Device for oral treatment

Abstract

An oral treatment device is provided. The oral treatment device comprises an image sensor device operable to generate image data depicting at least a portion of a user's oral cavity. The oral treatment device comprises a controller configured to process the generated image data to identify an interproximal space between adjacent teeth in the user's oral cavity. The controller is configured to compare at least one characteristic of the identified interproximal space with at least one characteristic of one or more previously identified interproximal spaces in the user's oral cavity. The controller is configured to control the oral treatment device to perform an action based on a result of the comparison.

Description

Technical Field

[0001] The present disclosure relates to devices for oral treatment. In particular, the present disclosure relates to means for operating an oral treatment device, such means including, but not limited to, methods, devices, and computer programs.

Background Art

[0002] Oral treatment devices are used to provide treatment to a user's oral cavity (i.e., the mouth). Examples of such devices include toothbrushes (which may be manual or electric), oral irrigators, interdental cleaning devices, flossing devices, and the like.

[0003] In some known cases, an oral treatment device (also referred to as an "oral care device" or "oral treatment instrument") can provide a flossing function in addition to other functions such as toothbrushing. For example, a fluid delivery system can be incorporated into an electric toothbrush and used to deliver the injection of a working fluid for adjacent interdental (or interproximal) cleaning. Such a fluid delivery system can include a nozzle disposed on the head of the device, which is used to eject the working fluid into the adjacent interdental space between teeth, for example, for the purpose of displacing food within the space, and a fluid reservoir for storing the working fluid on the device.

[0004] However, there are limitations to the freedom and / or versatility of known oral treatment devices. As a result, the ability to optimally perform treatment with known devices can be limited. For example, known oral treatment devices generally rely on the user using the device correctly, which may not always be the case.

[0005] For example, the efficient use of the working fluid can be a particular consideration in the case of an on-board fluid reservoir where the oral treatment device has a fixed volume. An increased amount and / or waste of the working fluid would require more frequent replenishment of the fluid reservoir. In some cases, effective treatment may not be achieved even after repeated attempts.

SUMMARY OF THE INVENTION

PROBLEMS TO BE SOLVED BY THE INVENTION

[0006] Therefore, it is desirable to provide an improved oral treatment device and / or an improved method for operating an oral treatment device.

MEANS FOR SOLVING THE PROBLEMS

[0007] According to one aspect of the present disclosure, there is provided an oral treatment device for use in treating a user's oral cavity, the oral treatment device comprising an image sensor device operable to generate image data depicting at least a portion of the user's oral cavity, and a control unit configured to process the generated image data to identify adjacent interdental spaces between adjacent teeth in the user's oral cavity, compare at least one characteristic of the identified adjacent interdental spaces with at least one characteristic of one or more adjacent interdental spaces previously identified in the user's oral cavity, and control the oral treatment device based on the result of the comparison to perform an action.

[0008] By comparing the characteristics of a specified interdental space with the characteristics of one or more interdental spaces of a user specified in the past, an oral treatment device is controlled in a more intelligent and / or more flexible manner. In particular, a determination can be made as to whether the specified space has been specified in the past during the current oral treatment session (i.e., during use of the device by the user). In various embodiments, a newly specified space is processed in a different manner than a previously specified space. That is, the device can be controlled by a first method if the specified space is determined to be a newly specified space, and can be controlled by a different second method if the specified space is determined to be a previously specified space (or similar to a previously specified space). Depending on the mode of operation of the oral treatment device by the user, the frequency of encounter with a given space can be once or multiple times during an oral treatment session. Thus, by processing a newly specified space in a different manner than a previously specified space, the device can be adapted to the behavior of the user.

[0009] In various embodiments, the control unit is configured to calculate a similarity metric indicating a level of similarity between the identified adjacent interproximal space and one or more adjacent interproximal spaces identified in the past, according to the result of the comparison. In such an embodiment, the control unit is configured to control the oral treatment device based on the derived similarity metric. The similarity metric can indicate whether the identified space is the same as or different from one or more spaces identified in the past. That is, the similarity metric can indicate whether the identified space is a newly identified space or a previously identified space. A space can be "newly identified" if it is determined not to have been encountered during the current oral treatment session. That is, even if a space may have been identified during a past oral treatment session, it can still be designated as a newly identified space if it has not been encountered during the current session. In various embodiments, the similarity metric is compared to a threshold value. If the similarity metric has a first predetermined relationship with the threshold value, for example, if the similarity metric is lower than the threshold value, the space is designated as a newly identified space. If the similarity metric has a second predetermined relationship with the threshold value, for example, if the similarity metric is higher than the threshold value, the space is designated as a previously identified space. In an alternative embodiment, if the similarity metric is equal to the threshold value, the space can be designated as either a previously identified space or a newly identified space.

[0010] In various embodiments, the control unit is configured to control the oral treatment device to treat the identified adjacent interproximal space in response to the similarity metric indicating that the identified adjacent interproximal space is different from one or more adjacent interproximal spaces identified in the past. Thus, if it is determined that the identified space is a newly identified space, the implementation of treatment can be triggered.

[0011] In various embodiments, the control unit is configured to store, in a memory, image data depicting a specified interproximal space for use in subsequent identification and / or comparison of interproximal spaces in response to the similarity score indicating that the specified interproximal space is different from one or more interproximal spaces specified in the past. In this way, by comparing the space with a subsequently specified space, it can be determined whether the subsequently specified space has been encountered in the past. In various embodiments, the image data is stored in a library that includes image data corresponding to a plurality of spaces specified in the past.

[0012] In various embodiments, the control unit is configured to control an oral treatment device to stop performing a treatment on a specified interproximal space in response to the similarity metric indicating that the specified interproximal space is the same as at least one of one or more interproximal spaces specified in the past. In this way, repeated treatment of the same space during a single oral treatment session can be reduced and / or avoided. This enables more efficient use of the oral treatment device. In an example where the treatment includes delivery of a working fluid via a fluid delivery system, reducing repeated treatment of the same space reduces the amount of working fluid used.

[0013] In various embodiments, the control unit is configured to derive an elapsed time from the time when at least one of one or more interproximal spaces specified in the past was specified in response to the similarity metric indicating that the specified interproximal space is the same as at least one of one or more interproximal spaces specified in the past. The control unit is configured to compare the derived elapsed time with a predetermined threshold. In such an embodiment, the control unit is configured to control the oral treatment device based on the result of the comparison between the derived elapsed time and the predetermined threshold. In this way, the control of the device can vary depending on the length of the elapsed time from the time when the space was specified in the past. This enables the device to be controlled in a more intelligent and / or more flexible manner.

[0014] In multiple embodiments, the control unit is configured to control the oral treatment device to perform a treatment on the identified adjacent interdental space in response to the derived elapsed time being longer than a predetermined threshold. Accordingly, when a predetermined length of time has elapsed since the treatment of a past space, the repeated treatment of the space can be performed. In various embodiments, the control unit is configured to control the oral treatment device to stop the performance of the treatment on the identified adjacent interdental space in response to the derived elapsed time being shorter than a predetermined threshold. Accordingly, when a predetermined length of time has not elapsed since the treatment of a past space, the repeated treatment of the space is not performed. For example, when the user moves the device back and forth in a "scrubbing" motion, the device may encounter the same space twice in relatively quick succession. In this case, it is not desirable to treat the space multiple times. However, if the user returns the device to a space that was treated in the past much later during the session, for example, if the initial treatment of the space was unsuccessful or insufficient, further treatment of the aforementioned space is likely to be desired.

[0015] In various embodiments, the control unit is configured to process the generated image data using a data analysis algorithm configured to detect adjacent interdental spaces. In various embodiments, the data analysis algorithm includes a classification algorithm. For example, the data analysis algorithm may include a trained classification algorithm. Using such a trained algorithm results in a more accurate and / or reliable detection of the interdental space compared to the case where a trained algorithm is not used. In various embodiments, the classification algorithm comprises a machine learning algorithm. Such a machine learning algorithm can be improved by experience and / or training (e.g., the accuracy and / or reliability of classification can be increased).

[0016] In various embodiments, the control unit is configured to process the generated image data to derive at least one characteristic of the identified adjacent interproximal spaces. In various embodiments, the control unit is configured to derive at least one characteristic by processing the generated image data using a machine learning algorithm trained to identify information used when distinguishing between adjacent interproximal spaces. Such a machine learning algorithm may be the same as or different from the machine learning algorithm optionally used to detect adjacent interproximal spaces in the image. That is, a first machine learning algorithm can be used to detect the spaces, and then a second machine learning algorithm can be used to identify information used when distinguishing the aforementioned spaces from other spaces. The identified information may include at least one characteristic of the spaces.

[0017] In various embodiments, the at least one characteristic includes a feature expected to differ between spaces or a feature specific to the identified space. In this way, the spaces can be distinguished using the at least one characteristic. In various embodiments, at least one characteristic of the identified adjacent interproximal spaces indicates at least one of the shape of the identified adjacent interproximal spaces, the appearance of the identified adjacent interproximal spaces, and the position of the identified adjacent interproximal spaces. In various embodiments, the at least one characteristic indicates frequency information based on, for example, a wavelet transform applied to an image of the space. In various embodiments, the at least one characteristic includes a combination of the above features, for example, a combination of shape, appearance, position, texture, etc.

[0018] In various embodiments, the image sensor device includes an intraoral camera. In this way, the interior of the user's oral cavity is imaged during use of the device.

[0019] In various embodiments, the oral treatment device comprises a head, and the image sensor device is at least partially included in the head. Since the head of the device is for performing a treatment inside the user's oral cavity, arranging the image sensor device at least partially within the head enables imaging of the inside of the oral cavity without the need for a separate camera (i.e., a camera attached separately from the head).

[0020] In various embodiments, the oral treatment device comprises a handle, and the image sensor device is at least partially included in the handle. By arranging the image sensor device at least partially within the handle of the device, the space on the device can be managed more efficiently. That is, the head of the device can be relatively small compared to the handle, and if the image sensor device is incorporated into the head, changes to the architecture and / or structure of the head may be required, and such changes can be relatively complex and / or costly. Further, in various embodiments, the head of the device is a disposable type separable from the handle, and in some cases, it may be desirable for the user to periodically replace the head after use. Therefore, by arranging at least a portion of the image sensor device within the handle rather than placing the entire image sensor device within the head 120, the cost of replacement parts is reduced.

[0021] In various embodiments, the oral treatment device comprises a fluid delivery system for delivering a working fluid to the user's oral cavity. In some such embodiments, the control unit is configured to output a control signal to the fluid delivery system based on the result of the comparison to control the delivery of the working fluid. Thus, the actions performed can include the controlled delivery (or the cessation of the delivery) of the working fluid. In various embodiments, the fluid delivery system comprises a fluid reservoir for storing the working fluid within the oral treatment device. The fluid reservoir may, for example, have a limited capacity. By reducing the repetition of fluid ejection into the same void (by comparing a specified void with a previously specified void), the frequency with which the fluid reservoir needs to be refilled is reduced.

[0022] In some embodiments, the oral treatment device comprises a toothbrush.

[0023] According to one aspect of the present disclosure, there is provided a method of operating an oral treatment device for use in treating a user's oral cavity, the oral treatment device comprising an image sensor device operable to generate image data depicting at least a portion of the user's oral cavity and a control unit. The method includes, in the control unit, processing the generated image data to identify an interdental space between adjacent teeth in the user's oral cavity, comparing at least one characteristic of the identified interdental space with at least one characteristic of one or more interdental spaces previously identified in the user's oral cavity, and controlling the oral treatment device based on the result of the comparison to perform an action.

[0024] According to one aspect of the present disclosure, there is provided a computer program comprising a set of instructions that, when executed by a computer device, cause the computer device to execute a method of operating an oral treatment device for use in treating a user's oral cavity, the oral treatment device comprising an image sensor device operable to generate image data depicting the user's oral cavity. The method includes processing the generated image data to identify an interdental space between adjacent teeth in the user's oral cavity, comparing at least one characteristic of the identified interdental space with at least one characteristic of one or more interdental spaces previously identified in the user's oral cavity, and controlling the oral treatment device based on the result of the comparison to perform an action.

[0025] It should be understood that features described in connection with one aspect of the present invention can be incorporated into other aspects of the present invention. For example, the method of the present invention can incorporate any of the features described in connection with the apparatus of the present invention, and vice versa.

[0026] Next, embodiments of the present disclosure will be described by way of example only with reference to the accompanying drawings.

Brief Description of the Drawings

[0027]

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Modes for Carrying Out the Invention

[0028] Figures 1A and 1B show perspective views of an oral treatment device 100 according to various embodiments. Figure 1C shows a plan view of the oral treatment device 100. The oral treatment device 100 and / or its components can be used to perform the methods described herein. In the embodiments shown in Figures 1A - 1C, the oral treatment device 100 comprises a toothbrush. In various embodiments, the oral treatment device 100 comprises an electric toothbrush. In various embodiments, the device 100 comprises an ultrasonic toothbrush. In alternative embodiments, the oral treatment device 100 can comprise other types of devices. For example, the device 100 can comprise a flossing device, an oral irrigator, an interdental cleaning device, an oral care monitoring device, or any combination thereof. The oral care monitoring device is configured to monitor the health condition of the user's oral cavity and provide corresponding feedback to the user.

