Oral treatment device

Abstract

An oral processing device is provided. The oral processing device includes an intraoral image sensor device configured to generate image data representing at least a portion of the user's oral cavity during use of the oral processing device by the user. The oral processing device includes a controller configured to process the generated image data to determine location data representing the location of adjacent gaps between adjacent teeth within the user's oral cavity. The controller is configured to process the generated image data using a trained classification algorithm configured to identify adjacent gaps, wherein the trained classification algorithm is trained prior to use of the oral processing device. The controller is configured to control the oral processing device to deliver processing to the detected adjacent gaps based on the location data during use of the oral processing device.

Description

Technology Field

[0001] The present invention relates to an oral treatment device. In particular, the present invention relates to means including, but not limited to, a method, apparatus, and computer program for operating an oral treatment device. Background Technology

[0002] Oral treatment devices are used to provide treatment to the user's oral cavity (i.e., mouth). Examples of such devices include toothbrushes (manual or electric), mouthwashes, interdental cleaning devices, and dental floss devices.

[0003] In some disclosed cases, an oral care device (also referred to as an “oral care device” or “oral care device”) may provide a flossing function in addition to other functions such as brushing. For example, a fluid delivery system may be integrated into an electric toothbrush and may be used to dispense a working fluid for cleaning adjacent interdental (or interdental) spaces. Such a fluid delivery system may include a nozzle arranged in the head of the device and used to spray the working fluid into the interproximal gap between teeth (e.g., to dislodge food particles in the gap), and a fluid reservoir for storing the working fluid in the device.

[0004] However, the flexibility and / or versatility of the disclosed oral treatment device are limited. Consequently, the ability of the disclosed device to deliver treatment in an optimal manner is limited. For example, the disclosed oral treatment device generally relies on the user using the device correctly, which is not always the case.

[0005] For example, if an oral treatment device includes an on-board fluid reservoir with a fixed capacity, the efficient use of the working fluid may require special consideration. Using more working fluid and / or wasting it necessitates replenishing the reservoir more frequently. In some cases, effective treatment may not be achieved despite repeated attempts.

[0006] Therefore, it is desirable to provide an improved oral treatment device and / or a method of operating the improved oral treatment device. means of solving the problem

[0007] According to one aspect of the present invention, an oral processing device for use in processing a user’s oral cavity is provided, wherein the oral processing device comprises: an intraoral image sensor device configured to generate image data representing at least a portion of the user’s oral cavity during use of the oral processing device by the user; and a controller, wherein the controller comprises: processing the generated image data to determine location data representing the location of adjacent gaps between adjacent teeth within the user’s oral cavity (the controller is configured to process the generated image data using a trained classification algorithm configured to identify adjacent gaps, wherein the trained classification algorithm is trained prior to use of the oral processing device); and controlling the oral processing device to deliver processing to the detected adjacent gaps based on the location data during use of the oral processing device.

[0008] Processing intraoral image data using a trained classification algorithm improves the accuracy and / or reliability of adjacent gap detection and / or adjacent gap location identification compared to cases where the intraoral image data is not processed using such a trained algorithm. Consequently, the intraoral processing device can be used more precisely and / or more intelligently. During the use of the device, the device location and / or adjacent gap can be detected more accurately, and by using this information to control processing delivery at that time (i.e., during the same use of the device), processing delivery can be performed more accurately. This improves the reliability and / or functionality of the device. Furthermore, using image data allows not only the detection of gaps but also the identification of their locations. Identifying the location of the gap enables more accurate and / or reliable processing delivery compared to cases where the location of the gap is not identified. In the embodiments, the determined gap location includes a location within the user's intraoral cavity.

[0009] In an embodiment, the oral treatment device includes a fluid delivery system for delivering a working fluid to the user's oral cavity. In this embodiment, the controller is configured to output a control signal to the fluid delivery system to control the delivery of the working fluid based on position data. Thus, during use of the device, the delivery of the working fluid is controlled in response to the automatic localization of adjacent gaps using an intraoral camera and a trained classification algorithm (during the same use of the device). Accordingly, the fluid delivery system can be used more accurately and / or reliably. In particular, the accuracy of fluid injection (i.e., the probability that the working fluid is actually injected into an adjacent gap rather than elsewhere) is increased. By improving the accuracy and / or reliability of the fluid delivery system, the amount of working fluid used is reduced, and more effective treatment is achieved more quickly.

[0010] In an embodiment, the oral processing device comprises a head, and an intraoral image sensor device is at least partially included in the head. Since the head of the device is intended to deliver processing into the user's oral cavity, by arranging the image sensor device at least partially in the head, the inside of the oral cavity can be imaged without the need to mount a separate intraoral camera (i.e., a camera mounted separately from the head). As used herein, the term "intraoral image sensor device" means that at least a portion of the image sensor device is arranged to be used inside the user's mouth.

[0011] In the embodiments, the oral processing device includes a handle, and the intraoral image sensor equipment is at least partially contained within the handle. By arranging the image sensor equipment at least partially within the handle of the device, space on the device can be managed more efficiently. That is, since the head of the device may be relatively small compared to the handle, incorporating the image sensor equipment into the head may require changes to the head's architecture and / or structure, which may be relatively complex and / or costly. Additionally, in the embodiments, the head of the device can be detached from the handle and is disposable, so it may be desirable for the user to periodically replace the head after use. Therefore, arranging the image sensor equipment at least partially within the handle instead of arranging the entire head reduces the cost of replacement parts.

[0012] In an embodiment, the oral processing device includes a head, and the intraoral image sensor equipment includes a sensor; and an aperture for receiving light and transmitting light to the sensor. The aperture is included in the head of the oral processing device. Accordingly, the aperture can receive light within the user's oral cavity. In an embodiment, the sensor is included in the handle of the device. In an alternative embodiment, the sensor is included in the head of the device. In an embodiment, the image sensor equipment includes a guide channel for guiding light from the aperture to the sensor. For example, if the oral processing device includes a head, a handle, and a stem connecting the head and the handle, the guide channel may extend from the aperture to the sensor along the stem (e.g., inside the stem). The guide channel may include, for example, a fiber optic cable. In some cases, the intraoral image sensor equipment may include a plurality of image sensors.

[0013] In an embodiment, the oral processing device includes an illuminator for illuminating the user's oral cavity while the oral processing device is in use. Illuminating the oral cavity facilitates accurate image processing of image data generated by the image sensor equipment. The illuminator may include, for example, one or more light-emitting diodes (LEDs). In an embodiment, the illuminator is positioned adjacent to the aperture of the image sensor equipment (for example, on the head of the device).

[0014] In an embodiment, the controller is configured to process generated image data using a sliding window. In this embodiment, location data is determined by detecting the presence of adjacent gaps within the sliding window. Accordingly, by determining, for example, a sub-region containing a gap within the image, adjacent gaps can be detected as well as their location identified.

[0015] In an embodiment, the controller is configured to process the generated image data by extracting one or more image features from the image data and determining location data using the extracted one or more image features. This further improves the accuracy of gap location identification. In an embodiment, the controller is configured to extract one or more image features using a discrete wavelet transform. Features extracted using the discrete wavelet transform can be used to more accurately detect and locate adjacent gaps from the image data. In an embodiment, the controller is configured to extract one or more image features using at least one of an edge detector, a corner detector, and a blob extractor. Extracting image features using this method can provide more accurate detection and / or location identification of adjacent gaps compared to other methods.

[0016] In the embodiment, the image data includes red, green, and blue (RGB) image data. Using RGB image data enables more accurate identification of gap locations compared to other types of image data.

[0017] In an embodiment, the oral treatment device includes a user interface. In this embodiment, the controller is configured to cause the user interface to provide an output based on position data. For example, the output may include a notification informing the user that an adjacent gap location has been identified, a notification indicating the location of the adjacent gap, a notification informing the user that a treatment delivery has been performed on the adjacent gap, and / or a notification instructing the user to adjust the position and / or orientation of the device so that a more accurate treatment delivery (e.g., injection of a working fluid) can be performed.

[0018] In an embodiment, the oral processing device includes memory, and the controller is configured to store one or more characteristics of adjacent gaps in memory for use in subsequent processing and / or control of the oral processing device. For example, one or more stored characteristics may be used to compare an adjacent gap with an adjacent gap subsequently identified. By distinguishing different adjacent gaps of the user, repetitive processing of a specific gap can be avoided if necessary, thereby reducing the use of working fluid. In other cases, one or more stored characteristics are used to track adjacent gaps over time.

