0192] In an embodiment, in response to classification data indicating that the oral care device 100 is moving according to a predetermined movement type, the delivery of care by the oral care device 100 in the user's mouth is blocked. Therefore, the action performed in item 1030 may include blocking care delivery. As described above, when the device 100 moves according to a predetermined movement type, its use in effectively caring for the user's mouth may be hindered, i.e., negatively impacted. Therefore, by blocking care delivery when it is determined that the device 100 is moving according to a predetermined movement type, the device 100 is operated more effectively. That is, due to the way the device 100 is moved, it does not attempt to deliver care when the probability of success is determined to be relatively low.

[0193] In an embodiment, in response to classification data indicating that the oral care device 100 is not moving according to a predetermined movement type, the oral care device 100 is controlled to deliver care in the user's mouth. Therefore, the delivery of care can be triggered by determining that the device 100 is not moving according to a predetermined movement type, for example, determining that the device 100 is not moving with a swishing motion. Thus, if it is determined that the device 100 is moving according to a predetermined type, care delivery can be prevented, and if it is determined that the device 100 is not moving according to a predetermined movement type, care delivery can be triggered (or allowed). Therefore, the movement type of the device 100 is used as a condition for deciding whether to perform care delivery.

[0194] In one embodiment, in response to classification data indicating that device 100 is moving according to another predetermined type of movement, device 100 is controlled to deliver oral care to the user. In an example where the predetermined type of movement includes swishing motions, for example, another predetermined type of movement may include no movement or a “smooth” gliding motion different from swishing motions. Therefore, to improve the efficiency and / or effectiveness of care delivery, the user may be discouraged from using a predetermined type of movement, and encouraged to use another predetermined type of movement.

[0195] In embodiments where the oral care device 100 includes a fluid delivery system 220 for delivering working fluid to a user's oral cavity, control signals are output to the fluid delivery system 220 to control the delivery of the working fluid based on classification data. Therefore, actions performed in item 1030 may include controlling the fluid delivery system 220. For example, if it is determined that the device 100 is moving according to a predetermined type of movement, the delivery of the working fluid can be blocked. The user may move the device 100 in a manner that hinders the accurate and / or reliable delivery of the working fluid to its target (e.g., the interproximal space between adjacent teeth). For example, if the device 100 moves too quickly, such as during a scrubbing motion, the fluid delivery system 220 is unlikely to deliver the jet of working fluid to where it is actually intended, such as the interproximal space. This can be a particular consideration when the coverage area of ​​the fluid jet is relatively small (i.e., focused). This means that the working fluid is more likely to be wasted because the target is missed, and effective care is less likely to be achieved (at least without repeated fluid jet attempts). By controlling the fluid delivery system 220 based on whether the device 100 moves according to a predetermined motion type, the accuracy and / or efficiency of the fluid delivery system 220 is increased, and the amount of working fluid used and / or wasted is reduced.

[0196] In an embodiment, Figure 10 The method is similar to image-based neighbor gap detection and processing procedures (e.g., the above). Figure 4 The method is combined with the execution. In such an embodiment, if the device 100 is moving in a scrubbing motion, the detection of adjacent gaps may be hindered because the image sensor device 230 is moving too fast. Even if the gap is successfully detected, the scrubbing motion may impede the accuracy of the fluid delivery system 220 in delivering the working fluid jet to the detected gap. Therefore, by selectively blocking care delivery when it is determined that the device 100 is moving according to a predetermined motion type, the performance of the adjacent gap detection and handling process is improved.

[0197] In this embodiment, features are extracted from the received IMU signals substantially in real time, i.e., during use of device 100. A sliding window may be applied to the IMU signals to extract features (e.g., one or more averages) from the signals. These extracted features are fed into a trained classification algorithm that determines whether device 100 is moving according to a predetermined motion type. In this embodiment, IMU 240 includes a 6-axis IMU providing accelerometer and gyroscope data. In an alternative embodiment, IMU 240 provides only one of the accelerometer and gyroscope data.

[0198] In this embodiment, the IMU signal is sampled at a predetermined sampling rate for analysis by a trained classification algorithm. The sampling rate can be predetermined based on the available computing resources of device 100, whether the analysis will be performed on a remote device rather than on device 100 itself, etc. For example, sampling the IMU signal relatively infrequently may be computationally cheaper than sampling it relatively frequently. However, sampling the IMU signal at a lower frequency may also increase the latency between signal acquisition and control device 100, and / or may reduce the accuracy of motion type determination by the classification algorithm. Therefore, a trade-off between performance and processing resources may exist when determining the sampling rate of the IMU signal.