[0029] The oral treatment device 100 comprises a handle 110 and a head 120. The handle 110 forms the main body of the device 100 and can be gripped by a user during use of the device 100. In the embodiments shown in Figures 1A - 1C, the handle 110 includes a user interface 112. The user interface 112 comprises user-operable buttons configured to be depressible by a user when the user is holding the handle 110. In some embodiments, the handle 110 comprises a display (not shown) that can be positioned so as to be visible to the user during use of the oral treatment device 100.

[0030] In the embodiments shown in FIGS. 1A - 1C, the head 120 includes a plurality of bristles 122 for performing a toothbrushing function. In alternative embodiments, the head 120 does not include bristles. For example, in some other embodiments, the oral treatment device 100 includes a dedicated fluid delivery device for, e.g., cleaning the spaces between adjacent teeth and / or delivering a cleaning or whitening medium to the user's teeth. In the embodiments shown in FIGS. 1A - 1C, the oral treatment device 100 includes a stem 130 that connects the handle 110 to the head 120. The stem 130 is elongate in shape, which helps to space the head 120 from the handle 110 to enhance the user operability of the oral treatment device 100. The head 120 and / or the stem 130 may be removable from the handle 110.

[0031] The oral treatment device 100 includes a dental treatment system for treating the user's oral cavity. In the embodiments shown in FIGS. 1A - 1C, the dental treatment system includes a fluid delivery system, but it should be understood that in other embodiments, other types of dental and / or oral treatment systems may be used. The fluid delivery system is arranged to deliver the injection of the working fluid into the oral cavity. In various embodiments, the working fluid includes a liquid, e.g., water. In alternative embodiments, the working fluid includes a gas and / or a powder. The working fluid can be delivered into the interdental space between adjacent teeth to displace obstacles disposed within the space, such as food like a prosthesis or other preserved processed meat. The interdental space is the space or gap between two adjacent teeth and / or can be the area surrounding the contact point between adjacent teeth. The interdental space can be defined as the area bounded by a plane that is tangential to the lingual sides of two adjacent teeth and the area between the teeth.

[0032] Additionally or alternatively, the working fluid can be delivered to the user's gum line, e.g., for treating gum inflammation or infection. In alternative embodiments, the dental treatment system is configured to deliver a whitening fluid and / or remove plaque from the user's teeth.

[0033] In the embodiments shown in FIGS. 1A to 1C, the oral treatment device 100 includes a fluid reservoir 114 for storing the working fluid. The fluid reservoir 114 is disposed within the handle 110 of the oral treatment device 100. The fluid reservoir 114 forms part of the fluid delivery system of the device 100. In some embodiments, the fluid reservoir 114 is removable from the handle 110, for example, to facilitate replenishment of the working fluid.

[0034] In some embodiments, the oral treatment device 100 further includes a nozzle 124. This is shown in FIG. 1C. The nozzle 124 forms part of the fluid delivery system of the device 100. The nozzle 124 is disposed on the head 120 of the device 100. The nozzle 124 is configured to deliver the working fluid to the user's oral cavity during use of the oral treatment device 100. In the embodiments shown in FIGS. 1A to 1C, the bristles 122 are at least partially disposed around the nozzle 124. The nozzle 124 extends along the nozzle axis A shown in FIG. 1C. The nozzle axis A is substantially perpendicular to the longitudinal axis Z of the handle 110.

[0035] The nozzle 124 is configured to receive the working fluid from the fluid reservoir 114 and deliver the injection of the working fluid to the user's oral cavity during use of the device 100. In some embodiments, the tip of the nozzle 124 includes a fluid outlet through which the injection of the working fluid is delivered to the oral cavity. Each injection of the working fluid may have a volume of less than 1 milliliter, and in some cases, less than 0.5 milliliter. The nozzle 124 may further include a fluid inlet for receiving the working fluid from the fluid reservoir 114.

[0036] In various embodiments, the fluid delivery system includes a pump assembly (not shown) for taking working fluid from the fluid reservoir 114 into the nozzle 124. The pump assembly can be disposed within the handle 110. The pump assembly can include a pump (e.g., a positive displacement pump) and a drive mechanism for driving the pump. In various embodiments, the drive mechanism includes a pump motor. Power can be supplied to the pump motor by a battery (e.g., a rechargeable battery).

[0037] In various embodiments, the fluid delivery system includes a control circuit (not shown) for controlling the drive of the pump motor, and thus, the control circuit and the pump motor provide a drive mechanism for driving the pump. The control circuit can include a motor control unit for supplying power to the pump motor. As described in more detail below, the control circuit of the fluid delivery system can receive a signal from the control unit of the oral treatment device 100.

[0038] FIG. 2 shows a schematic block diagram of the oral treatment device 100 according to various embodiments.

[0039] The oral treatment device 100 includes a control unit 210. As will be described in more detail below, the control unit 210 is operable to perform various data processing and / or control functions according to the embodiments. The control unit 210 can include one or more components. The one or more components can be implemented in hardware and / or software. The one or more components can be arranged at the same location of the oral treatment device 100 or can be arranged remotely from each other. The control unit 210 can be embodied as one or more software functions and / or hardware modules. In the embodiments, the control unit 210 includes one or more processors 210a configured to process instructions and / or data. The operations performed by the one or more processors 210a can be realized by hardware and / or software. The control unit 210 can be used to execute the methods described herein. In the embodiments, the control unit 210 is operable to output control signals for controlling one or more components of the oral treatment device 100.

[0040] In various embodiments, the oral treatment device 100 includes a fluid delivery system 220. As described above with reference to FIGS. 1A-1C, the fluid delivery system 220 is operable to deliver the working fluid to the user's oral cavity. In various embodiments, the fluid delivery system 200 includes a nozzle for discharging the working fluid, such as the nozzle 124, and a fluid reservoir for storing the working fluid within the oral treatment device. The fluid delivery system 220 is operable to receive a control signal from the control unit 210, thereby enabling the control unit 210 to control the delivery of the working fluid by the fluid delivery system 220. For example, the control unit 210 can output a control signal received by the control circuit of the fluid delivery system 220, and by this control signal, the control circuit of the fluid delivery system 220 drives the pump motor, and the pump motor causes the working fluid to be pumped from the fluid reservoir to the nozzle and discharged into the user's oral cavity. Additionally or alternatively, the control unit 210 can output a control signal received by the control circuit of the fluid delivery system 220, and by this control signal, the control circuit of the fluid delivery system 220 prevents the working fluid from being delivered through the nozzle. In an alternative embodiment, the oral treatment device 100 does not include a fluid reservoir. That is, the working fluid may be delivered from outside the oral treatment device 100 (e.g., through a dedicated fluid delivery channel) so as to be discharged through the nozzle without being stored within the oral treatment device 100.

[0041] In various embodiments, the oral treatment 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, active pixel sensors such as charge-coupled device (CCD) and complementary metal-oxide-semiconductor (CMOS) sensors. In various embodiments, the image sensor device includes an intraoral image sensor device. For example, the image sensor device can include an intraoral camera. The intraoral image sensor device (e.g., the intraoral camera) is operable to be used at least partially inside the user's oral cavity to generate image data depicting the user's oral cavity. For example, the image sensor device 230 can be disposed at least partially on the head 120 of the oral treatment device 100, and the head 120 is arranged to be inserted into the user's oral cavity. In various embodiments, the image sensor device 230 includes one or more processors. The control unit 210 is operable to receive image data from the image sensor device 230. The oral treatment device 100 can be controlled using the image data output from the sensor device 230. In various embodiments, the control unit 210 is operable to control the image sensor device 230.

[0042] In the embodiment shown in FIG. 2, the oral treatment device 100 includes an IMU (inertial measurement unit) 240. In such an embodiment, the control unit 210 is operable to receive from the IMU 240 a signal indicating the position and / or movement of the oral treatment device 100. In various embodiments, 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 may constitute a nine-axis IMU. In an alternative embodiment, the IMU 240 includes an accelerometer and a gyroscope but does not include a magnetometer. In such an embodiment, the IMU 240 constitutes a six-axis IMU. Since the nine-axis IMU has a higher degree of freedom, it can generate more accurate measurement values than the six-axis IMU. However, depending on the situation, the six-axis IMU may be preferred over the nine-axis IMU. For example, some oral treatment devices may generate and / or be subject to magnetic interference during use. Heating, the magnetism and / or magnetic inductance of the device, and / or other magnetic interferences may affect the behavior of the magnetometer. Thus, in some cases, the six-axis IMU may be more reliable and / or accurate than the nine-axis IMU. The IMU 240 is configured to output data indicating accelerometer signals and gyroscope signals (and in some embodiments magnetometer signals). In various embodiments, the IMU 240 is disposed within the head 120 of the oral treatment device 100. In an alternative embodiment, the IMU 240 is disposed within the handle 110 of the oral treatment device 100. In various embodiments, the oral treatment device 100 includes a plurality of IMUs 140. For example, a first IMU 240 can be disposed within the head 120, and a second IMU 240 can be disposed within the handle 110.

[0043] In various embodiments, the oral treatment device 100 includes a contact member 245. As described in more detail below, the contact member 245 is operable to contact the user's teeth during use of the oral treatment device 100. The contact member 245 is disposed on the head 120 of the oral treatment device 100. For example, the contact member 245 can include a nozzle of the fluid delivery system 220, such as the nozzle 124 described above with reference to FIGS. 1A-1C.

[0044] In various embodiments, the oral treatment device 100 includes a user interface 250. The user interface 250 can be similar to the user interface 112 described above with reference to FIGS. 1A-1C. The user interface 250 can include, for example, an audio and / or visual interface. In various embodiments, the user interface 250 includes a display (e.g., a touch screen display). In various embodiments, the user interface 250 includes an audio output device such as a speaker. In various embodiments, the user interface 250 includes a tactile feedback generating device configured to provide tactile feedback to the user. The control unit 210 is operable to control the user interface 250 and is operable, for example, to provide an output for the user via the user interface 250. In some embodiments, the control unit 210 is operable to receive data based on user input, for example, via the user interface 250. For example, the user interface 250 can include one or more buttons and / or touch sensors.

[0045] The oral treatment device 100 further includes a memory 260. The memory 260 is operable to store various data according to embodiments. The memory can include at least one volatile memory, at least one non-volatile memory, and / or at least one data storage device. The volatile memory, non-volatile memory, and / or data storage device can be configured to store computer-readable information and / or instructions for use or execution by the control unit 210.

[0046] In alternative embodiments, the oral treatment device 100 can include more components, fewer components, and / or different components. In particular, at least some of the components of the oral treatment device 100 shown in FIGS. 1A-1C and / or FIG. 2 may be omitted according to embodiments (e.g., may not be required). For example, in some embodiments, at least one of the fluid delivery system 220, the image sensor device 230, the IMU 240, the user interface 250, and the memory 260 can be omitted. In embodiments, the oral treatment device 100 includes additional components (not shown), such as a power source such as a battery.

[0047] FIG. 3 shows a method 300 for operating an oral treatment device according to embodiments. The method 300 can be used to operate the oral treatment device 100 described above with reference to FIGS. 1A, 1B, and 2. In the embodiment of FIG. 3, the oral treatment device 100 includes an IMU 240 and a contact member 245 operable to contact the user's teeth during use of the oral treatment device 100. In embodiments, the method 300 is at least partially executed by the control unit 210.

[0048] In step 310, a signal indicating the vibration characteristics of the oral treatment device 100 during use of the oral treatment device 100 is received from the IMU 240. The vibration characteristics depend on the contact between the contact member 245 and the teeth. Thus, the vibration characteristics can be different (or have different values) depending on whether the contact member 245 is in contact with the teeth.

[0049] In step 320, the signal is processed to detect an adjacent interdental space between adjacent teeth in the user's oral cavity.

[0050] In step 330, during the use of the oral treatment device, the oral treatment device is controlled to perform a treatment on the detected adjacent interdental space.

[0051] Therefore, during the use of device 100 by the user, the adjacent interdental space can be automatically detected by the use of the contact member 245 and the IMU 240, and the implementation of the treatment can be correspondingly controlled. In this way, the user does not need to determine when device 100 is in a position suitable for the implementation of the treatment, for example, when it is close to or within the adjacent interdental space. Instead, such determination is automatically made by monitoring the vibration characteristics of device 100 that change in response to the contact between the contact member 245 and the teeth. By automatically detecting the adjacent interdental space and / or the position of device 100 relative to the adjacent interdental space during use, and using such information to control the implementation of the treatment at that time (i.e., during the same use period of device 100), the implementation of the treatment becomes more accurate.

[0052] The vibration characteristics are the characteristics of the vibration of device 100 during the use of device 100. For example, the vibration characteristics may be related to the frequency and / or amplitude of the vibration. When the contact member 245 is in contact with the teeth, the vibration of device 100 is more attenuated due to the aforementioned contact compared to when the contact member 245 is not in contact with the teeth, for example, when the contact member 245 is within or at the adjacent interdental space between adjacent teeth. By analyzing the IMU signal to determine how the vibration of device 100 is attenuated, it is possible to infer whether the contact member 245 is currently within or at the adjacent interdental space.

[0053] In various embodiments, for example, when the head 120 of the oral treatment device 100 includes a plurality of bristles 122, the contact member 245 is independent of the plurality of bristles 122. Thus, both the bristles 122 and the contact member 245 can contact the user's teeth during use of the device 100, but can contact individually. The contact member 245 can include, for example, a member having higher rigidity than the bristles 122. By using an independent contact member 245, the characteristics of the contact member 245 can be selected and / or adjusted such that the detection of adjacent interdental spaces is optimized. For example, it may be desirable to use a contact member 245 having a relatively high rigidity, for example, a rigidity higher than a predetermined threshold value, in order to cause an easily detectable change in the vibration characteristics measured when the contact member 245 moves in and out of the adjacent interdental space. In some embodiments, the bristles themselves may be insufficiently rigid to cause such an easily detectable change, and attempting to increase the rigidity of the bristles to obtain such an effect may compromise the brushing function of the bristles.