[0019] In the example, the oral treatment device includes a toothbrush.

[0020] According to one aspect of the present invention, a method of operating an oral processing device for use in processing a user's oral cavity is provided, wherein the oral processing device comprises an intraoral image sensor device and a controller. The method comprises: generating image data representing at least a portion of the user's oral cavity during use of the oral processing device by the user using the intraoral image sensor device; processing the generated image data in the controller to determine location data representing the location of adjacent gaps between adjacent teeth in the user's oral cavity (the generated image data is processed using a trained classification algorithm configured to identify adjacent gaps, wherein the trained classification algorithm is trained prior to use of the oral processing device); and controlling the oral processing device in the controller to deliver processing to the detected adjacent gaps based on the location data during use of the oral processing device.

[0021] According to one aspect of the present invention, a computer program is provided comprising a set of instructions that, when executed by a computer device, cause the computer device to perform a method of operating an oral processing device for use in processing a user's oral cavity, said computer device, said method comprising: generating image data representing at least a portion of the user's oral cavity during use of the oral processing device by the user using an oral image sensor device; processing the generated image data to determine location data representing the location of adjacent gaps between adjacent teeth within the user's oral cavity (the generated image data is processed using a trained classification algorithm configured to identify adjacent gaps, wherein the trained classification algorithm is trained prior to use of the oral processing device); and controlling the oral processing device to deliver processing to the detected adjacent gaps based on the location data during use of the oral processing device.

[0022] Of course, it will be understood that the features described in connection with one aspect of the present invention may be incorporated into other aspects of the present invention. For example, the method of the present invention may include any of the features described with reference to the device of the present invention, and vice versa. Brief explanation of the drawing

[0023] Now, embodiments of the present invention will be described for illustrative purposes only with reference to the accompanying drawings, and in the drawings: FIGS. 1a and FIGS. 1b are perspective views of an oral treatment device according to an embodiment. FIG. 1c is a plan view of an oral treatment device according to an embodiment. FIG. 2 is a schematic diagram of an oral treatment device according to an embodiment. FIG. 3 is a flowchart illustrating the operation method of an oral treatment device according to an embodiment. FIG. 4 is a flowchart illustrating the operation method of an oral treatment device according to an embodiment. FIG. 5 is a flowchart illustrating the operation method of an oral treatment device according to an embodiment. FIG. 6 is a flowchart illustrating the operation method of an oral treatment device according to an embodiment. FIG. 7 is a flowchart illustrating the operation method of an oral treatment device according to an embodiment. FIG. 8 is a flowchart illustrating the operation method of an oral treatment device according to an embodiment. FIG. 9 is a flowchart illustrating the operation method of an oral treatment device according to an embodiment. FIG. 10 is a flowchart illustrating the operation method of an oral treatment device according to an embodiment. Specific details for implementing the invention

[0024] FIGS. 1a and 1b illustrate a perspective view of an oral treatment device (100) according to an embodiment. FIG. 1c illustrates a top view of the oral treatment device (100). The oral treatment device (100) and / or its components may be used to implement the methods described herein. In the embodiment illustrated in FIGS. 1a through 1c, the oral treatment device (100) includes a toothbrush. In the embodiment, the oral treatment device (100) includes an electric toothbrush. In the embodiment, the device (100) includes an ultrasonic toothbrush. In an alternative embodiment, the oral treatment device (100) may include other types of devices. For example, the device (100) may include a dental floss 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 user's oral health and provide feedback to the user accordingly.

[0025] The oral treatment device (100) includes a handle (110) and a head (120). The handle (110) forms the body of the device (100) and can be grasped by a user while using the device (100). In the embodiments illustrated in FIGS. 1a through 1c, the handle (110) includes a user interface (112). The user interface (112) includes a user-operable button configured to be pressed by the user while the user is grasping the handle (110). In some embodiments, the handle (110) includes a display (not shown) that can be positioned to be visible to the user while using the oral treatment device (100).

[0026] In the embodiment illustrated in FIGS. 1a through 1c, the head (120) includes a plurality of bristles (122) for performing a toothbrushing function. In other 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, which is intended to clean, for example, the gaps between adjacent teeth and / or to deliver a cleaning or whitening medium to the user's teeth. In the embodiment illustrated in FIGS. 1a through 1c, the oral treatment device (100) includes a stem (130) that connects the handle (110) to the head (120). The stem (130) has an elongated shape and serves to separate the head (120) from the handle (110) to facilitate user operability of the oral treatment device (100). The head (120) and / or the stem (130) may be separated from the handle (110).

[0027] The oral treatment device (100) includes a tooth treatment system for delivering treatment to the user's oral cavity. In the embodiments illustrated in FIGS. 1a through 1c, the tooth treatment system includes a fluid delivery system, but it will be understood that in other embodiments, other types of tooth and / or oral treatment systems may be used. The fluid delivery system is configured to deliver bursts of working fluid to the oral cavity. In the embodiments, the working fluid includes a liquid, e.g., water. In other embodiments, the working fluid includes a gas and / or powder. The working fluid is delivered to the adjacent gap between adjacent teeth to dislodge foreign matter located in the gap, such as food, e.g., prosciutto or other cured meats. The adjacent gap may be a space or void between two adjacent teeth and / or an area surrounding the contact point of the adjacent teeth. The adjacent gap may be defined as an area having boundaries by a plane that is tangential to the zone between the teeth and the lingual side surface of the two adjacent teeth.

[0028] Additionally or alternatively, the working fluid may be delivered to the user's gum line, for example, to treat inflammation or infection of the gums. In another embodiment, the tooth treatment system is configured to deliver a whitening fluid and / or remove plaque from the user's teeth.

[0029] In the embodiments illustrated in FIGS. 1a through 1c, the oral treatment device (100) includes a fluid reservoir (114) for storing a working fluid. The fluid reservoir (114) is arranged on 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 the embodiments, the fluid reservoir (114) may be detached from the handle (110), for example, to facilitate the replenishment of the working fluid.

[0030] In an embodiment, the oral treatment device (100) also includes a nozzle (124). This is illustrated in FIG. 1c. The nozzle (124) forms part of the fluid delivery system of the device (100). The nozzle (124) is arranged on the head (120) of the device (100). The nozzle (124) is configured to deliver working fluid to the user's oral cavity while using the oral treatment device (100). In the embodiment illustrated in FIG. 1a through 1c, bristles (122) are arranged at least partially around the nozzle (124). The nozzle (124) extends along the nozzle axis (A) as illustrated in FIG. 1c. The nozzle axis (A) is substantially perpendicular to the longitudinal axis (Z) of the handle (110).

[0031] The nozzle (124) is arranged to receive working fluid from the fluid reservoir (114) and deliver bursts of working fluid to the user's mouth while using the device (100). In an embodiment, the tip of the nozzle (124) includes a fluid outlet through which bursts of working fluid are delivered to the mouth. Each burst of working fluid may have a volume of less than 1 milliliter, and in some cases less than 0.5 milliliters. The nozzle (124) may also include a fluid inlet for receiving working fluid from the fluid reservoir (114).

[0032] In an embodiment, the fluid transfer system includes a pump assembly (not shown) for drawing working fluid from a fluid reservoir (114) to a nozzle (124). The pump assembly may be arranged within a handle (110). The pump assembly may include a pump (e.g., a positive displacement pump) and a drive for driving the pump. In an embodiment, the drive includes a pump motor. Power may be supplied to the pump motor by a battery (e.g., a rechargeable battery).

[0033] In an embodiment, the fluid delivery system includes a control circuit (not shown) for controlling the actuation of a pump motor, and accordingly, the control circuit and the pump motor provide a drive for driving the pump. The control circuit may include a motor controller that supplies power to the pump motor. The control circuit of the fluid delivery system may receive a signal from a controller of the oral treatment device (100), which is described in more detail below.

[0034] FIG. 2 illustrates a schematic block diagram of an oral treatment device (100) according to an embodiment.