[0199] In an embodiment, in response to an instruction that the oral care device 100 is exercising according to classification data of a predetermined type of movement, the user interface provides output. For example, the device 100 may include the above-mentioned reference. Figure 2 The user interface 250 is described, and output can be provided via the user interface 250. Therefore, actions performed in item 1030 may include providing output via the user interface 250. By providing output to the user, the user device 100 can be notified that it is moving in a manner that hinders effective processing of the device 100, thereby prompting the user to take corrective action. In embodiments, the output provided by the user interface 250 includes audio, visual, and / or tactile output. For example, output provided via the user interface 250 may include flashing lights, audio, and / or vibration.

[0200] In this embodiment, the user interface 250 provides output during the use of the oral care device to treat the user's mouth. By providing output during the use of the device 100, rather than after the oral care process is completed, feedback can be provided more rapidly. For example, the user interface 250 can provide output substantially in real time. This allows users to adjust their behavior during the use of the device 100, such as taking corrective actions, thereby improving the effectiveness of care delivery.

[0201] In this embodiment, the user interface 250 provides output after the user has used the oral care device 100 to care for their mouth. Providing output after using the device 100 allows for a more detailed level of feedback compared to providing output during use. For example, the use and / or movement of the device 100 can be analyzed throughout the oral care phase, and feedback about the entire phase can then be provided to the user. This feedback encourages the user to adjust their behavior in subsequent phases.

[0202] In this embodiment, user feedback is provided during use of device 100 (e.g., substantially in real time) and after the processing phase has ended. For example, during use of device 100, the user interface 250 of device 100 may provide the user with an indication that device 100 is moving suboptimally, such as during a scrubbing motion. Furthermore, an additional user interface located on a remote device may provide a more detailed analysis of user behavior after the care phase has ended. This allows the user to adjust how they will use device 100 in subsequent phases.

[0203] In this embodiment, the oral care device 100 includes a user interface 250. By providing the user interface 250 on the oral care device 100, the user can generate and receive output more quickly compared to a case where the oral care device does not have a user interface, because the need for communication between different devices is avoided. Furthermore, providing a user interface on the oral care device 100 increases the likelihood that the user will receive feedback quickly.

[0204] In one embodiment, the user interface is included in a remote device, such as a user device. In such an embodiment, a signal is output to the remote device to cause the user interface to provide output. This signal can be wirelessly transmitted to the remote device, for example, via Bluetooth technology. The user interface on such a remote device may be more versatile than the user interface on the oral care device itself. For example, since the oral care device 100 is typically handheld and may have various other components, the amount of space available for a user interface on the oral care device 100 may be limited.

[0205] In this embodiment, signals received from IMU 240 are used to improve the classification algorithm. That is, IMU signals can be used to train and / or further train the classification algorithm. Modifying the classification algorithm allows for improvements in accuracy and / or reliability through experience and / or the use of more training data. In other words, the confidence level of the determined movement type can be increased. Furthermore, modifying the classification algorithm allows it to be tailored to the user. For example, an initial classification algorithm may be provided on the oral care device 100, but this initial algorithm does not take into account the specific behavior of a given user. For example, a user may move device 100 in a specific manner different from other users. By using the generated signals as training data for dynamically retraining the classification algorithm, the algorithm can more reliably determine whether device 100 is moving according to a predetermined movement type.

[0206] In one embodiment, the classification algorithm is retrained (e.g., improved) using signals received from the IMU 240, such that the retrained classification algorithm is configured to determine whether the oral care device is moving according to a different type of movement than a predetermined type. Therefore, the classification algorithm can be initially trained to detect a first type of movement and can be retrained based on user-specific data to detect a second, different type of movement. Thus, the classification algorithm can be customized for the behavior of a particular user, such as detecting a specific type of movement used by the user.

[0207] In one embodiment, the categorized data is stored in memory 260. This allows the data to be used at a later time, for example, for post-processing analysis and / or for generating behavioral profiles of the user using device 100. In another embodiment, the categorized data is output for transmission to a remote device, such as a user device.

[0208] In one embodiment, training data is received from a remote device. In such an embodiment, the received training data is used to modify the classification algorithm. The training data can be received from a network, such as the "cloud." This training data may include IMU data and / or classification data associated with other users. For example, this training data may include crowdsourced data. In this embodiment, this training data is larger in quantity than the IMU data and / or classification data obtained directly using the oral care device 100. Using training data from a remote device to modify the classification algorithm can improve the accuracy and / or reliability of the classification algorithm compared to not using such training data.

[0209] In this embodiment, the classification algorithm includes a nonlinear classification algorithm. Nonlinear classification algorithms can be used to distinguish behaviors that cannot be linearly separable. This could be a situation where a user is using a mobile device during operation. Therefore, using a nonlinear classification algorithm to obtain classification data results in a more accurate and / or more reliable determination of the classification data compared to using a linear classification algorithm or function.