[0054] In various embodiments, for example, when the oral treatment device includes a fluid delivery system 220 that enables the delivery of a working fluid to the user's oral cavity, the contact member includes a nozzle, for example, the nozzle 124 described above with reference to FIGS. 1A - 1C. Thus, the nozzle can function both as a means for enabling the ejection of the working fluid toward the adjacent interdental space and as a contact member used for the automatic detection of the adjacent interdental space (and thereby triggering the ejection).

[0055] In some embodiments, the IMU 240 is included in the handle 110 of the device 100. By placing the IMU 240 within the handle 110 of the device 100 rather than within the head 120 of the device 100, the 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 if the IMU is incorporated into the head 120, unwanted architectural and / or structural changes to the head 120 may be required to accommodate the IMU 240. Further, in some embodiments, the head 120 of the device 100 is a disposable type separable from the handle 110, and in some cases it may be desirable for the user to periodically replace the head after use. Therefore, by placing the IMU 240 within the handle 110 rather than within the head 120, the cost of replacement parts is reduced.

[0056] In some embodiments, the IMU 240 is included in the head 120 of the device 100. Placing the IMU 240 within the head 120 of the device 100 allows for the generation of a more easily detectable signal (and thus a more accurate and / or reliable detection of the gap) because the IMU 240 is placed closer to the contact member 245 compared to when the IMU 240 is placed within the handle 110.

[0057] In various embodiments, for example, when the oral treatment device 100 includes a fluid delivery system 220, in response to detecting an adjacent interdental space, a control signal is output to the fluid delivery system 220 to control the delivery of the working fluid. In this way, the delivery of the working fluid during use of the device 100 is controlled in response to the automatic detection of adjacent interdental spaces (during the same period of use of the device 100) achieved using the contact member 245 and the IMU 240. This enables the use of a more accurate and / or reliable fluid delivery system 220. By improving the accuracy and / or reliability of the fluid delivery system 220, the amount of working fluid used is reduced and a more effective treatment is achieved more quickly. In various embodiments, a control signal is output to the fluid delivery system 220 to cause the fluid delivery system to deliver the working fluid to the adjacent interdental space. In this way, the ejection of the working fluid can be directly triggered in response to the detection of the adjacent interdental space performed by using the IMU 240 and the contact member 245. This improves the accuracy of the fluid ejection, for example, increasing the likelihood that the working fluid is actually ejected into the adjacent interdental space rather than elsewhere.

[0058] In various embodiments, the vibration characteristics indicate ultrasonic vibrations generated by the oral treatment device 100. The ultrasonic vibrations can be generated as part of the toothbrushing and / or plaque removal function of the device 100. In a plurality of other examples, the vibration characteristics indicate sonic 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, for example, the device 100. In this way, by leveraging the existing functions of the device 100, automatic detection of adjacent interdental spaces is realized and no separate vibration generating means is required.

[0059] In various embodiments, the received signal is processed to detect a change in the vibration characteristics of the oral treatment device 100. Based on the detected change, a determination is made as to whether the contact member 245 has moved into or out of the adjacent interdental space. Based on the above determination, the device 100 is controlled to perform an action.

[0060] In various embodiments, the received signal includes accelerometer data. In various embodiments, the vibration characteristics include one or more of the amplitude and frequency of the vibration of the oral treatment device. In various embodiments, the received signal is processed using one or more frequency filters to obtain a filtered signal. In various embodiments, the one or more frequency filters include a low-pass frequency filter. Such a low-pass frequency filter can be used to reduce noise from the received IMU signal. Such noise can result from, for example, vibrations of the device, defects during IMU manufacturing (e.g., variations between IMUs), etc. Reducing noise using one or more frequency filters increases the reliability and / or accuracy of gap detection, for example, by improving the signal-to-noise ratio. In various embodiments, by applying a moving average to the received IMU signal, signals corresponding to repetitive and / or regular rapid movements (e.g., the "scrubbing motion" of the device) can be removed, thereby enabling the detection of adjacent interproximal gaps even when the device is rapidly moved back and forth. In various embodiments, one or more amplitude thresholds are applied to the filtered signal to detect adjacent interproximal 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, as compared to the "raw" signal received from the IMU240. The filters and / or thresholds can be determined in advance and / or modified or calculated during use of the device 100 to improve the accuracy of gap detection.

[0061] Figure 4 shows a method 400 of operating an oral treatment device according to various embodiments. The oral treatment device 100 described above with reference to FIGS. 1A, 1B, and 2 can be operated using method 400. In the embodiment of FIG. 4, the oral treatment device 100 includes an image sensor device 230. In these embodiments, the image sensor device 230 includes an intraoral image sensor device. In various embodiments, method 400 is at least partially executed by the control unit 210.

[0062] In step 410, the intraoral image sensor device 230 generates image data depicting at least a portion of the user's oral cavity during use by the user of the oral treatment device 100.

[0063] In various embodiments, the intraoral image sensor device 230 is at least partially included in the head 120 of the oral treatment device 100. Since the head 120 of the device 100 is for performing a treatment inside the user's oral cavity, by at least partially disposing the intraoral image sensor device 230 within the head 120, imaging of the interior of the oral cavity is enabled without the need for a separate intraoral camera (i.e., a camera attached separately from the head 120).

[0064] In various embodiments, the intraoral image sensor device 230 is at least partially included in the handle 110 of the oral treatment device 100. Thus, even when a portion of the image sensor device 230, for example, the image sensor, is arranged to remain outside the user's oral cavity, the image sensor device 230 can still be referred to as an "intraoral image sensor device". By at least partially disposing the image sensor device 230 within the handle 110 of the device 100, the 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 if the image sensor device 230 is incorporated into the head 120, changes to the architecture and / or structure of the head 120 may be required, and such changes can be relatively complex and / or costly. Further, in various embodiments, the head 120 of the device 100 is a disposable type separable from the handle, and in some cases, it may be desirable for the user to regularly replace the head 120 after use. Therefore, by at least partially disposing the image sensor device 230 within the handle 110 instead of disposing the entire image sensor device 230 within the head 120, the cost of replacement parts is reduced.

[0065] In various embodiments, the intraoral image sensor device 230 includes a sensor and an opening for receiving light and delivering the light to the sensor. The opening is included in the head 120 of the oral treatment device 100. For example, if the head 120 of the device 100 includes a set of bristles 122 for performing a brushing function, for example, the opening can be disposed behind the bristles 122 such that the bristles 122 do not cover the opening (i.e., do not block the light from the opening). In various embodiments, the image sensor device 230 includes a guide channel for guiding the light from the opening to the image sensor. For example, if the oral treatment device 100 includes a head 120, a handle 110, and a stem 130 connecting the head 120 and the handle 110, the guide channel can extend from the opening to the sensor along (e.g., within) the stem 130. The guide channel can include, for example, an optical fiber cable. In an alternative embodiment, the stem 130 is hollow and is disposed to cover an image sensor disposed behind the head 120 of the device 100. This shortens the distance between the opening and the sensor while ensuring that the sensor is not included in the (disposable) head 120.

[0066] In various embodiments, the image data includes RGB (red, green, blue) image data. In alternative embodiments, other types of image data (e.g., black and white image data) can be used.

[0067] In step 420, the generated image data is processed to derive location data indicating the location of the adjacent interdental spaces between adjacent teeth in the user's oral cavity. The generated image data is processed using a trained classification algorithm configured to identify adjacent interdental spaces. The trained classification algorithm is trained prior to use of the oral treatment device.

[0068] In step 430, during use of the oral treatment device 100, the oral treatment device 100 is controlled to treat the detected adjacent interdental spaces.

[0069] Accordingly, during use of the device 100 by the user, the interproximal spaces can be automatically detected by use of the intraoral image sensor device 230 and the trained classification algorithm, and the performance of the treatment can be appropriately controlled without requiring user input. For example, the user does not need to determine when the device 100 is in a position suitable for the performance of the treatment, e.g., when it is close to or within the interproximal space. Instead, such determination is made automatically based on the intraoral image data and can be performed substantially in real time. Processing the intraoral image data using the trained classification algorithm enhances the accuracy and / or reliability of the detection and / or localization of the interproximal space as compared to cases where the intraoral image data is not processed using such a trained algorithm. By more accurately detecting the interproximal space and / or the position of the device 100 relative to the interproximal space during use and using such information to control the performance of the treatment at that time (i.e., during the same period of use of the device), the performance of the treatment becomes more accurate. Further, the use of the image data enables not only the detection of the space but also the localization of the space. Localizing the space enables the performance of a treatment with higher accuracy and / or reliability as compared to cases where the space is not localized.

[0070] In an embodiment where the oral treatment device 100 includes a fluid delivery system 220 that delivers a working fluid to the user's oral cavity, a control signal is output to the fluid delivery system 220 based on location data to control the delivery of the working fluid. In this way, the delivery of the working fluid during use of the device 100 is controlled in response to the automatic location identification of adjacent interdental spaces (during the same period of use of the device 100) achieved using the intraoral camera 250 and a trained classification algorithm. This enables the use of a fluid delivery system 220 with higher accuracy and / or reliability. In particular, the accuracy of fluid ejection, i.e., the likelihood that the working fluid is actually ejected into the adjacent interdental space rather than elsewhere, is increased. By improving the accuracy and / or reliability of the fluid delivery system 220, the amount of working fluid used is reduced and the treatment is achieved more quickly.

[0071] In embodiments, the generated image data is processed using a sliding window. In such embodiments, the location data is derived by detecting the presence of adjacent interdental spaces within the sliding window. In other words, the sliding window traverses the image, defining a partial region of the image, and a determination is made as to whether a gap exists within each partial region of the image. This will be described in more detail below.

[0072] In embodiments, the generated image data is processed by extracting one or more image features from the image data and using the one or more extracted image features to derive location data. The image features may include, for example, texture-based image features. Since one image consists of a plurality of highly correlated pixels, the extraction of image features is used to obtain the most representative and referenceable (i.e., non-redundant) information of the image in order to reduce the dimensionality and / or facilitate the learning of the classification algorithm.

[0073] In various embodiments, one or more image features are extracted using a discrete wavelet transform. The discrete wavelet transform can capture both frequency and location information within an image. The image frequency of the void region is typically higher than that of the tooth or gingival region. Thereby, the discrete wavelet transform can generate a frequency map of the image that can be used to detect adjacent interproximal spaces. In various embodiments, Haar wavelets are used, which have relatively low computational complexity and low memory usage compared to other wavelets. The coefficients (or approximations thereof) of the wavelet transform can be used as the extracted image features. For example, the output of feature extraction based on Haar wavelets applied to an image of size a×a can 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). In alternative embodiments, other wavelets can be used.

[0074] The extracted features can be used for a sliding window applied to the image. For example, in a sub-region of the image defined by the sliding window, after performing 2×2 pooling for each of h, v, and d, h, v, and d can be vectorized and combined into one vector of size 1×108. The resulting result can be normalized together with the trained data from the trained classification algorithm, for example, the trained mean and variance values. A support-vector machine (SVM) can be used as a non-probabilistic non-linear binary classifier with a Gaussian radial basis function kernel that receives the data normalized from the previous stage. The trained SVM has trained coefficients and biases, that is, it includes the support vectors derived during the previous training stage. For example, when applying ground truth labeling to a set of images, the classification algorithm can be trained to assign new examples to one category (e.g., void) or another category (e.g., non-void).

[0075] In various embodiments, one or more image features are extracted using at least one of an edge detector, a corner detector, and a blob extractor. By extracting image features using such a method, more accurate detection and / or localization of adjacent interdental spaces can be provided compared to other methods.

[0076] In various embodiments, for example, when the oral treatment device 100 includes a user interface, the user interface provides an output according to the location data. For example, the output can notify the user that an adjacent interdental space has been discovered, indicate the location of the adjacent interdental space, inform the user that a treatment has been performed on the adjacent interdental space, and / or include a notification that guides the user to adjust the position and / or orientation of the device so that a more accurate treatment can be performed (e.g., ejection of the working fluid). The provided output can include, for example, a visual output, an audio output, and / or a tactile output.

[0077] In various embodiments, for example, when the oral treatment device 100 includes a memory 260, one or more characteristics of the adjacent interdental space are stored in the memory 260 for use in subsequent processing and / or control of the oral treatment device 100. For example, the stored one or more characteristics can be used to compare an adjacent interdental space with a subsequently identified adjacent interdental space. In other cases, the stored one or more characteristics are used to track the adjacent interdental space over time.

[0078] FIG. 5 shows a method 500 for operating an oral treatment device according to various embodiments. The method 500 can be used to operate the oral treatment device 100 described above with reference to FIGS. 1A, 1B, and 2. In the embodiment of FIG. 5, the oral treatment device 100 includes an image sensor device 240. In various embodiments, the method 500 is at least partially executed by the control unit 210.

[0079] In step 510, image data is generated by the image sensor device 240. The image data represents an image sequence depicting at least a part of the user's oral cavity. Thus, images of a part of the oral cavity can be captured at a plurality of different time points.

[0080] In step 520, the image data is processed to derive movement parameters. The movement parameters indicate the movement of the oral treatment device 100 relative to the interdental spaces between adjacent teeth within the user's oral cavity.