[0035] The oral processing device (100) includes a controller (210). The controller (210) may operate to perform various data processing and / or control functions according to the embodiment, which will be described in more detail below. The controller (210) may include one or more components. One or more components may be implemented in hardware and / or software. One or more components may be placed together within the oral processing device (100) or placed apart from each other. The controller (210) may be implemented as one or more software functions and / or hardware modules. In an embodiment, the controller (210) includes one or more processors (210a) configured to process instructions and / or data. The operation performed by one or more processors (210a) may be executed by hardware and / or software. The controller (210) may be used to implement the methods described herein. In an embodiment, the controller (210) may operate to output a control signal for controlling one or more components of the oral processing device (100).

[0036] In an embodiment, the oral treatment device (100) includes a fluid delivery system (220). As discussed with reference to FIGS. 1a through 1c, the fluid delivery system (220) can operate to deliver a working fluid to the user's oral cavity. In an embodiment, the fluid delivery system (200) includes a nozzle for ejecting the working fluid and a fluid reservoir for storing the working fluid within the oral treatment device [e.g., the nozzle (124) and fluid reservoir (114) described above]. The fluid delivery system (220) can operate to receive a control signal from a controller (210), thereby allowing the controller (210) to control the delivery of the working fluid by the fluid delivery system (220). For example, the controller (210) may output a control signal received by the control circuit of the fluid delivery system (220), which causes the control circuit of the fluid delivery system (220) to operate the pump motor, thereby allowing the working fluid to be pumped from the fluid reservoir to the nozzle and discharged from the nozzle into the user's oral cavity. Additionally or alternatively, the controller (210) may output a control signal received by the control circuit of the fluid delivery system (220), which causes the control circuit of the fluid delivery system (220) to prevent the delivery of the working fluid through the nozzle. In an alternative embodiment, the oral treatment device (100) does not include a fluid reservoir. That is, the working fluid is not stored in the oral treatment device (100) but can be delivered from outside the oral treatment device (100) (e.g., via a dedicated fluid delivery channel) and discharged through the nozzle.

[0037] In an embodiment, the oral processing 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 devices (CCDs) and complementary metal-oxide-semiconductor (CMOS) sensors. In an embodiment, the image sensor device includes an intraoral image sensor device. For example, the image sensor device may include an intraoral camera. The intraoral image sensor device (e.g., intraoral camera) may operate to be used at least partially within the user's oral cavity to generate image data representing the user's oral cavity. For example, the image sensor device (230) may be at least partially arranged on the head (120) of the oral processing device (100) which is arranged to be inserted into the user's oral cavity. In an embodiment, the image sensor device (230) includes one or more processors. The controller (210) can operate to receive image data from the image sensor equipment (230). The image data output from the sensor equipment (230) can be used to control the oral processing device (100). In an embodiment, the controller (210) can operate to control the image sensor equipment (230).

[0038] In the embodiment illustrated in FIG. 2, the oral processing device (100) includes an inertial measurement unit (IMU: 240). In this embodiment, the controller (210) may operate to receive a signal from the IMU (240) indicating the position and / or movement of the oral processing device (100). In an embodiment, the IMU (240) includes an accelerometer, a gyroscope, and a magnetometer. Each of the accelerometer, gyroscope, and magnetometer has three axes or three degrees of freedom (x, y, z). Thus, the IMU (240) may include a 9-axis IMU. In another embodiment, the IMU (240) includes an accelerometer and a gyroscope but does not include a magnetometer. In this embodiment, the IMU (240) includes a 6-axis IMU. A 9-axis IMU can obtain more accurate measurements than a 6-axis IMU due to additional degrees of freedom. However, in some scenarios, a 6-axis IMU may be more desirable than a 9-axis IMU. For example, some oral processing devices may experience and cause magnetic disturbances during use. Heating of the device, magnetism and / or magnetic inductance, and / or other magnetic disturbances may affect the operation of the magnetometer. Therefore, in some cases, a 6-axis IMU may be more reliable and / or accurate than a 9-axis IMU. The IMU (240) is configured to output data representing accelerometer and gyroscope signals (also magnetometer signals in some embodiments). In an embodiment, the IMU (240) is positioned on the head (120) of the oral processing device (100). In an alternative embodiment, the IMU (240) is positioned on the handle (110) of the oral processing device (100). In an embodiment, the oral processing device (100) includes a plurality of IMUs (140). For example, the first IMU (240) may be arranged on the head (120) and the second IMU (240) may be arranged on the handle (110).

[0039] In an embodiment, the oral treatment device (100) includes a contact member (245). The contact member (245) may operate to contact the user's teeth during use of the oral treatment device (100), as described in more detail below. The contact member (245) is arranged on the head (120) of the oral treatment device (100). For example, the contact member (245) may include a nozzle of a fluid delivery system (220), for example, the nozzle (124) described earlier with reference to FIGS. 1a through 1c.

[0040] In an embodiment, the oral processing device (100) includes a user interface (250). The user interface (250) may be similar to the user interface (112) previously described with reference to FIGS. 1a through 1c. The user interface (250) may include, for example, an auditory and / or visual interface. In an embodiment, the user interface (250) includes a display (e.g., a touchscreen display). In an embodiment, the user interface (250) includes an audio output device such as a speaker. In an embodiment, the user interface (250) includes a haptic feedback generator configured to provide haptic feedback to the user. A controller (210) may operate to control the user interface (250) so that, for example, the user interface (250) may provide output to the user. In some embodiments, the controller (210) may operate to receive data (e.g., based on user input) through the user interface (250). For example, the user interface (250) may include one or more buttons and / or touch sensors.

[0041] The oral treatment device (100) also includes a memory (260). According to an embodiment, the memory (260) may be operated to store various data. The memory may include at least one volatile memory, at least one non-volatile memory, and / or at least one data storage unit. The volatile memory, the non-volatile memory, and / or the data storage unit may be configured to store computer-readable information and / or instructions to be used / executed by the controller (210).

[0042] In alternative embodiments, the oral processing device (100) may include more components, fewer components, and / or different components. In particular, at least some of the components of the oral processing device (100) illustrated in FIG. 1a through 1c and / or FIG. 2 may be omitted according to the embodiment (e.g., may not be required). For example, at least one of the fluid delivery system (220), image sensor equipment (230), IMU (240), user interface (250), and memory (260) may be omitted in some embodiments. In an embodiment, the oral processing device (100) includes additional components not illustrated (e.g., a power source such as a battery).

[0043] FIG. 3 illustrates a method (300) of operating an oral treatment device according to an embodiment. The method (300) can be used to operate the oral treatment device (100) described above with reference to FIG. 1a, 1b, and 2. In the embodiment of FIG. 3, the oral treatment device (100) includes an IMU (240) and also includes a contact member (245) that can be operated to contact the user's teeth during use of the oral treatment device (100). In the embodiment, the method (300) is performed at least partially by a controller (210).

[0044] In step 310, a signal indicating the vibration characteristics of the oral processing device (100) is received from the IMU (240) during use of the oral processing device (100). The vibration characteristics vary depending on the contact between the contact member (245) and the tooth. Therefore, the vibration characteristics may vary (or have different values) depending on whether the contact member (245) and the tooth are in contact.

[0045] In step 320, the signal is processed to detect adjacent gaps between adjacent teeth within the user's oral cavity.

[0046] In step 330, while the oral treatment device is in use, the oral treatment device is controlled to deliver treatment to a detected adjacent gap.

[0047] Accordingly, while the user is using the device (100), the adjacent gap can be automatically detected using the contact member (245) and the IMU (240), and the delivery of processing can be controlled accordingly. Thus, the user does not need to determine whether the device (100) is in a position suitable for processing delivery (e.g., a position close to the adjacent gap or a position within the adjacent gap). Instead, this determination is made automatically by monitoring the vibration characteristics of the device (100) that change according to the contact between the contact member (245) and the tooth. By automatically detecting the position of the device (100) relative to the adjacent gap and / or the adjacent gap during use, and using this information to control the delivery of processing at that time [i.e., during the same use of the device (100)], the delivery of processing can be made more accurately.

[0048] Vibration characteristics refer to the characteristics of the device (100) vibrating while the device (100) is in use. For example, vibration characteristics may be related to the frequency and / or amplitude of the vibration. When the contact member (245) is in contact with a tooth, the vibration of the device (100) is dampened due to the contact compared to when the contact member (245) is not in contact with the tooth [e.g., when the contact member (245) is in the adjacent gap between adjacent teeth]. By analyzing the IMU signal to determine how the vibration of the device (100) is damped, it is possible to infer whether the contact member (245) is currently in or within the adjacent gap.