[0210] In this embodiment, the classification algorithm includes a machine learning algorithm. This machine learning algorithm can be improved through experience and / or training (e.g., to improve the accuracy and / or reliability of classification). In this embodiment, the classification algorithm...

[0211] Supervised and / or unsupervised machine learning methods are used to train the device 100 to detect whether it is moving according to a predetermined motion type.

[0212] In one embodiment, the oral care device includes a machine learning agent that includes a classification algorithm. Thus, the classification algorithm can reside on the oral care device 100. Performing motion type determination on the device 100 reduces latency compared to a scenario where the classification algorithm is not located on the device 100, because it eliminates the need to send data to and / or receive data from another device. This allows for faster differentiation of motion types, thereby reducing the time spent taking any corrective actions and / or providing output via a user interface.

[0213] It should be understood that any feature described with respect to any embodiment and / or aspect may be used alone or in combination with other described features, and may also be used in combination with one or more features of any other embodiment and / or aspect, or in any combination of any other embodiment and / or aspect. For example, it will be appreciated that features and / or steps described with respect to a given method of methods 300, 400, 500, 600, 700, 800, 900, 1000 may be included in place of or supplement to features and / or steps described with respect to other methods of methods 300, 400, 500, 600, 700, 800, 900, 1000.

[0214] In embodiments of this disclosure, the automated operation of device 100 (e.g., with respect to any of methods 300, 400, 500, 600, 700, 800, 1000) can be overridden by a user of device 100. For example, a user may desire re-care (e.g., another jet of working fluid) to be delivered to an already treated adjacent gap, where automated operation implemented by controller 210 prevents such re-care. This may occur, for example, if the initial care of the gap is unsuccessful and / or the user is dissatisfied. In embodiments, device 100 includes a user interface, such as a button, to enable the user to force re-care, thereby overriding the automated operation of device 100.

[0215] In embodiments of this disclosure, one or more data analysis algorithms are used to control the oral care device 100, such as detecting interproximal gaps, determining the intraoral position of the head of the device 100, determining whether the device 100 is moving according to a predetermined type of movement, etc. The data analysis algorithms are configured to analyze received data, such as image data and / or IMU data, and produce outputs that can be used as conditions for controlling the device 100, such as gaps or no gaps. In embodiments, the data analysis algorithms include classification algorithms, such as nonlinear classification algorithms. In embodiments, the data analysis algorithms include trained classification algorithms, such as those referenced above. Figures 3 to 10 As described. However, in alternative embodiments, the data analysis algorithm includes other types of algorithms, for example, that are not necessarily trained and / or configured to perform classification.

[0216] In embodiments of this disclosure, oral care device 100 includes a controller 210. The controller 210 is configured to perform the various methods described herein. In embodiments, the controller 210 includes a processing system. Such a processing system may include one or more processors and / or memory. Each device, component, or function described with respect to any example described herein, such as image sensor device 230, user interface 250, and / or machine learning agent, may similarly include a processor or may be included in a device including a processor. One or more aspects of the embodiments described herein include processes performed by the device. In some examples, the device includes one or more processors configured to perform these processes. In this respect, embodiments may be implemented at least in part by computer software stored in (non-transitory) memory and executable by a processor, or by hardware, or by a combination of software and hardware (and firmware) in tangible storage. Embodiments also extend to computer programs, particularly computer programs on or in a carrier, suitable for putting the above embodiments into practice. The program may be in the form of non-transitory source code, object code, or any other non-transitory form suitable for use in the implementation of the processes according to the embodiments. The carrier can be any entity or device capable of carrying a program, such as RAM, ROM, or optical storage devices.

[0217] One or more processors in the processing system may include a central processing unit (CPU). One or more processors may include a graphics processing unit (GPU). One or more processors may include one or more of a field-programmable gate array (FPGA), a programmable logic device (PLD), or a complex programmable logic device (CPLD). One or more processors may include an application-specific integrated circuit (ASIC). Those skilled in the art will understand that many other types of devices besides the examples provided can be used to provide one or more processors. One or more processors may include multiple co-located processors or multiple differently located processors. Operations performed by one or more processors may be performed by one or more of hardware, firmware, and software. It should be understood that the processing system may include more, fewer, and / or different components than described.

[0218] The techniques described herein can be implemented in software or hardware, or in a combination of software and hardware. They can include devices configured to perform and / or support any or all of the techniques described herein. While at least some aspects of the examples described herein with reference to the accompanying drawings include computer processes executed in a processing system or processor, the examples described herein also extend to computer programs, such as computer programs on or within a carrier, suitable for putting the examples into practice. A carrier can be any entity or device capable of carrying a program. A carrier can include a computer-readable storage medium. Examples of tangible computer-readable storage media include, but are not limited to, optical media (e.g., CD-ROM, DVD-ROM, or Blu-ray), flash memory cards, floppy disks, or hard disks, or any other medium capable of storing computer-readable instructions such as firmware or microcode in at least one ROM or RAM or programmable ROM (PROM) chip.