[0081] In step 530, the oral treatment device 100 is controlled based on the derived movement parameters to execute an action.

[0082] By deriving movement parameters indicating the movement of the oral treatment device relative to the interdental spaces, finer and / or more intelligent control of the device 100 becomes possible. In particular, by considering the movement of the device 100 relative to the spaces (or vice versa), the treatment can be applied to the spaces more accurately and / or effectively.

[0083] In various embodiments, the oral treatment device is controlled based on the derived movement parameters to perform a treatment on the interdental spaces. Thus, the action executed in step 530 may include performing a treatment on the interdental spaces.

[0084] In various embodiments, the performance of the treatment by the oral treatment device 100 is stopped based on the derived movement parameters. Thus, the action executed in step 530 may include stopping the performance of the treatment on the interdental spaces.

[0085] In various embodiments, the derived movement parameters indicate the predicted position of the adjacent interproximal space relative to the oral treatment device 100 at a predetermined future time point. The predetermined future time point can be the earliest time point at which the implementation of the treatment can be initiated. By predicting the position of the space at such a predetermined future time point, it is possible to determine the likelihood that a desired (e.g., accurate) treatment will be performed on the space. If it is determined that such a likelihood is high, for example, if it is determined to be higher than a predetermined threshold, the implementation of the treatment can be permitted. On the other hand, if it is determined that such a likelihood is low, for example, if it is determined to be lower than a predetermined threshold, the implementation of the treatment can be stopped. Thereby, the implementation of the treatment is triggered only when it is determined based on the movement parameters that the likelihood of the space being treated accurately and / or effectively is sufficiently high, enabling more efficient use of the device 100.

[0086] In various embodiments, the derived movement parameters indicate a future time point at which the adjacent interproximal space is predicted to be at a predetermined position relative to the oral treatment device 100. The predetermined position can be, for example, a position within the path of the jet of the working fluid from the fluid delivery system. Thus, by controlling (e.g., delaying) the implementation of the treatment based on the derived movement parameters, it is possible to increase the likelihood that a desired accurate treatment of the adjacent interproximal space will be performed. Thereby, more efficient use of the oral treatment device 100 is possible.

[0087] In various embodiments, the derived movement parameters indicate the velocity and / or acceleration of the oral treatment device 100 relative to the adjacent interproximal space. The derived velocity and / or acceleration can be used to track the trajectory of the space relative to the device 100, thereby increasing the accuracy of the implementation of the treatment.

[0088] In an embodiment where the oral treatment device 100 includes a fluid delivery system 220 that delivers a working fluid to the user's oral cavity, a control signal is output to the fluid delivery system 220 based on the derived movement parameters to control the delivery of the working fluid. Thus, the action performed at item 530 may include controlling the fluid delivery system 220. In this way, the delivery of the working fluid during use of the device is controlled based on the movement of the device relative to the derived voids (during the same period of use of the device). This enables the use of a fluid delivery system with higher accuracy and / or reliability. In particular, the accuracy of fluid ejection, i.e., the likelihood that the working fluid is actually ejected into the adjacent interdental space rather than elsewhere, is increased. For example, there may be a given latency from the time an adjacent interdental space is detected until the time the working fluid can be delivered to the void. Such latency may be due to data processing, signal transmission between different components and / or devices, the operation of the fluid delivery system 220, etc. Such a delay means that at the time the fluid delivery system ejects the working fluid, the detected void may no longer be in the path of the ejected fluid. However, by considering the movement of the device 100 relative to the voids, such movement can be corrected, thereby increasing the accuracy of fluid ejection. For example, the ejection can be delayed until the void enters the path of the working fluid. By improving the accuracy and / or reliability of the fluid delivery system 220, the amount of working fluid used is reduced, and a more effective treatment is achieved more quickly.

[0089] In various embodiments, the image sensor device 230 is at least partially included in the head 120 of the oral treatment device 100. Since the head 120 of the device 100 is for treating the interior of the user's oral cavity, by at least partially disposing the image sensor device 230 within the head 120, imaging of the interior of the oral cavity is enabled without the need for a separate camera (i.e., a camera attached separately from the head 120).

[0090] In various embodiments, the image sensor device 230 is at least partially included in the handle 110 of the oral treatment device 100. By disposing the image sensor device 230 at least partially within the handle 110 of the device 100, as described above, the space on the device can be more efficiently managed and the cost of replacement parts (i.e., the head 120) can be reduced.

[0091] In various embodiments, the image sensor device 230 comprises an intraoral camera. The intraoral camera is operable to capture digital images from within the user's mouth. Such images are then processed to track the movement of the device relative to the adjacent interproximal spaces or vice versa. In this way, the interior of the user's oral cavity is imaged during use of the device 100. In some cases, the intraoral camera is operable to generate video data.

[0092] In various embodiments, the image data is processed to detect adjacent interproximal spaces. Thus, first, the image data is processed to detect the spaces, and second, the trajectory of the spaces relative to the device 100 is dynamically tracked. For example, a space can be detected in a first image of an image sequence, and subsequent images in the image sequence can be used to track the movement of the space, e.g., as indicated by movement parameters.

[0093] In various embodiments, the interproximal spaces are tracked between frames by comparing the movement and / or displacement of image pixels between frames. For example, pixel I(x,y,t) of a first frame in a sequence is compared with pixel I(x+dx,y+dy,t+dt) of a second frame in the sequence to derive the movement between the frames, i.e., to determine that the pixel has moved by (dx,dy) over time dt. The location of the space can be predicted based on the displacement calculated from the first and second frames (i.e., the current frame and one or more previous frames). Since the teeth are rigid objects, the pixels in the space region have a similar displacement as the pixels in the tooth region between two frames. Thus, the space can be tracked even if the space itself does not exist in one or more of the images. The optical flow method can be used to estimate the velocity (pixels / second) of the space with respect to device 100, and based on the velocity and the known time between frames, the location of the space at a given future time point can be predicted.

[0094] In various embodiments, the interproximal spaces do not exist in at least one image of the image sequence. In such embodiments, for at least one image of the image sequence, the location of the interproximal spaces is estimated based on the location of the interproximal spaces in at least one other image of the image sequence. Thus, the trajectory of the space can be tracked even if the space does not exist (i.e., is not visible) in the image. For example, depending on the image, the space may be hidden behind other objects and not visible. In various embodiments, the optical flow method is used to derive the velocity of pixels and / or objects between images in the sequence. Then, the location of the space in a first image where the space itself does not exist can be estimated based on the calculated velocity, the location of the space in a second image, and the time between the first and second images.

[0095] In various embodiments, the movement parameters are derived according to signals output by the IMU. For example, when the oral treatment device 100 includes the IMU 240, the IMU 240 can be configured to output signals indicating the position and / or movement of the oral treatment device 100 relative to the user's oral cavity. For example, the angular movement of the device 100 relative to the gap can be derived using the IMU 240. Such signals can be used in combination with the image data in the derivation of the movement parameters.

[0096] FIG. 6 shows a method 600 for operating an oral treatment device according to various embodiments. The oral treatment device 100 described above with reference to FIGS. 1A, 1B, and 2 can be operated using the method 600. In the embodiment shown in FIG. 6, the oral treatment device 100 includes an image sensor device 230. The image sensor device 230 is operable to generate image data depicting at least a portion of the user's oral cavity. In various embodiments, the method 600 is at least partially executed by the control unit 210.

[0097] In step 610, the generated image data is processed to identify adjacent interdental spaces between adjacent teeth in the user's oral cavity.

[0098] In step 620, at least one characteristic of the identified interproximal space is compared with at least one characteristic of one or more interproximal spaces previously identified in the user's oral cavity. In embodiments, at least one characteristic of the identified space includes features that are expected to vary between different spaces and / or features that are unique to the identified space. Thus, at least one characteristic can be used to distinguish between spaces. The at least one characteristic can include visual characteristics. In embodiments, at least one characteristic of the identified interproximal space indicates at least one of the shape of the identified interproximal space, the appearance of the identified interproximal space, the position of the identified interproximal space, or any unique feature associated with the identified interproximal space. In embodiments, at least one characteristic of the identified space indicates frequency characteristics based, for example, on a wavelet transform applied to an image of the identified space.

[0099] In step 630, the oral treatment device 100 is controlled to perform an action based on the result of the comparison.

[0100] By comparing the characteristics of the identified interproximal space with the characteristics of one or more interproximal spaces of the user previously identified, the device 100 is controlled in a more intelligent and / or more flexible manner. In particular, a determination can be made as to whether the identified space has been previously identified during the current oral treatment session (i.e., during use of the device 100 by the user). Such a determination can be made substantially in real time, enabling rapid and responsive control of the device 100. Thus, previously identified spaces can be re-identified even if the imaging conditions have changed from a previous point in time.

[0101] In various embodiments, newly identified voids are processed in a different manner than previously identified voids. That is, the device 100 can be controlled by a first method if the identified void is determined to be a newly identified void, and can be controlled by a different second method if the identified void is determined to be a previously identified void (or similar to a previously identified void). Depending on the mode of operation of the device 100 by the user, the frequency of encountering a given void can be once or multiple times during an oral treatment session. Thus, by processing newly identified voids in a manner different from previously identified voids, the device 100 can adapt to the user's behavior.

[0102] In various embodiments, a similarity metric is calculated based on the result of the comparison. The similarity metric indicates the level of similarity between the identified interproximal void and one or more previously identified interproximal voids. In such embodiments, the oral treatment device 100 is controlled based on the derived similarity metric. The similarity metric can indicate whether the identified void is the same as or different from one or more previously identified voids. That is, the similarity metric can indicate whether the identified void is a newly identified void or a previously identified void. A void can be "newly identified" if it is determined not to have been encountered during the current oral treatment session. That is, even if a void may have been identified during a previous oral treatment session, it can still be designated as a newly identified void if it has not been encountered during the current session. In various embodiments, the similarity metric is compared to a threshold. If the similarity metric is lower than the threshold, the void is designated as a newly identified void. If the similarity metric is higher than the threshold, the void is designated as a previously identified void.

[0103] In various embodiments, in response to an indication by a similarity metric that a particular interproximal space is different from one or more previously identified interproximal spaces, device 100 is controlled to treat the particular interproximal space. Thus, the action performed at item 630 may include performing a treatment on the identified space. As such, if the identified space is determined to be a newly identified space, performance of the treatment is triggered.

[0104] In various embodiments, in response to an indication by a similarity metric that a particular interproximal space is different from one or more previously identified interproximal spaces, the image data depicting the particular interproximal space is stored in memory, for example, for use in subsequent identification and / or comparison of interproximal spaces. Thus, by comparing the space with subsequently identified spaces, it can be determined whether the subsequently identified space has been encountered in the past. In various embodiments, the image data is stored in a library or data bank that includes image data corresponding to previously identified spaces of the user and / or other representative data. The image data may be stored in device 100 or output for transmission to a remote device, for example, for storage via a network.

[0105] In various embodiments, in response to the similarity index indicating that a particular interproximal space is the same as at least one of one or more previously identified interproximal spaces, the oral treatment device 100 is controlled to cease performing treatment on the particular interproximal space. Thus, the action performed at item 630 may include ceasing the performance of treatment. In this way, repeated treatment of the same space during a single oral treatment session can be reduced and, in some cases, completely avoided. In other words, each space is treated only once during an oral treatment session. This enables more efficient use of the oral treatment device 100. In an example where the treatment includes delivery of a working fluid via, for example, the fluid delivery system 220, reducing repeated treatment of the same space reduces the amount of working fluid used. In an alternative embodiment, in response to the similarity index indicating that a particular space is the same as at least one of one or more previously identified spaces, the performance of treatment is not ceased.

[0106] In various embodiments, in response to the similarity index indicating that a particular interproximal space is the same as at least one of one or more previously identified interproximal spaces, the elapsed time since at least one of one or more previously identified interproximal spaces was identified in the past is derived. The derived elapsed time is compared to a predetermined threshold. In such embodiments, the oral treatment device 100 is controlled based on the result of the comparison between the derived elapsed time and the predetermined threshold. In this way, the control of the device 100 can vary depending on the length of the elapsed time since the space was previously identified.

[0107] In various embodiments, the oral treatment device 100 is controlled to treat a specified adjacent interdental space in response to the derived elapsed time being longer than a predetermined threshold. Thus, when a predetermined length of time has elapsed since the treatment of a past space, repeated treatment of the space can be performed. In various embodiments, the oral treatment device 100 is controlled to cease performing treatment on a specified adjacent interdental space in response to the derived elapsed time being shorter than a predetermined threshold. Thus, when a predetermined length of time has not elapsed since the treatment of a past space, repeated treatment of the space is not performed. For example, when the user moves the device 100 back and forth in a "scrubbing" motion, the same space may be encountered twice in relatively quick succession. In this case, treating the space multiple times may not be effective and / or efficient. However, if the user returns the device 100 to a previously treated space significantly later during a session, it can be inferred that further treatment of the aforementioned space is desired, for example, because the treatment of the past space was not successful.

[0108] In various embodiments, the generated image data is processed using a trained classification algorithm configured to detect adjacent interdental spaces. Using such a trained algorithm results in a more accurate and / or reliable detection of spaces compared to when a trained algorithm is not used. In various embodiments, the classification algorithm comprises a machine learning algorithm. Such a machine learning algorithm can be improved by experience and / or training (e.g., the accuracy and / or reliability of classification can be increased).