[0049] In an embodiment, for example, when the head (120) of the oral treatment device (100) includes a plurality of bristles (122), the contact member (245) is separate from the plurality of bristles (122). Thus, both the bristles (122) and the separate contact member (245) can come into contact with the user's teeth during use of the device (100). The contact member (245) may include, for example, a member having a higher rigidity than the bristles (122). By using a separate contact member (245), the properties of the contact member (245) can be selected and / or tuned so that the detection of adjacent gaps 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, so as to produce an easily detectable change in the measured vibration characteristics when the contact member (245) moves into or out of the adjacent gap. In some embodiments, the bristles themselves may have insufficient stiffness to produce such easily detectable changes, and increasing the stiffness of the bristles to achieve the effect may interfere with the brushing function of the bristles.

[0050] In an embodiment, where the oral treatment device includes a fluid delivery system (220) capable of delivering a working fluid to the user's oral cavity, for example, the contact member includes the nozzle, for example, the nozzle (124) described with reference to FIGS. 1a through 1c. Accordingly, the nozzle can function as both a means for the working fluid to be sprayed toward an adjacent gap and a contact member used for automatic detection of the adjacent gap [and thus triggering the spray].

[0051] In an embodiment, the IMU (240) is contained in the handle (110) of the device (100). By arranging the IMU (240) in the handle (110) of the device (100) instead of 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) may be relatively small compared to the handle (110), and if the IMU is contained in the head (120), undesirable architectural and / or structural changes may be required in the head (120) to accommodate the IMU (240). Additionally, in an embodiment, the head (120) of the device (100) can be detached from the handle (110) and is disposable, so it may be desirable for the user to periodically replace the head after use. Therefore, arranging the IMU (240) in the handle (110) instead of the head (120) can reduce the cost of replacement parts.

[0052] In an embodiment, the IMU (240) is included in the head (120) of the device (100). When the IMU (240) is arranged in the head (120) of the device (100), the IMU (240) is arranged closer to the contact member (245), so that a signal that is more easily detected can be generated compared to when the IMU (240) is arranged in the handle (110), and thus more accurate and / or reliable gap detection can be achieved.

[0053] In an embodiment, for example, if the oral treatment device (100) includes a fluid delivery system (220), a control signal for controlling the delivery of working fluid in response to adjacent gap detection is output to the fluid delivery system (220). Thus, during use of the device (100), the delivery of working fluid is controlled in response to automatic detection of adjacent gaps using the contact member (245) and the IMU (240) [during the same use of the device (100)]. Accordingly, the fluid delivery system (220) can be used more accurately and / or reliably. By improving the accuracy and / or reliability of the fluid delivery system (220), the amount of working fluid used is reduced and more effective processing is performed more quickly. In an embodiment, the control signal is output to the fluid delivery system (220) to cause the fluid delivery system to deliver working fluid to the adjacent gap. Thus, the injection of working fluid can be triggered immediately in response to the detection of adjacent gaps performed using the IMU (240) and the contact member (245). This improves the accuracy of working fluid injection, for example, by increasing the likelihood that the working fluid is actually injected into an adjacent gap rather than elsewhere.

[0054] In an embodiment, the vibration characteristic refers to ultrasonic vibrations generated by the oral treatment device (100). The ultrasonic vibrations may be generated as part of the toothbrushing function and / or plaque removal function of the device (100). In another example, the vibration characteristic refers to sound wave vibrations generated by the device (100) [e.g., generated by a motor configured to drive the movement of the device (100) head (120) relative to the device (100) handle (110). Thus, automated detection of adjacent gaps is provided by utilizing the existing functions of the device (100), and a separate means of generating vibration is not required.

[0055] In an embodiment, a received signal is processed to detect a change in the vibration characteristics of the oral processing device (100). Based on the detected change, it is determined whether the contact member (245) has moved into or out of an adjacent gap. The device (100) is controlled to perform an action based on the determination.

[0056] In an embodiment, the received signal includes accelerometer data. In an embodiment, the vibration characteristics include one or more of the amplitude and frequency of the oral processing device vibration. In an embodiment, the received signal is processed using one or more frequency filters to obtain a filtered signal. In an embodiment, one or more frequency filters include a low-pass frequency filter. Such a low-pass frequency filter can be used to reduce noise in the received IMU signal. This noise may be caused by, for example, vibration of the device, or manufacturing defects of the IMU (e.g., variation between different IMUs). Reducing noise using one or more frequency filters improves the reliability and / or accuracy of gap detection, for example, by improving the signal-to-noise ratio. In an embodiment, a moving average is applied to the received IMU signal so that signals corresponding to repetitive and / or regular rapid movements (e.g., corresponding to the "scrubbing motion" of the device) can be removed, and thus adjacent gap detection can be performed even when the device moves rapidly back and forth. In an embodiment, one or more amplitude thresholds are applied to a filtered signal for detecting adjacent gaps. These filters and / or thresholds are selected to increase the reliability and / or accuracy of gap detection by improving the signal-to-noise ratio compared to, for example, the "raw" signal received from the IMU (240). The filters and / or thresholds may be pre-set and / or modified or calculated during use of the device (100) to improve the accuracy of gap detection.

[0057] FIG. 4 illustrates a method (400) of operating an oral processing device according to an embodiment. The method (400) can be used to operate the oral processing device (100) described above with reference to FIG. 1a, 1b, and 2. In the embodiment of FIG. 4, the oral processing device (100) includes an image sensor device (230). In this embodiment, the image sensor device (230) includes an intraoral image sensor device. In the embodiment, the method (400) is performed at least partially by a controller (210).

[0058] In step 410, the intraoral image sensor equipment (230) generates image data representing at least a portion of the user's oral cavity while the user is using the oral processing device (100).

[0059] In an embodiment, the intraoral image sensor equipment (230) is at least partially included in the head (120) of the intraoral processing device (100). Since the head (120) of the device (100) is intended to deliver processing into the user's intraoral cavity, by arranging the intraoral image sensor equipment (230) at least partially in the head (120), the inside of the intraoral cavity can be imaged without the need to mount a separate intraoral camera [i.e., a camera mounted separately from the head (120)].

[0060] In an embodiment, the intraoral image sensor equipment (230) is at least partially contained in the handle (110) of the oral processing device (100). Accordingly, even if a part of the image sensor equipment (230) (e.g., one image sensor) is arranged to remain outside the user's oral cavity, the image sensor equipment (230) can still be referred to as "intraoral image sensor equipment." By arranging the image sensor equipment (230) at least partially in the handle (110) of the device (100), space on the device can be managed more efficiently. That is, since the head (120) of the device (100) may be relatively small compared to the handle (110), incorporating the image sensor equipment (230) into the head (120) may require changes to the architecture and / or structure of the head (120), which may be relatively complex and / or costly. Additionally, in the embodiment, the head (120) of the device (100) can be detached from the handle and is disposable, so it may be desirable for the user to periodically replace the head (120) after use. Accordingly, instead of arranging the entire image sensor equipment (230) on the head (120), arranging at least a portion on the handle (110) can reduce the cost of replacement parts.

[0061] In an embodiment, the intraoral image sensor equipment (230) includes a sensor and an aperture for receiving light and transmitting light to the sensor. The aperture is included in the head (120) of the intraoral processing device (100). For example, if the head (120) of the device (100) includes a set of bristles (122) for performing a brushing function, the aperture may be arranged behind the bristles (122) so that the bristles (122) do not obscure the aperture (i.e., do not block light from the aperture). In an embodiment, the image sensor equipment (230) includes a guide channel for guiding light from the aperture to the image sensor. For example, if the oral processing device (100) comprises a head (120), a handle (110), and a stem (130) connecting the head (120) and the handle (110), a guide channel may extend from an aperture to a sensor along the stem (130) (e.g., inside the stem). The guide channel may include, for example, a fiber optic cable. In an alternative embodiment, the stem (130) is hollow and sheathes an image sensor, and the image sensor is positioned behind the head (120) of the device (100). This reduces the distance between the aperture and the sensor while ensuring that the sensor is not contained within the (disposable) head (120).

[0062] In the embodiments, the image data includes red, green, and blue (RGB) image data. Other types of image data (e.g., black and white image data) may be used in alternative embodiments.

[0063] In step 420, the generated image data is processed to determine location data indicating the location of adjacent gaps between adjacent teeth in the user's oral cavity. The generated image data is processed using a trained classification algorithm configured to identify adjacent gaps. The trained classification algorithm is trained before using the oral processing device.