[0219] In the foregoing description, references have been made to elements or components having known, obvious, or foreseeable equivalents, which are incorporated herein as if individually stated. The true scope of this disclosure should be determined with reference to the claims, which should be interpreted as including any such equivalents. The reader will also understand that elements or features of this disclosure described as preferred, advantageous, convenient, etc., are optional and do not limit the scope of the independent claims. Furthermore, it should be understood that while such optional elements or features may be beneficial in some embodiments of this disclosure, they may be undesirable in other embodiments and therefore may not be present.

Claims

1. An oral care device, comprising: The head is used to care for the user's oral cavity, which includes multiple oral regions; An inertial measurement unit (IMU) is operable to output signals depending on the position and / or movement of the head of the oral care device; as well as Fluid delivery systems are used to deliver working fluids to the user's oral cavity; The controller is configured as follows: Receive signals from the IMU indicating the position and / or movement of the head of the oral care device relative to the user's mouth; The received signals are processed to obtain classification data to identify the oral cavity in which the head of the oral care device is located from the plurality of oral cavity areas, wherein the obtained classification data indicates the oral cavity in which the head of the oral care device is located; Using the classification data to control the oral care device to perform actions includes outputting control signals to the fluid delivery system to control the delivery of working fluid based on the classification data.

2. The oral treatment device of claim 1, wherein, The plurality of oral regions includes more than two oral regions.

3. The oral care device of claim 1, wherein, The multiple oral regions include 18 oral regions.

4. The oral care device of claim 1, wherein, Indication of a given oral region among the plurality of oral regions: The quadrants or sextant of the oral cavity, and Selected from a list including the buccal, lingual, and occlusal surfaces of teeth.

5. The oral care device according to claim 1, The received signal is processed using a trained nonlinear classification algorithm to obtain classified data.

6. The oral care device of claim 5, wherein, The classification algorithm includes machine learning algorithms.

7. The oral care device of claim 1, wherein, The oral care device includes a machine learning agent, which includes a classification algorithm.

8. The oral care device according to claim 1, wherein, The controller is configured to control the oral care device based on the classification data to deliver care to the user's mouth.

9. The oral care device according to claim 1, wherein, The control signal is operable to block the delivery of the working fluid based on the classification data.

10. The oral care device according to claim 1, wherein, The controller is configured to enable the user interface to provide output based on the classification data.

11. The oral care device according to claim 10, wherein, The controller is configured to enable the user interface to provide output during oral care for a user using the oral care device.

12. The oral care device according to claim 10, wherein, The controller is configured to enable the user interface to provide output after the user's oral cavity has been cared for using the oral care device.

13. The oral care device according to claim 10, wherein, The output provided by the user interface includes audio, visual, and / or haptic output.

14. The oral care device according to any one of claims 10 to 13, in, The user interface is included in a remote device, and The controller is configured to output a signal to the remote device so that the user interface provides output.

15. The oral care device according to any one of claims 10 to 13, wherein, The oral care device includes a user interface.

16. The oral care device according to claim 1, wherein, The controller is configured to enable the user interface to provide output, which includes a notification to the user to position the head of the oral care device in a predetermined oral cavity area.

17. The oral care device according to claim 5, wherein, The controller is configured to use signals received from the IMU to modify the classification algorithm.

18. The oral care device according to claim 1, wherein, The controller is configured to store the classified data in a memory.

19. The oral care device according to claim 1, wherein, The controller is configured to output the classification data for transmission to a remote device.

20. The oral care device according to claim 5, wherein, The controller is configured as follows: Receive training data from a remote device; and The classification algorithm is modified using the received training data.

21. A computer program comprising a set of instructions, when executed by a computerized device, the instructions causing the computerized device to perform a method of operating an oral care device for caring for a user's oral cavity, the oral care device including a head for caring for the user's oral cavity, the oral cavity including a plurality of oral regions; an inertial measurement unit (IMU) operable to output a signal depending on the position and / or motion of the head of the oral care device; And a fluid delivery system for delivering working fluid to a user's oral cavity; the method includes: Receive signals from the IMU indicating the position and / or movement of the head of the oral care device relative to the user's mouth; The received signal is processed using a trained nonlinear classification algorithm to obtain classification data, wherein the classification algorithm is trained to identify the oral cavity in which the head of the oral care device is located from the plurality of oral cavity cavities, wherein the obtained classification data indicates that the head of the oral care device is located in the oral cavity cavities; and the classification data is used to control the oral care device to perform actions, including outputting control signals to the fluid delivery system to control the delivery of working fluid based on the classification data.

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