[0109] In various embodiments, the generated image data is processed to derive at least one characteristic of the identified adjacent interproximal spaces. In various embodiments, the at least one characteristic is derived by processing the generated image data using a machine learning algorithm. The machine learning algorithm is trained to identify information used in distinguishing between adjacent interproximal spaces. Such information includes features representative of the spaces, i.e., non-redundant features and / or features predicted to be different for each space. The identified information may include at least one characteristic of the spaces. In various embodiments, such a machine learning algorithm (or one or more different machine learning algorithms) is also used to derive at least one characteristic of one or more spaces identified in the past, e.g., features representative of the spaces identified in the past and / or features usable in distinguishing between the spaces, which are used in comparing the spaces identified in the past with the currently identified spaces. In an alternative embodiment, features specific to the spaces are extracted from the raw image data without using a machine learning algorithm.

[0110] In various embodiments, the image sensor device 230 comprises an intraoral camera. In various embodiments, the image sensor device 230 is at least partially included in the head 120 of the oral treatment device 100. Since the head 120 of the device 110 is for performing a treatment inside the user's oral cavity, disposing the image sensor device 230 at least partially within the head 120 enables imaging of the inside of the oral cavity without the need for a separate camera.

[0111] In various embodiments, the image sensor device 230 is at least partially included in the handle 110 of the oral treatment device 100. By disposing the image sensor device 230 at least partially within the handle 110 of the device 100, as described above, the space on the device can be managed more efficiently and the cost of replacement parts (i.e., the head 120) can be reduced.

[0112] In an embodiment where the oral treatment device comprises a fluid delivery system 220 that delivers a working fluid to the user's oral cavity, a control signal is output to the fluid delivery system 220 based on the result of the determined comparison to control the delivery of the working fluid. Thus, the action performed at item 630 may include controlling the delivery of the working fluid (e.g., performing and / or stopping the delivery of the working fluid). In embodiments, the fluid delivery system 220 comprises a fluid reservoir for storing the working fluid within the oral treatment device 100. Accordingly, the frequency with which the fluid reservoir needs to be refilled can be reduced by comparing the identified voids with the previously identified voids, thereby reducing the repetition of the ejection of fluid into the same void.

[0113] FIG. 7 shows a method 700 for operating an oral treatment device according to embodiments. The method 700 can be used to operate the oral treatment device 100 described above with reference to FIGS. 1A, 1B, and 2. In the embodiment of FIG. 7, the oral treatment device 100 comprises an IMU 240. The IMU 240 is operable to output signals corresponding to the position and / or movement of the oral treatment device 100. In these embodiments, the oral treatment device 100 further comprises a fluid delivery system 220 that delivers a working fluid to the user's oral cavity. In embodiments, the method 700 is at least partially executed by the control unit 210.

[0114] In step 710, a signal received from the IMU 240 indicating the position and / or movement of the oral treatment device 100 relative to the user's oral cavity is processed.

[0115] In step 720, based on the processing of step 710, a control signal is output to the fluid delivery system 220 to control the delivery of the working fluid.

[0116] Accordingly, the delivery of the working fluid by the fluid delivery system 220 is controlled based on the IMU signal. Thereby, the accuracy of fluid delivery, such as the ejection of the working fluid, can be improved as compared to the case where the IMU signal is not used to control the fluid delivery system 220.

[0117] In various embodiments, the control signal is operable to cause the fluid delivery system 220 to stop delivering the working fluid. By selectively stopping the delivery of the working fluid based on the IMU signal, the amount of the working fluid used is reduced as compared to the case where the delivery is not selectively stopped. Thus, the efficiency of the device 100 is improved.

[0118] In various embodiments, the signal received from the IMU is processed to determine whether the oral treatment device is being moved according to a predetermined movement pattern. In response to the determination, a control signal is output to the fluid delivery system 220 to stop the delivery of the working fluid. Accordingly, the delivery of the working fluid to the user's oral cavity is selectively stopped based on the movement pattern of the device 100 by the user. Thereby, for example, by preventing the ejection of the working fluid when the device 100 is moved in a specific manner, more efficient use of the device 100 and / or more effective treatment becomes possible. For example, when the device 100 is being moved according to a predetermined movement pattern, the possibility of poor ejection of the fluid delivery system 220 and / or the possibility of damage caused by the ejection of the fluid may increase. In various embodiments, the signal received from the IMU 240 is processed using a trained classification algorithm, such as a machine learning algorithm, configured to determine whether the device 100 is being moved according to a predetermined movement pattern.

[0119] In various embodiments, the movement of the oral treatment device 100 according to a predetermined movement method inhibits the use of the oral treatment device 100 when treating the user's oral cavity. Therefore, when the device 100 is being used in a manner that inhibits the use of the device 100 when treating the oral cavity, fluid delivery can be selectively stopped. When the device is being moved in such a way, for example, the accuracy of the fluid delivery system 220 when delivering the working fluid to the target is reduced, and the possibility of performing the desired treatment is decreased. This means that, for example, although the working fluid is ejected by the fluid delivery system 220, the desired treatment is not performed, which increases the likelihood of waste of the working fluid. By selectively stopping fluid delivery when moving the device 100 according to a predetermined movement method, the working fluid is used more efficiently.

[0120] In various embodiments, the predetermined movement method includes a scrubbing movement. When moving the device 100 according to the scrubbing movement method, the accuracy of the fluid delivery system 220 when delivering the working fluid to the target, for example, an adjacent interdental space, is reduced, and the possibility of poor ejection increases. This means that the working fluid is more likely to be wasted. Therefore, by selectively stopping fluid delivery when moving the device 100 in a scrubbing motion, the working fluid is used more efficiently. In alternative embodiments, the predetermined movement method includes other movement methods.

[0121] In various embodiments, the signal received from the IMU 240 is processed to determine the orientation of the oral treatment device 100. A control signal is output to the fluid delivery system 220 based on the determined orientation. Thus, the fluid delivery system 220 can be controlled based on the current orientation of the device 100 determined using the IMU signal. The likelihood that the fluid delivery system 220 provides a desired treatment may depend on the orientation of the device 100. For example, when the working fluid is to be ejected into the interdental space between adjacent teeth to push aside an obstacle, the treatment is more likely to succeed (with fewer attempts) when the device 100 is oriented such that the nozzle of the fluid delivery system 220 extends substantially perpendicular to and faces the buccal or lingual surface of the tooth. On the other hand, when the device 100 is oriented such that the nozzle extends substantially perpendicular to and faces the occlusal surface of the tooth, the success rate of pushing aside the obstacle decreases. This means that the working fluid is more likely to be wasted, for example, because the desired treatment is not performed even when the working fluid is ejected from the fluid delivery system 220. By controlling fluid delivery based on the determined orientation of the device 100, the working fluid is used more efficiently.

[0122] In various embodiments, the orientation of the device 100 is compared to an ejection angle threshold. The ejection angle threshold is a threshold for determining whether to stop or permit the delivery of the working fluid based on the orientation of the head 120 of the device 100. For example, fluid delivery can be permitted when the orientation of the head 120 is higher than the ejection angle threshold, and fluid delivery can be stopped when the orientation of the head 120 is lower than the ejection angle threshold. In various embodiments, the ejection angle threshold can be determined for the user based on the IMU signal. The ejection angle threshold can be optimized for a particular user by analyzing the orientation of the head 120 when the user moves the device 100 along the dental arch. This is because the orientation and / or direction of movement of the device 100 along the path can vary from user to user. As used herein, "path" refers to the movement of the head 120 of the device 100 along the dental arch.

[0123] In various embodiments, the signals received from the IMU 240 are processed to derive changes in the orientation of the oral treatment device 100 during use of the oral treatment device 100. The control signal is output to the fluid delivery system 220 based on the derived changes in the orientation of the oral treatment device 100. In this way, fluid delivery can be controlled in response to changes in the orientation of the device 100 during use. For example, the device 100 can be moved from a first orientation where the desired treatment is relatively unlikely to occur, e.g., a location where the nozzle is oriented substantially perpendicular to and facing the occlusal surface of the tooth, to a second orientation where the desired treatment is relatively likely to occur, e.g., a location where the nozzle is oriented substantially perpendicular to and facing the lingual or buccal surface of the tooth. When the device 100 is in the first orientation, fluid delivery can be stopped to reduce the amount of working fluid used by ejecting the working fluid at a location where the desired treatment is relatively unlikely to occur. When the device 100 moves to the second orientation, the stop of fluid delivery can be aborted. Similarly, when the device 100 moves from the second orientation to the first orientation, fluid delivery can be selectively stopped.

[0124] In various embodiments, the head 120 of the device 100 is operable to move along the dental arch between a first end of the dental arch and a second end of the dental arch, and the fluid delivery system 220 is at least partially included in the head 120. In various embodiments, the signals received from the IMU 240 are processed to derive the trajectory of the head 120 of the oral treatment device 100 between the first end of the dental arch and the second end of the dental arch. The control signal is output to the fluid delivery system 220 based on the derived trajectory. By controlling the fluid delivery system 220 based on the trajectory of the head 120 as it moves along the dental arch, the device 100 can be controlled in a more intelligent and / or more degrees-of-freedom manner. In particular, if the trajectory indicates that the desired treatment is relatively unlikely to be performed using the fluid delivery system 220, fluid delivery can be stopped (thereby preventing waste of the working fluid).

[0125] In various embodiments, the signals received from the IMU 240 are processed to derive a change in the orientation of the head 120 of the oral treatment device 100 during movement of the head 120 of the oral treatment device 100 between a first end of the dental arch and a second end of the dental arch. A control signal is output to the fluid delivery system 220 based on the derived change in the orientation of the head 120. Thus, fluid delivery can be controlled in response to a change in the orientation of the head 120 when moving the head 120 along the dental arch. For example, the orientation of the head 120 can change when the user moves the device 100 along the dental arch, for example, the user can rotate the device 100 when moving the device 100 along the dental arch. By taking into account such changes in orientation, the fluid delivery system 220 can deliver a jet of working fluid, for example, when it is determined that there is a relatively high likelihood that a desired treatment will be performed based on the orientation, and stop the jet when it is determined that there is a relatively low likelihood that the desired treatment will be performed, thereby becoming more accurate and / or efficient.

[0126] In various embodiments, the signals received from the IMU 240 are processed to determine that the movement of the oral treatment device 100 with respect to the oral cavity has been stopped. In response to the determination, a control signal is output to the fluid delivery system 220, and the fluid delivery system 220 delivers the working fluid. Thus, the user can move the device 100 along the dental arch and can pause the device 100 when the device 100 is adjacent to an interproximal space between adjacent teeth that the user wishes to treat. By using the IMU signal to detect such a pause and automatically trigger the fluid delivery system 220 accordingly, the need for user input to trigger the fluid delivery system 220 is reduced, thereby enhancing the functionality of the device 100 and improving the user experience.

[0127] In various embodiments, the signals received from the IMU 240 are processed to detect adjacent interdental spaces between adjacent teeth in the user's oral cavity. In response to detecting an adjacent interdental space, a control signal is output to the fluid delivery system 220. In various embodiments, the control signal is output to the fluid delivery system 220 to cause the fluid delivery system to deliver an actuating fluid to the detected adjacent interdental space. Thus, the adjacent interdental spaces can be automatically detected based on the IMU signals substantially in real time during use of the device 100, and an actuating fluid can be delivered to the detected spaces during use of the device 100. In some cases, the user may not be aware of the presence of a particular space, but the space can still be detected by the device based on the IMU signals. Further, the efficiency and / or accuracy of the fluid delivery system 220 is enhanced by precisely triggering the ejection of the actuating fluid when a space is detected.

[0128] In various embodiments, a velocity and / or position estimation algorithm is used to process the IMU signals. For example, the velocity and / or position estimation algorithm can be configured to estimate the velocity of the device 100 for use in detecting a rapidly changing velocity in any direction (e.g., for detecting a scrubbing motion). In various embodiments, the velocity and / or position estimation algorithm is configured to be supplied with accelerometer signals and gyroscope signals from the IMU. These signals can be processed separately or combined into one data stream for use by the algorithm. For example, determining that the device is moving along the dental arch, determining the position of the device relative to the oral cavity, and / or deriving the velocity of the device can be performed using the velocity and / or position estimation algorithm. The velocity and / or position estimation algorithm can be implemented using software or hardware, such as an application specific integrated circuit (ASIC), or a combination of hardware and software. The velocity and / or position estimation algorithm can be used in the various methods described herein.

[0129] If not properly corrected, an IMU may be accompanied by noise, bias, and / or drift that can cause errors in the resulting calculation results. For example, gyroscope signals can drift over time, accelerometers can be biased by gravity, and both gyroscope signals and accelerometer signals can be accompanied by noise. In various embodiments, filtering, such as high and / or low-pass filters and / or median filters, is used to remove at least a portion of the noise in the IMU signals. In various embodiments, filters are used to correct the drift of the gyroscope and / or compensate for gravity, whereby the linear velocity can be obtained, and then the velocity can be integrated to obtain the position and / or displacement. The measured values of velocity and / or position can be individually configured for all three axes, or the direction components can be synthesized to obtain the magnitude of the velocity and / or the magnitude of the position.

[0130] In various embodiments, the IMU signals are processed to generate a user behavior profile for the user. Such a profile indicates the usage pattern, e.g., a routine, of the device 100 by the user based on movement, orientation, speed, etc. The user behavior profile can be used, for example, to provide the user with individually tailored advice. The user behavior profile can be modified and / or updated when new IMU data is obtained.