[0064] In step 430, while using the oral treatment device (100), the oral treatment device (100) is controlled so that treatment is delivered to the detected adjacent gap.

[0065] Accordingly, while the user is using the device (100), adjacent gaps can be automatically detected using the intraoral image sensor equipment (230) and a trained classification algorithm, and the delivery of processing can be controlled accordingly without requiring user input. For example, the user does not need to determine whether the device (100) is in a suitable location for processing delivery (e.g., a location close to the adjacent gap or a location within the adjacent gap). Instead, this determination is made automatically based on intraoral image data and can be performed substantially in real time. Processing intraoral image data using a trained classification algorithm improves the accuracy and / or reliability of adjacent gap detection and / or adjacent gap localization compared to cases where intraoral image data is not processed using such a trained algorithm. By automatically detecting the location of the device (100) relative to the adjacent gap and / or the adjacent gap during use, and using this information to control the delivery of processing at that time (i.e., during the same use of the device), the delivery of processing can be performed more accurately. Furthermore, using image data allows not only the detection of gaps but also the identification of their locations. Identifying the gap locations enables more accurate and / or reliable processing delivery compared to cases where the locations are not identified.

[0066] In an embodiment in which an oral treatment device (100) includes a fluid delivery system (220) for delivering a working fluid to the user's oral cavity, a control signal for controlling the delivery of the working fluid based on location data is output to the fluid delivery system (220). Accordingly, the delivery of the working fluid during use of the device (100) is controlled in response to automatic localization of adjacent gaps using an intraoral camera (250) and a trained classification algorithm [during the same use of the device (100)]. Accordingly, the fluid delivery system (220) can be used more accurately and / or reliably. In particular, the accuracy of fluid injection, that is, the likelihood that the working fluid is actually injected into an adjacent gap 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 processing is performed more quickly.

[0067] In an embodiment, the generated image data is processed using a sliding window. In this embodiment, position data is determined by detecting the presence of adjacent gaps within the sliding window. That is, the sliding window moves across the image to define sub-regions of the image, and it is determined whether a gap exists in each sub-region of the image. This is described in more detail below.

[0068] In an embodiment, the generated image data is processed by extracting one or more image features from the image data and determining location data using the extracted one or more image features. The image features may include, for example, texture-based image features. Since an image consists of highly correlated pixels, image feature extraction is used to obtain the most representative and informative (i.e., non-redundant) information of the image to facilitate the training of a classification algorithm and / or to reduce dimensionality.

[0069] In the embodiments, one or more image features are extracted using a discrete wavelet transform. The discrete wavelet transform can capture both frequency and positional information of the image. Generally, the image frequency of the gap region is higher than the image frequency of the tooth or gum region. Therefore, the discrete wavelet transform can generate a frequency map of the image that can be used to detect adjacent gaps. In the embodiments, the Haar wavelet is used, which has relatively lower computational complexity and less memory usage compared to other wavelets. The coefficients of the wavelet transform (or approximations thereof) can be used as the extracted image features. For example, the output of feature extraction based on the Haar wavelet applied to an image of size axa may include a horizontal wave h (a / 4 xa / 4), a vertical wave v (a / 4 xa / 4), and a diagonal wave d (a / 4 xa / 4). Other wavelets may be used in alternative embodiments.

[0070] The extracted features can be used in a sliding window applied to the image. For example, in an image subregion defined by the sliding window, after 2 x 2 pooling is performed for h, v, and d respectively, h, v, and d can be vectorized and combined into a single vector of size 1 x 108. This can be normalized along with the training data (e.g., trained mean and variance values) of the trained classification algorithm. A support-vector machine (SVM) can be used as a non-probabilistic non-linear binary classifier with a Gaussian radial basis function kernel and receives the normalized data from the previous step. The trained SVM includes support vectors with trained coefficients and biases determined in the previous training phase. For example, given a set of images along with ground truth labeling, a classification algorithm can be trained to assign new examples to one category (e.g., gap) or another category (e.g., not a gap).

[0071] In the embodiments, one or more image features are extracted using at least one of an edge detector, a corner detector, and a blob extractor. Extracting image features using this method can provide more accurate detection and / or localization of adjacent gaps compared to other methods.

[0072] In an embodiment, for example, if the oral treatment device (100) includes a user interface, the user interface provides an output based on location data. For example, the output may include a notification informing the user that an adjacent gap location has been identified, a notification indicating the location of the adjacent gap, a notification informing the user that a treatment delivery has been performed on the adjacent gap, and / or a notification instructing the user to adjust the position and / or orientation of the device so that a more accurate treatment delivery (e.g., injection of a working fluid) can be performed. The provided output may include, for example, visual, auditory, and / or tactile outputs.

[0073] In an embodiment, for example, if the oral processing device (100) includes a memory (260), one or more characteristics of adjacent gaps are stored in the memory (260) and used for subsequent processing and / or control of the oral processing device (100). For example, one or more stored characteristics may be used to compare adjacent gaps with adjacent gaps subsequently identified. In other cases, one or more stored characteristics are used to track adjacent gaps over time.

[0074] FIG. 5 illustrates a method (500) of operating an oral processing device according to an embodiment. The method (500) can be used to operate the oral processing device (100) described above with reference to FIG. 1a, 1b, and 2. In the embodiment of FIG. 5, the oral processing device (100) includes an image sensor device (240). In the embodiment, the method (500) is performed at least partially by a controller (210).

[0075] In step 510, image data is generated by the image sensor equipment (240). The image data represents a sequence of images representing at least a portion of the user's oral cavity. Thus, images of a portion of the oral cavity can be captured at multiple different points in time.

[0076] In step 520, image data is processed to determine motion parameters. The motion parameters represent the movement of the oral processing device (100) in the adjacent gap between adjacent teeth in the user's oral cavity.

[0077] In step 530, the oral processing device (100) is controlled to perform an action based on the determined motion parameters.

[0078] By determining movement parameters representing the movement of the oral treatment device with respect to an adjacent gap, the device (100) can be controlled more precisely and / or intelligently. In particular, by considering the movement of the device (100) with respect to the gap (or vice versa), treatment can be delivered to the gap more accurately and / or effectively.

[0079] In the embodiment, the oral processing device is controlled to deliver processing to a proximal gap based on determined motion parameters. Accordingly, the operation performed in step 530 may include delivering processing to an adjacent gap.

[0080] In the embodiment, processing transfer by the oral processing device (100) is prevented based on the determined motion parameter. Accordingly, the operation performed in step 530 may include preventing processing transfer to an adjacent gap.

[0081] In an embodiment, the determined motion parameter represents the predicted location of an adjacent gap for the oral processing device (100) at a predetermined future time. The predetermined future time may be the earliest time at which processing delivery can be activated. By predicting the gap location at this predetermined future time, the likelihood of processing being successfully (e.g., accurately) delivered to the gap can be determined. If the likelihood is determined to be high (e.g., exceeding a predetermined threshold), processing delivery may be allowed. However, if the likelihood is determined to be low (e.g., below a predetermined threshold), processing delivery may be prevented. This allows the device (100) to be used more efficiently in that processing delivery is triggered only when it is determined, based on the motion parameter, that the likelihood of the gap being accurately and / or effectively processed is sufficiently high.

[0082] In an embodiment, the determined motion parameter represents a predicted future point in time when the adjacent gap has a preset position relative to the oral processing device (100). The preset position may be, for example, a position within the path of a working fluid jet from a fluid delivery system. Accordingly, to increase the possibility of successful and accurate adjacent gap processing, the delivery of processing can be controlled (e.g., delayed) based on the determined motion parameter. This enables the oral processing device (100) to be used more efficiently.

[0083] In an embodiment, the determined motion parameter represents the speed and / or acceleration of the oral processing device (100) relative to an adjacent gap. The determined speed and / or acceleration can be used to track the trajectory of the gap relative to the device (100), thereby increasing the accuracy of the processing delivery.

[0084] In an embodiment in which an oral treatment device (100) includes a fluid delivery system (220) for delivering a working fluid to the user's oral cavity, a control signal for controlling the delivery of the working fluid based on determined motion parameters is output to the fluid delivery system (220). Thus, the operation performed in item 530 may include the control of the fluid delivery system (220). In this way, the delivery of the working fluid during device use is controlled based on the determined movement of the device relative to the gap (during the same use of the device). This allows the fluid delivery system to be used more accurately and / or reliably. In particular, the accuracy of fluid injection (i.e., the probability that the working fluid is actually injected into an adjacent gap rather than elsewhere) is increased. For example, there may be a specific latency between the time when an adjacent gap is detected and the time when the working fluid can be delivered into the gap. This latency may be due to data processing, signal transmission between different components and / or devices, operation of the fluid delivery system (220), etc. The occurrence of a delay means that when the fluid delivery system injects the working fluid, the detected gap may not already be in the path of the injected fluid. However, by considering the movement of the device (100) regarding the gap, this movement can be corrected, and thus the accuracy of the fluid injection can be increased. For example, the injection can be delayed until the gap is within 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 more effective processing is performed more quickly.

[0085] In an embodiment, the image sensor equipment (230) is at least partially included in the head (120) of the oral processing device (100). Since the head (120) of the device (100) is intended to deliver processing into the user's oral cavity, by arranging the image sensor equipment (230) at least partially in the head (120), the inside of the oral cavity can be imaged without the need to mount a separate camera [i.e., a camera mounted separately from the head (120)].

[0086] In an embodiment, the image sensor equipment (230) is at least partially included in the handle (110) of the oral processing device (100). By arranging the image sensor equipment (230) at least partially in the handle (110) of the device (100), the space on the device can be managed more efficiently as previously discussed, and the cost of replacement parts [i.e., the head (120)] can be reduced.

[0087] In an embodiment, the image sensor equipment (230) includes an intraoral camera. The intraoral camera may operate to capture digital images inside the user's mouth. These images are subsequently processed to track the movement of the device relative to adjacent gaps (or vice versa). Accordingly, the inside of the user's mouth is imaged during the use of the device (100). In some cases, the intraoral camera may operate to generate image data.

[0088] In an embodiment, image data is processed to detect adjacent gaps. The image data is processed first to detect the gaps and second to dynamically track the trajectory of the gaps relative to the device (100). For example, the gaps can be detected in the first image of an image sequence, and subsequent images of the image sequence can be used to track the movement of the gaps, for example, represented by motion parameters.

[0089] In the embodiment, adjacent gaps are tracked between frames by comparing the movement and / or displacement of image pixels between frames. For example, pixels of the first frame in the sequence I(x, y, t) The pixel of the second frame within the sequence I(x+dx, y+dy, t+dt) Compared to, movement between frames, that is, pixels over time dt during (dx, dy) It is confirmed that it has moved by a certain amount. The location of the gap can be predicted based on the displacement calculated in the first frame and the second frame [i.e., the current frame and the previous consecutive frame(s)]. Since teeth are hard objects, the displacement of pixels within the gap area between two frames is similar to the displacement of pixels within the tooth area. Therefore, the gap can be tracked even if the gap itself does not exist in one or more images. An optical flow technique is used to estimate the velocity of the gap (in pixels / second) for the device (100), and based on the known time and velocity between frames, the location of the gap at a preset future point in time can be predicted.

[0090] In an embodiment, the adjacent gap does not exist within at least one image of the image sequence. In this embodiment, the location of the adjacent gap for said at least one image of the image sequence is estimated based on the location of the adjacent gap within said at least one other image of the image sequence. Thus, the trajectory of the gap can be tracked even if the gap does not exist within the image (i.e., is not visible). For example, the gap may be obscured by other objects in some images. In an embodiment, an optical flow technique is used to determine the velocity of pixels and / or objects between images in the sequence. Subsequently, based on the calculated velocity, the location of the gap in the second image, and the time between the first and second images, the location of the gap in the first image, where the gap itself does not exist, can be estimated.

[0091] In an embodiment, motion parameters are determined based on a signal output by an IMU. For example, if the oral processing device (100) includes an IMU (240), the IMU (240) may be configured to output a signal indicating the position and / or movement of the oral processing device (100) relative to the user's oral cavity. For example, the IMU (240) may be used to determine the angular motion of the device (100) relative to a gap. This signal may be combined with image data and used to determine motion parameters.

[0092] FIG. 6 illustrates a method (600) of operating an oral processing device according to an embodiment. The method (600) can be used to operate the oral processing device (100) described above with reference to FIG. 1a, 1b, and 2. In the embodiment of FIG. 6, the oral processing device (100) includes an image sensor device (230). The image sensor device (230) can be operated to generate image data representing at least a portion of the user's oral cavity. In the embodiment, the method (600) is performed at least partially by a controller (210).

[0093] In step 610, the generated image data is processed to identify adjacent gaps between adjacent teeth in the user's oral cavity.

[0094] In step 620, at least one characteristic of an identified adjacent gap is compared with at least one characteristic of one or more previously identified adjacent gaps for the user's oral cavity. In the embodiments, at least one characteristic of an identified gap includes features expected to differ between different gaps and / or features unique to the identified gap. Thus, at least one characteristic can be used to distinguish the gaps. At least one characteristic may include visual characteristics. In the embodiments, at least one characteristic of an identified adjacent gap represents: at least one of the shape of the identified adjacent gap, the appearance of the identified adjacent gap, the location of the identified adjacent gap, or any distinctive feature of the identified adjacent gap. In the embodiments, at least one characteristic of an identified gap represents, for example, a frequency characteristic based on a wavelet transform applied to an image of the identified gap.

[0095] In step 630, the oral processing device (100) is controlled to perform an action based on the comparison result.

[0096] By comparing the characteristics of an identified adjacent gap with the characteristics of one or more adjacent gaps previously identified for the user, the device (100) is controlled in a more intelligent and / or flexible manner. In particular, a determination can be made as to whether the identified gap was previously identified during the current oral processing session [i.e., while the user is using the device (100)]. Since this determination can be performed substantially in real time, the device (100) can be controlled quickly and responsively. Thus, even if imaging conditions have changed since the previous identification, the previously identified gap can be identified again.

[0097] In the embodiment, a newly identified gap is treated differently from a previously identified gap. That is, the device (100) may be controlled in a first manner when the identified gap is determined to be a newly identified gap, and may be controlled in a second different manner when the identified gap is determined to be a previously identified gap (or a similar gap). Depending on how the user operates the device (100), a specific gap may be encountered once or multiple times during an oral processing session. Thus, the device (100) can adapt to the user's behavior by treating the newly identified gap differently from the previously identified gap.

[0098] In an embodiment, a similarity metric is calculated based on the comparison result. The similarity metric represents the level of similarity between an identified adjacent gap and one or more previously identified adjacent gaps. In this embodiment, the oral processing device (100) is controlled based on the determined similarity metric. The similarity metric may indicate whether the identified gap is identical or different from one or more previously identified gaps. That is, the similarity metric may indicate whether the identified gap is a newly identified gap or a previously identified gap. If it is determined that the gap has not been previously encountered during the current oral processing session, the gap may be "newly identified." That is, the gap may have been identified in a previous oral processing session, but if the gap has not been previously encountered in the current session, it may still be designated as a newly identified gap. In an embodiment, the similarity metric is compared to a threshold. If the similarity metric is below the threshold, the gap is designated as a newly identified gap. If the similarity metric exceeds the threshold, the gap is designated as a previously identified gap.

[0099] In an embodiment, corresponding to a similarity metric indicating that an identified adjacent gap is different from one or more previously identified adjacent gaps, the device (100) is controlled to deliver processing to the identified adjacent gap. Thus, the operation performed in item 630 may include delivering processing to the identified gap. In this way, when the identified gap is determined to be a newly identified gap, processing delivery is triggered.

[0100] In an embodiment, image data representing an identified adjacent gap is stored in memory (e.g., for use in subsequent identification and / or comparison of adjacent gaps) corresponding to a similarity metric indicating that the identified adjacent gap is different from one or more previously identified adjacent gaps. Thus, the gap can be compared with subsequently identified gaps to determine whether the subsequently identified gaps have been previously encountered. In an embodiment, the image data is stored in a library or data bank containing image data and / or other representative data corresponding to the user's previously identified gaps. The image data may be stored in the device (100) or output to be transmitted to be stored in a remote device, for example, via a network.