[0131] In various embodiments, the IMU signals are combined with intraoral image data generated by an image sensor device, such as the above-mentioned image sensor device 230. By using both the IMU signals 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.

[0132] Figure 8 shows a method 800 for operating an oral treatment device according to various embodiments. The method 800 can be used to operate the oral treatment device 100 described above with reference to FIGS. 1A, 1B, and 2. In the embodiment of FIG. 8, the oral treatment device 100 includes a head 120 that is used for treating a user's oral cavity. The oral cavity includes a plurality of oral zones. In these embodiments, the oral treatment device 100 includes an IMU 240. The IMU 240 is operable to output a signal in response to the position and / or movement of the head 120 of the oral treatment device 100. In various embodiments, the method 800 is at least partially executed by the control unit 210.

[0133] In step 810, a signal indicating the position and / or movement of the head 120 of the oral treatment device 100 with respect to the user's oral cavity is received from the IMU 240.

[0134] In step 820, the received signal is processed using a trained non-linear classification algorithm to obtain classification data. The classification algorithm is trained to identify the oral zone in which the head 120 of the oral treatment device 100 is placed from a plurality of oral zones. The obtained classification data indicates the oral zone in which the head 120 of the oral treatment device 100 is placed.

[0135] In step 830, the classification data is used to control the oral treatment device 100 to execute an action.

[0136] In various embodiments, the plurality of oral zones includes three or more oral zones. In various embodiments, the plurality of oral zones includes five or more oral zones. In various embodiments, the plurality of oral zones includes twelve oral zones. In various embodiments, the plurality of oral zones includes eighteen oral zones.

[0137] In various embodiments, a given oral zone of the plurality of oral zones represents a quadrant or sextant of the user's oral cavity and a tooth surface selected from a list including the buccal tooth surface, the lingual tooth surface, and the occlusal tooth surface. Thus, there can be 18 distinct oral zones corresponding to six oral cavities each having three tooth surfaces. In alternative embodiments, the plurality of oral zones includes 19 or more oral zones.

[0138] By using the IMU signal as an input to a trained non-linear classification algorithm, the oral zone in which the head 120 is disposed can be identified without requiring user input. Thus, the device 100 can autonomously identify the usage mode of the device 100 by the user and adapt accordingly. For example, one or more operating settings of the device 100 can be controlled based on the identified oral zone. This further enables the device 100 to notify the user about where the head 120 is in the oral cavity, how much time is spent in each oral zone, etc. This information can also be used to determine whether the head 120 has reached a particular oral zone during the current oral treatment session. In addition to providing direct user feedback, such information can facilitate the generation of a behavior profile indicating the usage tendency of the device 100 by the user, based on information such as the time spent in each oral zone, the presence or absence of overlooked oral zones, etc. Further, using a trained algorithm results in a more accurate and / or reliable localization of the head 120 compared to the case where a trained algorithm is not used. That is, the spatial resolution of the head 120 localization is enhanced by the use of a trained algorithm. Further, a non-linear classification algorithm can be used to distinguish factors that are not linearly separable. Thus, obtaining classification data using a non-linear classification algorithm results in a more accurate and / or reliable derivation of classification data.

[0139] In various embodiments, the classification algorithm comprises a machine learning algorithm. Such a machine learning algorithm can be improved by experience and / or training (e.g., the accuracy and / or reliability of classification can be increased).

[0140] In various embodiments, the oral treatment device comprises a machine learning agent. The machine learning agent comprises a classification algorithm. Thus, the classification algorithm can be arranged in the oral treatment device 100. By performing the identification of the oral zone on the device 100, transmission of data to another device and / or reception of data from another device are not required, so the latency is reduced as compared with the case where the classification algorithm is not arranged in the device 100. Thereby, quicker identification of the oral zone becomes possible, and the time required to take some corrective action and / or the time required to provide an output via the user interface can be shortened. In an alternative embodiment, the classification algorithm is arranged on a remote device. Such a remote device may have, for example, more processing resources than the oral treatment device 100.

[0141] In various embodiments, the oral treatment device 100 is controlled based on the classification data to treat the user's oral cavity. Thus, the action performed at item 830 may include performing treatment on the user's oral cavity.

[0142] In an embodiment where the oral treatment device includes a fluid delivery system 220 that delivers a working fluid to the user's oral cavity, a control signal can be output to the fluid delivery system 220 based on classification data to control the delivery of the working fluid. Thus, the action performed at item 830 can include controlling the delivery of the working fluid by the fluid delivery system 220. In various embodiments, the control signal is operable to cause the cessation of the delivery of the working fluid based on the classification data. Thereby, the efficiency and / or accuracy of the fluid delivery system 220 is improved, that is, the efficiency and / or accuracy of the fluid delivery system 220 is improved by considering the intraoral location of the head 120 of the determined device 100 when (or when not) performing the treatment.

[0143] In various embodiments, the user interface 250 outputs an output according to the classification data. Thus, the action performed at item 830 can include providing an output via the user interface 250. For example, such an output can include a notification that notifies the user to spend more time within a particular oral zone in order to improve the use of the device 100 during the treatment.

[0144] In various embodiments, the user interface 250 provides an output during the use of the oral treatment device 100 when treating the user's oral cavity. By providing the output by the user interface 250 during the use of the device 100 rather than after the completion of the oral treatment session, feedback can be provided more quickly. For example, the user interface 250 can provide an output substantially in real time. Thereby, it becomes possible for the user to adjust the user's behavior during the use of the device 100, for example, to take corrective actions, so that the effectiveness of the treatment implementation can be improved.

[0145] In various embodiments, the user interface 250 provides an output after use of the oral treatment device 100 when treating the user's oral cavity. By providing an output after use of the device 100, a more detailed level of feedback can be provided as compared to when an output is provided during use. For example, the use and / or movement of the device 100 can be analyzed throughout the entire oral treatment session and then feedback regarding the entire session can be provided to the user, for example, advising the user that it takes more time to treat a given oral zone. Such feedback encourages the user to adjust their behavior in subsequent sessions.

[0146] In various embodiments, the output provided by the user interface includes audio output, visual output, and / or tactile output. For example, the output can be provided via a display, a speaker, and / or a tactile actuator.

[0147] In various embodiments, the user interface is included in a remote device and a signal is output to the remote device such that the user interface provides the output. The user interface of such a remote device can be handheld and / or can be more versatile than the user interface of the oral treatment device 100 itself where space for the user interface may be limited.

[0148] In various embodiments, the oral treatment device 100 includes a user interface 250. By providing the user interface 250 on the oral treatment device 100, there is no need to communicate between different devices, so that an output can be generated and received by the user more quickly compared to the case where the user interface 250 is not provided on the oral treatment device 100. Further, by providing the user interface 250 on the oral treatment device 100, the possibility for the user to receive feedback quickly can be increased. For example, the user may not be in the same location as the remote device during the use of the oral treatment device 100, and thus may not be able to quickly view or hear the notifications on the remote device.

[0149] In various embodiments, an output including a notification for notifying the user to position the head 120 of the oral treatment device 100 in a predetermined oral zone is provided by a user interface (e.g., of the device 100 or the remote device). Such a notification is provided at the start of the oral treatment session. By providing such a notification to the user, the starting location of the head 120, i.e., the oral zone where the head 120 is disposed at the start of the session, is recognized by the non-linear classification algorithm. This can then be used as a constraint for the classification algorithm, thereby enhancing the accuracy and / or reliability of the algorithm when deriving the subsequent intraoral location of the head 120.

[0150] In various embodiments, the classification algorithm is modified using the signals received from the IMU 240. That is, the classification algorithm can be trained and / or further trained using the signals generated by the IMU 240. Modifying the classification algorithm can improve the accuracy and / or reliability of the classification algorithm by experience and / or the use of more training data. Further, by modifying the classification algorithm, it becomes possible to individually adjust the classification algorithm for the user. By dynamically retraining the classification algorithm using the generated IMU signals as training data, the classification algorithm can more reliably identify the oral zone where the head 120 of the device 100 is located.

[0151] In various embodiments, the classification data is stored in the memory 260. This enables the data to be used later, for example, for post-treatment analysis, and / or to generate a usage behavior profile of the device 100 for the user. In various embodiments, the classification data is output for transmission to a remote device, such as a user device like a mobile phone, tablet, laptop, personal computer, etc.

[0152] In various embodiments, training data is received from a remote device. The training data can be received from a network, such as the "cloud". Such training data can include IMU data and / or classification data associated with other users. Such training data can include, for example, crowdsourced data. In various embodiments, such training data is larger in quantity than the IMU data and / or classification data directly obtained from using the oral treatment device 100. By modifying the classification algorithm using the training data from the remote device, the accuracy and / or reliability of the classification algorithm can be increased compared to the case where such training data is not used.

[0153] FIG. 9 shows a method 900 for operating an oral treatment device according to various embodiments. The method 900 can be used to operate the oral treatment device 100 described above with reference to FIGS. 1A, 1B, and 2. In the embodiment of FIG. 9, the oral treatment device 100 comprises a head used for treating the user's oral cavity. In these embodiments, the oral treatment device 100 further comprises an IMU 240 and an image sensor device 230. In the embodiment of FIG. 9, the image sensor device 230 comprises an intraoral image sensor device. In various embodiments, the method 900 is at least partially executed by a control unit 210.

[0154] In step 910, a signal corresponding to the head position and / or movement of the oral treatment device 100 with respect to the user's oral cavity is generated using the IMU 240.

[0155] In step 920, image data depicting at least a part of the user's oral cavity is generated using the image sensor device 230. It should be understood that steps 910 and 920 can be executed substantially simultaneously or sequentially in any order.

[0156] In step 930, the generated signal and the generated image data are processed using a trained classification algorithm to derive the intraoral location of the head 120 of the oral treatment device 100.

[0157] In step 940, the oral treatment device 100 is controlled based on the derived intraoral location to execute an action.

[0158] By using the IMU signals and the image data as inputs to a trained classification algorithm, the intraoral location of the head 120 of the device 100 can be derived without the need for user input. Thus, the device 100 can autonomously identify the usage pattern of the device 100 by the user and adapt accordingly. Thereby, the device 100 can be controlled more intelligently. For example, one or more operation settings of the device 100 can be controlled according to the derived intraoral location. Further, the use of image data combined with IMU data provides a more accurate derivation of the intraoral location of the head 120 as compared to the case where only the image data and / or the IMU data are used. For example, the spatial resolution of the derivation of the intraoral location is improved by the use of image data combined with IMU data.

[0159] In some embodiments, the oral cavity includes a plurality of oral zones. In such embodiments, the generated signals and the generated image data are processed to identify the oral zone in which the head 120 is disposed from among the plurality of oral zones. The oral treatment device 100 is controlled based on the identified oral zone to perform an action. In some embodiments, a given oral zone among the plurality of oral zones represents, as described above, a quadrant or sextant of the oral cavity and a tooth surface selected from a list including the buccal tooth surface, the lingual tooth surface, and the occlusal tooth surface. Thereby, for example, it becomes possible to notify the user of where in the oral cavity the head 120 of the device 100 is located, how much time is spent in each oral zone, and the like. This information can also be used to determine whether the oral zone in which the head 120 is disposed has been reached during the current oral treatment session. In addition to providing direct user feedback, such information can facilitate the generation of a behavior profile indicating the usage tendency of the device 100 by the user based on information such as, for example, the time spent in each oral zone and the presence or absence of overlooked oral zones.

[0160] In various embodiments, the oral cavity includes a plurality of teeth, and the generated signal and the generated image data are processed to identify the tooth (e.g., the closest tooth) adjacent to the head 120 of the oral treatment device 100 from the plurality of teeth. The oral treatment device 100 is controlled based on the identified tooth to perform an action. Thus, the intraoral location of the head 120 of the device 100 is determined on a tooth-by-tooth basis (for each individual tooth). This enables, for example, the provision of user feedback to inform the user which specific teeth require further treatment. Thus, compared to the case where the tooth adjacent to the head 120 of the device 100 is not identified, more detailed and / or individually adjusted levels of feedback (e.g., having a higher spatial resolution) can be provided.

[0161] In various embodiments, the generated signal and the generated image data are processed to identify the interdental space between adjacent teeth in the user's oral cavity. The oral treatment device 100 is controlled based on the identified interdental space to perform an action. Thus, the interdental space can be automatically detected based on the IMU signal and the image data during use of the device 100. In some cases, the user may not be aware of the presence of a particular space, but the space can still be detected by the device 100 based on the IMU signal and the image data. As a result of the space detection, the user can be notified of the location of the space, and the device 100 can be controlled to treat the space. Thus, the intraoral location of the head 120 of the device 100 is determined on an interdental space-by-interdental space basis (for each individual space). Therefore, the method described herein has a higher spatial resolution than other methods. In various embodiments, identifying the space is a separate process from identifying the oral zone in which the head 120 is located. For example, first, it may be determined that the head 120 is close to the interdental space between adjacent teeth, and then, it may be further determined that the head 120 is in a specific oral zone (i.e., region) of the mouth. This facilitates the localization of the detected space.

[0162] In various embodiments, the classification algorithm comprises a machine learning algorithm. Such a machine learning algorithm can be improved by experience and / or training (e.g., the accuracy and / or reliability of classification can be increased).