[0101] In an embodiment, corresponding to a similarity metric indicating that an identified adjacent gap is identical to at least one of one or more previously identified adjacent gaps, the oral processing device (100) is controlled to prevent processing from being transferred to the identified adjacent gap. Thus, the operation performed in item 630 may include preventing processing transfer. In this way, repetitive processing of the same gap during a single oral processing session can be reduced, and in some cases, completely prevented. That is, each gap is processed only once during an oral processing session. This allows the oral processing device (100) to be used more efficiently. For example, if the processing involves the transfer of working fluid through a fluid transfer system (220), reducing repetitive processing of the same gap reduces the amount of working fluid used. In an alternative embodiment, processing transfer is not prevented corresponding to a similarity metric indicating that an identified gap is identical to at least one of previously identified gaps.

[0102] In an embodiment, corresponding to a similarity metric indicating that an identified adjacent gap is identical to at least one of one or more previously identified adjacent gaps, the time elapsed since at least one of the one or more previously identified adjacent gaps was previously identified is determined. The determined elapsed time is compared with a preset threshold. In this embodiment, the oral processing device (100) is controlled based on the result of comparing the determined elapsed time with the preset threshold. Thus, the control of the device (100) may vary depending on how recently the gap was previously identified.

[0103] In an embodiment, in response to the determined elapsed time being longer than a preset threshold, the oral processing device (100) is controlled to deliver processing to an identified adjacent gap. Thus, if a preset time has elapsed since the previous gap processing, repetitive processing may be performed on the gap. In an embodiment, in response to the determined elapsed time being shorter than a preset threshold, the oral processing device (100) is controlled to prevent processing from being delivered to an identified adjacent gap. Thus, if a preset time has not elapsed since the previous gap processing, repetitive processing is not performed on the gap. For example, if a user moves the device (100) back and forth with a 'scrubbing' motion, the gap may be encountered twice in a relatively short period of time. In this case, processing the gap multiple times may not be effective or / or efficient. However, if the user returns the device (100) to a previously processed gap at a substantially later time during the session, it can be inferred that processing the additional gap is desirable (e.g., that the previous processing of the gap was unsuccessful).

[0104] In an embodiment, the generated image data is processed using a trained classification algorithm configured to detect adjacent gaps. Using this trained algorithm enables more accurate and / or reliable gap detection compared to not using the trained algorithm. In an embodiment, the classification algorithm includes a machine learning algorithm. This machine learning algorithm can be improved through experience and / or training (e.g., increasing the accuracy and / or reliability of classification).

[0105] In an embodiment, the generated image data is processed to determine at least one characteristic of the identified adjacent gaps. In an embodiment, at least one characteristic is determined by processing the generated image data using a machine learning algorithm. The machine learning algorithm is trained to identify information to be used to distinguish adjacent gaps. This information includes features representing the gaps, namely non-overlapping features and / or features predicted to differ from gap to gap. The identified information may include at least one characteristic of the gaps. In an embodiment, this machine learning algorithm (or one or more different machine learning algorithms) may also be used to determine at least one characteristic of one or more previously identified gaps (e.g., features that may be used to represent and / or distinguish previously identified gaps, and features used to compare previously identified gaps with the currently identified gaps). In an alternative embodiment, features unique to the gaps are extracted from the raw image data without using a machine learning algorithm.

[0106] In an embodiment, the image sensor equipment (230) includes an intraoral camera. In an embodiment, the image sensor equipment (230) is at least partially included in the head (120) of the oral processing device (100). Since the head (120) of the device (110) is intended to deliver processing into the user's oral cavity, by arranging the image sensor equipment (230) at least partially in the head (120), the inside of the oral cavity can be imaged without the need to mount a separate camera.

[0107] In an embodiment, the image sensor equipment (230) is at least partially included in the handle (110) of the oral processing device (100). By arranging the image sensor equipment (230) at least partially in the handle (110) of the device (100), the space on the device can be managed more efficiently as previously discussed, and the cost of replacement parts [i.e., the head (120)] can be reduced.

[0108] In an embodiment in which the oral treatment device includes a fluid delivery system (220) for delivering a working fluid to the user's oral cavity, a control signal for controlling the delivery of the working fluid based on a determined comparison result is output to the fluid delivery system (220). Accordingly, the operation performed in item 630 may include the control of the working fluid delivery (e.g., inducing and / or preventing the delivery of the working fluid). In an embodiment, the fluid delivery system (220) includes a fluid reservoir for storing the working fluid within the oral treatment device (100). Accordingly, by comparing the identified gap with previously identified gaps, the repetitive injection of fluid into the same gap is reduced, and the frequency of replenishing the fluid reservoir may be reduced.

[0109] FIG. 7 illustrates a method (700) of operating an oral treatment device according to an embodiment. The method (700) can be used to operate the oral treatment device (100) previously described with reference to FIG. 1a, 1b, and 2. In the embodiment of FIG. 7, the oral treatment device (100) includes an IMU (240). The IMU (240) may be operated to output a signal according to the position and / or movement of the oral treatment device (100). In this embodiment, the oral treatment device (100) also includes a fluid delivery system (220) for delivering a working fluid to the user's oral cavity. In the embodiment, the method (700) is performed at least partially by a controller (210).

[0110] In step 710, a signal received from the IMU (240) indicating the position and / or movement of the oral processing device (100) relative to the user's oral cavity is processed.

[0111] In step 720, based on the processing of step 710, a control signal for controlling the delivery of the working fluid is output to the fluid delivery system (220).

[0112] Accordingly, the delivery of the working fluid by the fluid delivery system (220) is controlled based on the IMU signal. Accordingly, the accuracy of fluid delivery (e.g., injection of the working fluid) can be increased compared to the case where the IMU signal is not used to control the fluid delivery system (220).

[0113] In an embodiment, the control signal may operate to prevent the transfer of working fluid by the fluid transfer system (220). By selectively preventing the transfer of working fluid based on the IMU signal, less working fluid is used compared to the case where the transfer is not selectively prevented. Thus, the efficiency of the device (100) is improved.

[0114] In an embodiment, a signal received from the IMU is processed to determine whether the oral processing device is moving according to a preset type of movement. In response to this determination, a control signal is output to the fluid delivery system (220) to prevent the delivery of working fluid. Thus, the delivery of working fluid to the user's oral cavity is selectively prevented based on how the user moves the device (100). This allows the device (100) to be used more efficiently and / or processed more effectively by preventing the working fluid from being sprayed when, for example, the device (100) is moved in a specific manner. For example, if the device (100) is moving according to a preset type of movement, the possibility of the fluid delivery system (220) spraying incorrectly and / or damage caused by the spraying of fluid may increase. In an embodiment, a signal received from the IMU (240) is processed using a trained classification algorithm (e.g., a machine learning algorithm) configured to determine whether the device (100) is moving according to a preset type of movement.

[0115] In the embodiment, the movement of the oral treatment device (100) according to a preset movement type interferes with the use of the oral treatment device (100) for oral treatment by the user. Therefore, when the device (100) is used in a manner that interferes with the use of the device (100) for oral treatment, fluid delivery can be selectively prevented. When the device is moved in this manner, for example, the possibility of successful treatment is reduced due to a decrease in the accuracy with which the fluid delivery system (220) delivers the working fluid to the target. This means, for example, that there is a high probability that the working fluid will be wasted as the working fluid is injected by the fluid delivery system (220) but does not lead to successful treatment. By selectively preventing fluid delivery when the device (100) moves according to a preset movement type, the working fluid can be used more efficiently.

[0116] In an embodiment, the predetermined movement type includes a scrubbing movement. If the device (100) is moved according to the scrubbing movement type, the accuracy with which the fluid delivery system (220) delivers the working fluid to a target (e.g., an adjacent gap) is reduced, and the likelihood of incorrect injection increases. This means that the working fluid is more likely to be wasted. Therefore, by selectively preventing fluid delivery when the device (100) moves in a scrubbing motion, the working fluid can be used more efficiently. In an alternative embodiment, the predetermined movement type includes other movement types.

[0117] In an embodiment, a 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) will provide successful treatment may depend on the orientation of the device (100). For example, if a working fluid needs to be injected into an adjacent gap between adjacent teeth to dislodge foreign matter, the likelihood of success may be higher (with fewer attempts) if the device (100) is oriented such that the nozzle of the fluid delivery system (220) extends substantially perpendicularly to the buccal or lingual surface of the tooth and faces said surfaces. On the other hand, if the nozzle extends substantially perpendicularly to the occlusal surface of the tooth and the device (100) is oriented toward the occlusal surface, the likelihood of successfully dislodgement of foreign matter is reduced. This means, for example, that there is a higher likelihood of working fluid being wasted as the working fluid is injected by the fluid delivery system (220) but does not lead to successful processing. By controlling the delivery of working fluid according to the determined orientation of the device (100), the working fluid can be used more efficiently.