[0163] In various embodiments, the oral treatment device 100 comprises a machine learning agent, and the machine learning agent comprises a classification algorithm. Thus, the classification algorithm can be disposed on the oral treatment device 100. By performing the derivation of the intraoral location on the device 100, transmission of data to another device and / or reception of data from another device are not required, so the latency is reduced compared to the case where the classification algorithm is not disposed on the device 100. Thereby, it becomes possible to derive the intraoral location more quickly, and the time required to take any corrective action and / or the time required to provide an output via the user interface can be shortened. In an alternative embodiment, the classification algorithm is disposed on a remote device, e.g., a device having more processing resources than the oral treatment device 100.

[0164] In various embodiments, the generated signal and / or the generated image data are used to modify the classification algorithm. That is, the generated signal and / or the generated image data can be used to train and / or further train the classification algorithm. Modifying the classification algorithm can improve the accuracy and / or reliability of the classification algorithm by experience and / or the use of more training data. That is, the reliability of the derived intraoral location can be increased. Further, by modifying the classification algorithm, it becomes possible to individually adjust the classification algorithm for the user. By dynamically retraining the classification algorithm using the generated signal and / or the generated image data as training data, the classification algorithm can derive the intraoral location of the head 120 of the device 100 with higher reliability.

[0165] In various embodiments, the oral treatment device 100 is controlled based on the derived oral location to treat the user's oral cavity. Thus, the action performed at item 940 may include performing a treatment by the device 100.

[0166] In an embodiment where the oral treatment device 100 includes a fluid delivery system 220 that delivers a working fluid to the user's oral cavity, a control signal is output to the fluid delivery system 220 based on the derived oral location to control the delivery of the working fluid. Thus, the action performed at item 940 may include controlling the fluid delivery system 220. For example, the oral location can be used to determine whether to actuate the ejection of the working fluid. Thereby, the efficiency and / or accuracy of the fluid delivery system 220 is improved, that is, the efficiency and / or accuracy of the fluid delivery system 220 is improved by considering the determined oral location of the head 120 of the device 100 when (or when not) performing the treatment.

[0167] In various embodiments, the user interface 250 provides an output corresponding to the derived oral location. Thus, the action performed at item 940 may include providing an output via the user interface 250. In various embodiments, the user interface 250 provides an output during the use of the oral treatment device 100 when treating the user's oral cavity. By providing an output by the user interface 250 during the use of the device 100 rather than after the completion of the oral treatment session, feedback can be provided more quickly. For example, the user interface 250 can provide an output substantially in real time. Thereby, it becomes possible for the user to adjust the user's behavior during the use of the device 100, for example, to take a corrective action, so that the effectiveness of performing the treatment can be improved.

[0168] In various embodiments, the user interface 250 provides an output after the use of the oral treatment device 100 when treating the user's oral cavity. By providing an output after the use of the device 100, a more detailed level of feedback can be provided compared to when an output is provided during use. For example, the use and / or movement of the device can be analyzed throughout the entire oral treatment session, and then feedback regarding the entire session can be provided to the user. In various embodiments, the user interface 250 provides an output both during and after the use of the device 100.

[0169] In various embodiments, the output provided by the user interface includes audio output, visual output, and / or tactile output. For example, the output can be provided via a display, a speaker, and / or a tactile actuator.

[0170] In various embodiments, the user interface is included in a remote device, such as a user device like a mobile phone. In such embodiments, a signal is output to the remote device, and the user interface provides the output. The user interface of such a remote device can be more versatile than the user interface of the oral treatment device 100 itself.

[0171] In various embodiments, the oral treatment device 100 includes the user interface 250. By providing the user interface 250 on the oral treatment device 100, there is no need to communicate between different devices, so an output can be generated and received by the user more quickly compared to the case where the user interface 250 is not provided on the oral treatment device 100. Furthermore, by providing the user interface 250 on the oral treatment device 100, the possibility that the user can receive feedback more quickly can be increased.

[0172] In various embodiments, data indicating the determined oral location is output for storage in the memory 260. This enables the data to be used later, for example, for post-treatment analysis and / or to generate a usage behavior profile of the device 100 for the user. In various embodiments, data indicating the determined oral location is output for transmission to a remote device, such as a user device.

[0173] In various embodiments, the determined oral location of the head 120 of the device 100 is used as part of an adjacent interproximal space detection and treatment process, such as one or more of the methods described above with reference to FIGS. 3-6. In various embodiments, the determined oral location of the head 120 is used in a plaque detection process, for example, using qualitative plaque fluorescence.

[0174] FIG. 10 shows a method 1000 for operating an oral treatment device according to various embodiments. The method 1000 can be used to operate the oral treatment device 100 described above with reference to FIGS. 1A, 1B, and 2. In the embodiment of FIG. 10, the oral treatment device 100 includes an IMU 240. The IMU 240 is operable to output a signal in response to movement of the oral treatment device 100. In various embodiments, the method 1000 is at least partially executed by the control unit 210.

[0175] In step 1010, a signal indicating movement of the oral treatment device 100 relative to the user's oral cavity is received.

[0176] 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 treatment device 100 is being moved according to a predetermined movement pattern.

[0177] In step 1030, the classification data is used to control the oral treatment device 100 to perform an action.

[0178] By using the signal from the IMU240 as an input to the classification algorithm, the current movement mode of the device 100 can be recognized. Therefore, the device 100 can automatically identify the usage mode of the device 100 by the user and adapt accordingly. Thereby, the device 100 can be controlled more intelligently. For example, one or more operation settings of the device 100 can be controlled according to the identified behavior. Thereby, the settings of the device 100 can be closely adapted to the usage mode of the device 100 by the user. Using a trained algorithm results in a more accurate and / or reliable classification of the movement mode compared to the case where a trained algorithm is not used.

[0179] In some embodiments, the movement of the oral treatment device 100 according to a predetermined movement mode inhibits the use of the oral treatment device 100 when treating the user's oral cavity. Therefore, it can be determined when the device 100 is being moved so that the possibility of the desired treatment being performed by the device 100 is reduced. Based on such a determination, the user can be warned accordingly and / or the device 100 can be controlled. For example, in some embodiments, the predetermined movement mode includes a scrubbing movement. The scrubbing movement includes a rapid back-and-forth movement. Such a movement mode inhibits the effective implementation of some treatments, for example, the delivery of the working fluid to the adjacent interdental spaces between teeth. Therefore, by determining whether the device 100 is being moved in such a manner, it is possible for the user to take a corrective action immediately when the device 100 notifies that the movement mode is inhibiting an effective treatment, or for the device 100 itself to take a corrective action, for example, by controlling the implementation of the treatment.

[0180] In response to the classification data indicating that the oral treatment device 100 is being moved according to a predetermined movement pattern, the execution of treatment by the oral treatment device 100 in the user's oral cavity is stopped. Thus, the action performed in item 1030 may include stopping the execution of the treatment. As described above, when the device 100 is being moved according to a predetermined movement pattern, the use of the device 100 in effectively treating the user's oral cavity may be inhibited, i.e., the use of the device 100 may be adversely affected. Therefore, by stopping the execution of the treatment when it is determined that the device 100 is being moved according to a predetermined pattern, the device 100 is operated more efficiently. That is, if the method of moving the device 100 is determined to have a relatively low probability of success, the execution of the treatment is not attempted.

[0181] In response to the classification data indicating that the oral treatment device 100 is not being moved according to a predetermined movement pattern, the oral treatment device 100 is controlled to perform a treatment in the user's oral cavity. Thus, it is possible to enable the execution of the treatment by determining that the device 100 is not being moved according to a predetermined movement pattern, for example, by determining that the device 100 is not being moved while performing a scrubbing motion. Therefore, when it is determined that the device 100 is being moved according to a predetermined pattern, the execution of the treatment can be stopped, and when it is determined that the device 100 is not being moved according to a predetermined movement pattern, the execution of the treatment can be enabled (or the trigger can be permitted). Thus, the movement pattern of the device 100 is used as a condition for determining whether to execute the treatment.

[0182] In various embodiments, in response to classification data indicating that device 100 is being moved according to a further predetermined movement pattern, device 100 is controlled to treat the user's oral cavity. In an example where the predetermined movement pattern includes, for example, a scrubbing motion, the further predetermined movement pattern may not include motion or may include a "smooth" sliding motion different from the scrubbing motion. Thus, the user may be encouraged not to use the predetermined movement pattern or to continue using the predetermined movement pattern to improve the efficiency and / or effectiveness of the treatment.

[0183] In an embodiment where oral treatment device 100 includes a fluid delivery system 220 that delivers a working fluid to the user's oral cavity, a control signal is output to fluid delivery system 220 based on the classification data to control the delivery of the working fluid. Thus, the action performed at item 1030 may include controlling fluid delivery system 220. For example, if it is determined that device 100 is being moved according to a predetermined movement pattern, the delivery of the working fluid can be stopped. The user may move device 100 in a manner that inhibits the accurate and / or reliable delivery of the working fluid to a target, such as an interdental space between adjacent teeth. For example, if device 100 is being moved too quickly, such as in a scrubbing motion, fluid delivery system 220 may be less likely to deliver a jet of the working fluid to the actually intended location, such as an interdental space. This can be a particular consideration when the reach of the fluid jet is relatively small (i.e., concentrated). This means that there is a higher likelihood that the working fluid will be wasted by missing the target, and a reduced likelihood that an effective treatment will be achieved (at least, achieved without repeatedly attempting fluid ejection). By controlling fluid delivery system 220 based on whether device 100 is being moved according to a predetermined movement pattern, the accuracy and / or efficiency of fluid delivery system 220 is increased and the amount of working fluid used and / or wasted is reduced.

[0184] In various embodiments, the method of FIG. 10 is performed in conjunction with an image-based interproximal space detection and treatment process, such as the method of FIG. 4 above. In such an embodiment, the detection of the interproximal space can be inhibited if the movement of the image sensor device 230 is too rapid when the device 100 is being moved in a scrubbing motion. Even if the space is successfully detected, the scrubbing motion can reduce the accuracy of the fluid delivery system 220 when delivering a jet of the working fluid to the detected space. Therefore, the performance of the interproximal space detection and treatment process is improved by selectively stopping the performance of the treatment when it is determined that the device 100 is being moved according to a predetermined movement pattern.

[0185] In various embodiments, the feature quantity is extracted substantially in real time from the received IMU signals, i.e., during the use of the device 100. A sliding window can be applied to the IMU signals to extract feature quantities (e.g., one or more average values) from the signals. Such extracted feature quantities are input into a trained classification algorithm, which determines whether the device 100 is being moved according to a predetermined movement pattern. In various embodiments, the IMU 240 comprises a six-axis IMU that provides accelerometer and gyroscope data. In alternative embodiments, only one of the accelerometer data and the gyroscope data is provided by the IMU 240.

[0186] In various embodiments, the IMU signals are sampled at a predetermined sampling rate for analysis by a trained classification algorithm. The sampling rate can be determined in advance based on information such as the available computing resources of device 100, whether the analysis is to be performed on a remote device rather than on device 100 itself, etc. For example, if the sampling frequency of the IMU signals is relatively low, the computational load can be less compared to when the sampling frequency of the IMU signals is relatively high. However, the lower the sampling frequency of the IMU signals, the longer the latency from when the signals are acquired until device 100 is controlled may become, and / or the accuracy of the determination of the movement mode made by the classification algorithm may decrease. Therefore, there can be a trade-off between performance and processing resources when determining the sampling rate of the IMU signals.

[0187] In various embodiments, in response to the classification data indicating that the oral treatment device 100 is being moved according to a predetermined movement pattern, an output is provided by the user interface. For example, device 100 can include the user interface 250 described above with reference to FIG. 2, and the output can be provided by the user interface 250. Thus, the action performed at item 1030 can include providing an output via the user interface 250. By providing the output to the user, the user can be notified that device 100 is being moved in a way that may impede an effective treatment using device 100, thereby prompting the user to take a corrective action. In various embodiments, the output provided by the user interface 250 includes an audio output, a visual output, and / or a tactile output. For example, the output provided by the user interface 250 can include a flashing light, an audio tone, and / or a vibration.

[0188] In various embodiments, the user interface 250 provides an output during use of the oral treatment device when treating the user's oral cavity. By providing the output during use of the device 100 rather than after completion of the oral treatment session, feedback can be provided more quickly. For example, the user interface 250 can provide the output substantially in real time. This enables the user to adjust the user's behavior during use of the device 100, for example, to take corrective actions, thereby improving the effectiveness of the treatment implementation.

[0189] In various embodiments, the user interface 250 provides an output after use of the oral treatment device 100 when treating the user's oral cavity. By providing the output after use of the device 100, a more detailed level of feedback can be provided compared to when the output is provided during use. For example, the use and / or movement of the device 100 can be analyzed throughout the oral treatment session and then feedback regarding the entire session can be provided to the user. Such feedback prompts the user to adjust the user's behavior in subsequent sessions.

[0190] In various embodiments, user feedback is provided both during use of the device 100 (e.g., substantially in real time) and after the end of the treatment session. For example, the user interface 250 of the device 100 can provide the user with an indication that the device 100 is being moved optimally, for example, in a scrubbing motion, during use of the device 100. Further, a further user interface located on a remote device can provide a more detailed analysis of the user's behavior after the end of the treatment session. Thereby, the user can adjust the manner of use of the device 100 by the user in subsequent sessions.

[0191] In various embodiments, the oral treatment device 100 includes a user interface 250. By providing the user interface 250 on the oral treatment device 100, there is no need to communicate between different devices, so that an output can be generated and received by the user more quickly compared to the case where the user interface is not provided on the oral treatment device. Further, by providing the user interface on the oral treatment device 100, the possibility that the user can receive feedback quickly can be increased.

[0192] In various embodiments, 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 and the output is provided by the user interface. Such a signal can be transmitted wirelessly to the remote device, for example, via Bluetooth (trademark) technology. The user interface of such a remote device can be more versatile than the user interface of the oral treatment device itself. For example, the oral treatment device 100 is generally handheld and can have various other components, so the amount of space on the oral treatment device 100 available for the user interface can be limited.

[0193] In various embodiments, the classification algorithm is modified using the signals received from the IMU 240. That is, the IMU signals can be used to train and / or further train the classification algorithm. Modifying the classification algorithm can improve the accuracy and / or reliability of the classification algorithm by experience and / or the use of more training data. That is, the confidence level of the determined movement mode can be increased. Further, by modifying the classification algorithm, it becomes possible to individually adjust the classification algorithm for the user. For example, an initial classification algorithm may be provided on the device 100, but the initial classification algorithm does not take into account the specific behavior of a given user. A user can move the device 100, for example, by a specific usage different from other users. By dynamically retraining the classification algorithm using the generated signals as training data, the classification algorithm can determine with higher reliability whether the device 100 is being moved according to a predetermined movement mode.

[0194] In various embodiments, the classification algorithm is retrained (e.g., modified) using the signals received from the IMU 240, and as a result, the retrained classification algorithm is configured to determine whether the oral treatment device is being moved according to a further movement mode different from the predetermined movement mode. Thus, the classification algorithm can initially be trained to detect a first movement mode and retrained based on user-specific data to detect a different second movement mode. In this way, the classification algorithm can be individually adjusted to the behavior of a specific user, for example, to detect a specific movement mode used by the user.

[0195] In various embodiments, the classification data is stored in the memory 260. This makes it possible to use the data later, for example, for post-treatment analysis and / or to generate a usage behavior profile of the device 100 for the user. In various embodiments, the classification data is output for transmission to a remote device, such as a user device.

[0196] In various embodiments, training data is received from a remote device. In such embodiments, the received training data is used to modify a classification algorithm. The training data can be received from a network, such as the "cloud". Such training data can include IMU data and / or classification data associated with other users. Such training data can include, for example, crowdsourced data. In various embodiments, such training data is greater in quantity than IMU data and / or classification data directly obtained from using the oral treatment device 100. By using the training data from the remote device to modify the classification algorithm, the accuracy and / or reliability of the classification algorithm can be increased compared to when such training data is not used.

[0197] In various embodiments, the classification algorithm includes a non-linear classification algorithm. The non-linear classification algorithm can be used to distinguish behaviors that are not linearly separable. This can be the case when the user moves the device being used. Thus, using a non-linear classification algorithm to obtain classification data results in the derivation of more accurate and / or reliable classification data compared to the use of a linear classification algorithm or function.

[0198] In various embodiments, the classification algorithm comprises a machine learning algorithm. Such a machine learning algorithm can be improved by experience and / or training (e.g., the accuracy and / or reliability of classification can be increased). In various embodiments, the classification algorithm is trained using supervised and / or unsupervised machine learning methods for detecting whether the device 100 is being moved according to a predetermined movement pattern.

[0199] In various embodiments, the oral treatment device 100 includes a machine learning agent, and the machine learning agent includes a classification algorithm. Thus, the classification algorithm can be disposed in the oral treatment device 100. By performing determination of the movement mode regarding the device 100, transmission of data to another device and / or reception of data from another device are not required, so the latency is reduced as compared with the case where the classification algorithm is not disposed in the device 100. Thereby, it becomes possible to distinguish the movement mode more quickly, and the time required to take some corrective action and / or the time required to provide an output via the user interface can be shortened.

[0200] It should be understood that any feature described in connection with any one embodiment and / or aspect may be used alone or in combination with other features described, and further may be used in combination with one or more features of any other embodiment and / or aspect, or any combination of any other embodiment and / or aspect. For example, it should be understood that features and / or steps described in connection with a given one of methods 300, 400, 500, 600, 700, 800, 900, 1000 may be included instead of, or in addition to, features and / or steps described in connection with other ones of methods 300, 400, 500, 600, 700, 800, 900, 1000.

[0201] In various embodiments of the present disclosure, the automatic operation of the device 100 (e.g., related to any of methods 300, 400, 500, 600, 700, 800, 1000) can be overridden by a user of the device 100. For example, a user may desire that a repetitive procedure (e.g., further jetting of the working fluid) be delivered to an adjacent interdental space that has already been treated if the automatic operation executed by the control unit 210 is stopping such a repetitive procedure. Such a situation can occur, for example, when the initial treatment of the space was not successful and / or satisfactory for the user. In embodiments, the device 100 includes a user interface, such as a button, to enable the user to force a repetitive procedure, thereby overriding the automatic operation of the device 100.

[0202] In various embodiments of the present disclosure, one or more data analysis algorithms are used to control the oral treatment device 100, for example, to detect adjacent interdental spaces, to determine the intraoral location of the head of the device 100, to determine whether the device 100 is being moved according to a predetermined movement pattern, and the like. The data analysis algorithm analyzes the received data, such as image data and / or IMU data, and is configured to generate an output that can be used as a condition for controlling the device 100, such as the presence or absence of a space. In embodiments, the data analysis algorithm includes a classification algorithm, such as a non-linear classification algorithm. In embodiments, the data analysis algorithm includes a trained classification algorithm, as described above with reference to FIGS. 3-10. However, in alternative embodiments, the data analysis algorithm includes other types of algorithms that are not necessarily trained and / or configured to perform classification.

[0203] In various embodiments of the present disclosure, the oral treatment device 100 includes a control unit 210. The control unit 210 is configured to execute the various methods described herein. In embodiments, the control unit 210 includes a processing system. Such a processing system can include one or more processors and / or memories. Each device, component, or function described in connection with any of the examples described herein, such as the image sensor device 230, the user interface 250, and / or the machine learning agent, can similarly include a processor or can be included in a device that includes a processor. One or more aspects of the embodiments described herein include processes executed by a device. In some examples, the device includes one or more processors configured to execute these processes. In this regard, the embodiments can be implemented, at least in part, by computer software executable by a processor, or by hardware, or by a combination of software (and firmware stored in a tangible medium) and hardware (and tangible medium). The embodiments also extend to computer programs adapted to implement the above embodiments, in particular computer programs carried on or in a carrier. The program can be in the form of non-transitory source code, object code, or any other non-transitory form suitable for use in implementing the processes according to the embodiments. The carrier can be any entity or device capable of carrying the program, such as a RAM, a ROM, or an optical memory device.

[0204] One or more processors of the processing system can include a central processing unit (CPU). One or more processors can include a graphics processing unit (GPU). One or more processors can 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 can include an application specific integrated circuit (ASIC). Those skilled in the art should understand that, in addition to these examples, numerous other types of devices can be used to provide one or more processors. One or more processors can include multiple processors located in the same location or multiple processors located in different locations. Operations executed by one or more processors can be executed by one or more of hardware, firmware, and software. It should be understood that the processing system can include more, fewer, and / or different components than the described components.

[0205] The techniques described herein can be implemented in the form of software or hardware, or in a combination of software and hardware. The techniques described herein may include configuring an apparatus for performing and / or assisting in performing any or all of the techniques described herein. At least some aspects of the examples described herein with reference to the drawings include computer processes executed in a processing system or processor, but the examples described herein also extend to computer programs adapted to implement these examples, such as computer programs on or in a carrier. A carrier can be any entity or device capable of executing a program. A carrier can comprise a computer-readable storage medium. Examples of computer-readable tangible storage media include, but are not limited to, optical media (such as CD-ROM, DVD-ROM or Blu-ray), flash memory cards, floppy disks or hard disks, or any other medium capable of storing at least one computer-readable instruction in a ROM or RAM or programmable ROM (PROM) chip such as firmware or microcode.

[0206] If there are equivalents known, obvious, or foreseeable to the numerical values or elements mentioned in the above description, such equivalents shall also be incorporated into the present disclosure individually. The present disclosure includes all such equivalents, and the true scope of the present disclosure shall be determined by the scope of the claims. It should be understood that all the preferred numerical values or features, advantageous numerical values or features, or convenient numerical values or features, etc. of the present disclosure mentioned in the above description are all optionally selectable and do not limit the scope of the independent claims. Furthermore, such optionally selectable numerical values or features may be beneficial in some embodiments of the present disclosure but not desirable in other embodiments, and thus may be omitted depending on the embodiments.

Claims

**Claim 1** An oral treatment device for use in treating a user's oral cavity, comprising: an image sensor device operable to generate image data depicting at least a portion of the user's oral cavity; a control unit configured to: process the generated image data using a data analysis algorithm configured to identify adjacent interdental spaces between adjacent teeth within the user's oral cavity; compare at least one characteristic of the identified adjacent interdental spaces with at least one characteristic of one or more adjacent interdental spaces of the user's oral cavity previously identified during the same oral treatment session; and control the oral treatment device to perform an action based on the result of the comparison. In an oral treatment device comprising: the data analysis algorithm includes a classification algorithm. **Claim 2** The oral treatment device according to claim 1, wherein the control unit is configured to: calculate a similarity metric indicative of a level of similarity between the identified adjacent interdental spaces and the one or more previously identified adjacent interdental spaces in response to the result of the comparison; and control the oral treatment device based on the derived similarity metric. **Claim 3** The oral treatment device according to claim 2, wherein the control unit is configured to control the oral treatment device to treat the identified adjacent interdental spaces in response to the similarity metric indicating that the identified adjacent interdental spaces are different from the one or more previously identified adjacent interdental spaces. **Claim 4** The oral treatment device according to claim 2 or 3, wherein the control unit is configured to store, in a memory, image data depicting the identified adjacent interdental spaces for use in subsequent identification and / or comparison of adjacent interdental spaces in response to the similarity metric indicating that the identified adjacent interdental spaces are different from the one or more previously identified adjacent interdental spaces. **Claim 5** The oral treatment device according to any one of claims 2 to 4, wherein ​ ​ ​ ​ ​ ​ ​ In response to the similarity index indicating that the identified adjacent interproximal space is the same as at least one of the one or more adjacent interproximal spaces identified in the past, the control unit is configured to control the oral treatment device to stop performing treatment on the identified adjacent interproximal space. Oral treatment device.

6. The oral treatment device according to any one of claims 2 to 5, wherein in response to the similarity index indicating that the identified adjacent interproximal space is the same as at least one of the one or more adjacent interproximal spaces identified in the past, the control unit derives the elapsed time from the time when the at least one of the one or more adjacent interproximal spaces identified in the past was identified, compares the derived elapsed time with a predetermined threshold, and controls the oral treatment device based on the result of the comparison between the derived elapsed time and the predetermined threshold. It is configured as follows. Oral treatment device.

7. The oral treatment device according to claim 6, wherein the control unit, in response to the derived elapsed time being longer than the predetermined threshold, controls the oral treatment device to perform treatment on the identified adjacent interproximal space, and in response to the derived elapsed time being shorter than the predetermined threshold, controls the oral treatment device to stop performing treatment on the identified adjacent interproximal space. It is configured as follows. Oral treatment device.

8. The oral treatment device according to claim 1, wherein the data analysis algorithm includes a trained classification algorithm. Oral treatment device.

9. The oral treatment device according to any one of claims 1 to 8, wherein the control unit is configured to process the generated image data to derive at least one characteristic of the identified adjacent interproximal space. Oral treatment device.

10. The oral treatment device according to claim 9, wherein the control unit processes the generated image data using a machine learning algorithm trained to identify information used to distinguish between adjacent interproximal spaces to derive the at least one characteristic. Oral treatment device.

11. An oral treatment device according to any one of claims 1 to 10, wherein the image sensor device comprises an intraoral camera, Oral treatment device.

12. An oral treatment device according to any one of claims 1 to 11, wherein the oral treatment device comprises a head, and the image sensor device is at least partially included in the head, Oral treatment device.

13. An oral treatment device according to any one of claims 1 to 12, wherein the oral treatment device comprises a handle, and the image sensor device is at least partially included in the handle, Oral treatment device.

14. An oral treatment device according to any one of claims 1 to 13, wherein the oral treatment device comprises a fluid delivery system for delivering an action fluid to the oral cavity of the user, the control unit is configured to output a control signal to the fluid delivery system based on the result of the comparison to control the delivery of the action fluid, Oral treatment device.

15. The oral treatment device according to claim 14, wherein the fluid delivery system comprises a fluid reservoir for storing the action fluid within the oral treatment device, Oral treatment device.

16. An oral treatment device according to any one of claims 1 to 15, Toothbrush An oral treatment device comprising

17. An oral treatment device according to any one of claims 1 to 16, wherein at least one of the characteristics of the identified adjacent interdental space indicates at least one of the shape of the identified adjacent interdental space, the appearance of the identified adjacent interdental space, and the position of the identified adjacent interdental space, Oral treatment device.

18. A computer program comprising a set of instructions that, when executed by a computer device, cause the computer device to execute a method of operating an oral treatment device used for treating a user's oral cavity, wherein the oral treatment device comprises an image sensor device operable to generate image data depicting the oral cavity of the user, the method comprising processing the generated image data using a data analysis algorithm configured to identify adjacent interdental spaces between adjacent teeth in the oral cavity of the user, comparing at least one characteristic of the specified interdental space with at least one characteristic of one or more interdental spaces of the user's oral cavity that have been previously specified during the same oral treatment session; controlling the oral treatment device based on the result of the comparison to perform an action; comprising; in a computer program; a computer program in which the data analysis algorithm includes a classification algorithm.

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