[0118] In an embodiment, the orientation of the device (100) is compared with a jetting angle threshold. The jetting angle threshold is a threshold for determining whether working fluid transfer should be prevented or allowed based on the orientation of the device (100) head (120). For example, if the orientation of the head (120) exceeds the jetting angle threshold, fluid transfer may be allowed, and if the orientation of the head (120) is below the jetting angle threshold, fluid transfer may be prevented. In an embodiment, the jetting angle threshold may be determined for a user based on an IMU signal. Since different users may orient and / or move the device (100) differently along a pass, the jetting angle threshold may be optimized for a specific user by analyzing the orientation of the head (120) as the user moves the device (100) along a row of teeth. As used herein, the term "pass" refers to the movement of the device (100) head (120) along a row of teeth.

[0119] In an embodiment, a signal received from the IMU (240) is processed to determine a change in the orientation of the oral treatment device (100) during use of the oral treatment device (100). Based on the determined change in the orientation of the oral treatment device (100), a control signal is output to the fluid delivery system (220). Accordingly, fluid delivery can be controlled in response to the change in orientation of the device (100) during use. For example, the device (100) can be moved from a first orientation (e.g., an orientation where the nozzle is substantially perpendicular to the occlusal surface of the tooth and faces the occlusal surface) where the probability of successful treatment is relatively low, to a second orientation (e.g., an orientation where the nozzle is substantially perpendicular to the lingual or buccal surface of the tooth and faces said surfaces) where the probability of successful treatment is relatively high. When the device (100) is in the first orientation, fluid delivery can be prevented to reduce the consumption of working fluid by spraying working fluid to a location where the probability of successful treatment is relatively low. When the device (100) moves to a second orientation, the prevention of fluid transfer may be stopped. Likewise, when the device (100) moves from the second orientation to the first orientation, fluid transfer may be selectively prevented.

[0120] In an embodiment, the head (120) of the device (100) may be operated to move along a row of teeth between the first end and the second end of the row, and the fluid delivery system (220) is at least partially included in the head (120). In an embodiment, a signal received from the IMU (240) is processed to determine the trajectory of the oral processing device (100) head (120) between the first end and the second end of the row. Based on the determined trajectory, a control signal is output to the fluid delivery system (220). By controlling the fluid delivery system (220) based on the trajectory of the head (120) moving along the row of teeth, the device (100) can be controlled in a more intelligent and / or flexible manner. In particular, if the trajectory indicates a relatively low probability of successful processing using the fluid delivery system (220), fluid delivery may be prevented (thereby preventing the waste of working fluid).

[0121] In an embodiment, a signal received from the IMU (240) is processed to determine a change in orientation of the head (120) of the oral processing device (100) while the head (120) of the oral processing device (100) moves between the first end of the row and the second end of the row. Based on the determined change in orientation of the head (120), a control signal is output to the fluid delivery system (220). Thus, fluid delivery can be controlled in response to a change in orientation of the head (120) while the head (120) moves along the row of teeth. For example, the orientation of the head (120) can change while a user moves the device (100) along the row of teeth, for example, the user can rotate the device (100) while the device (100) moves along the row of teeth. By taking into account such changes in orientation, for example, by delivering the working fluid when the probability of successful processing is judged to be relatively high based on the orientation and preventing injection when the probability of successful processing is judged to be relatively low, the fluid delivery system (220) can be made more accurate and / or efficient.

[0122] In an embodiment, a signal received from the IMU (240) is processed to determine that the movement of the oral processing device (100) to the oral cavity has stopped. In response to this determination, a control signal is output to the fluid delivery system (220), causing the fluid delivery system (220) to deliver the working fluid. Thus, the user can move the device (100) along the row of teeth and pause briefly when the device (100) comes into contact with an adjacent gap that the user wishes to process. By using the IMU signal to detect this pause and automatically triggering the fluid delivery system (220) accordingly, the need for user input to trigger the fluid delivery system (220) is reduced, thereby improving the functionality of the device (100) and enhancing the user experience.

[0123] In an embodiment, a signal received from the IMU (240) is processed to detect adjacent gaps between adjacent teeth in the user's oral cavity. In response to the detection of adjacent gaps, a control signal is output to the fluid delivery system (220). In an embodiment, the control signal is output to the fluid delivery system (220) to cause the fluid delivery system to deliver working fluid to the detected adjacent gap. Thus, adjacent gaps can be automatically detected based on the IMU signal in substantially real-time during use of the device (100), and working fluid can be delivered to the detected gap during use of the device (100). In some cases, the user may not be aware that a specific gap exists, but the gap can still be detected by the device based on the IMU signal. Additionally, by specifically triggering the injection of working fluid when a gap is detected, the efficiency and / or accuracy of the fluid delivery system (220) is increased.

[0124] In an embodiment, the IMU signal is processed using a velocity and / or position estimation algorithm. For example, the velocity and / or position estimation algorithm may be configured to estimate the velocity of the device (100) for use in detecting a velocity that changes rapidly in any direction (e.g., to detect scrubbing motion). In an embodiment, the velocity and / or position estimation algorithm is configured to receive accelerometer and gyroscope signals from the IMU. These signals may be processed individually or fused into a single data stream for use by the algorithm. For example, determining whether the device is moving along a row of teeth, determining the position of the device relative to the oral cavity, and / or determining the speed of the device may be performed using the velocity and / or position estimation algorithm. The velocity and / or position estimation algorithm may be implemented using software or hardware [e.g., an Application-Specific Integrated Circuit (ASIC)], or a combination of hardware and software. The velocity and / or position estimation algorithm may be used in various methods described herein.

[0125] An IMU may have issues due to noise, bias, and / or drift, which, if not properly corrected, can lead to inaccurate calculation results. For example, gyroscope signals may drift over time, accelerometers may be biased by gravity, and noise may occur in both gyroscope and accelerometer signals. In an embodiment, at least some of the noise in the IMU signal is removed using filtering (e.g., high-pass and / or low-pass and / or median filters). In an embodiment, the filter is used to correct gyroscope drift and / or compensate for gravity to obtain linear velocity, which can then be integrated to obtain position and / or displacement. The velocity and / or position measurements may include measurements for all three axes individually, or a combination of directional components may provide velocity magnitude and / or position magnitude.

[0126] In an embodiment, an IMU signal is processed to generate a user behavior profile for a user. This profile indicates how the user uses the device (100) (e.g., routines based on movement, orientation, speed, etc.). For example, the user behavior profile can be used to provide personalized advice to the user. The user behavior profile may be modified and / or updated as new IMU data is acquired.

[0127] In an embodiment, the IMU signal is combined with intraoral image data generated by an image sensor device, for example, the image sensor device (230) described above. By controlling the fluid delivery system (220) using both the IMU signal and the intraoral image data, the accuracy of the fluid delivery system (220) can be further improved compared to the case where the intraoral image data is not used.

[0128] FIG. 8 illustrates a method (800) of operating an oral processing device according to an embodiment. The method (800) may be used to operate the oral processing device (100) described above with reference to FIG. 1a, FIG. 1b, and FIG. 2. In the embodiment of FIG. 8, the oral processing device (100) includes a head (120) for use in processing a user's oral cavity. The oral cavity includes a plurality of oral cavity zones. In this embodiment, the oral processing device (100) includes an IMU (240). The IMU (240) may be operated to output a signal according to the position and / or movement of the head (120) of the oral processing device (100). In the embodiment, the method (800) is performed at least partially by a controller (210).

[0129] In step 810, a signal indicating the position and / or movement of the head (120) of the oral processing device (100) for the user's oral cavity is received from the IMU (240).

[0130] 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 region among a plurality of oral regions where the head (120) of the oral processing device (100) is located. The acquired classification data indicates the oral region where the head (120) of the oral processing device (100) is located.

[0131] In step 830, the oral processing device (100) is controlled to perform an action using classification data.

[0132] In an example, the plurality of oral regions includes more than two oral regions. In an example, the plurality of oral regions includes more than four oral regions. In an example, the plurality of oral regions includes 12 oral regions. In an example, the plurality of oral regions includes 18 oral regions.

[0133] In an embodiment, a given oral region among a plurality of oral regions represents: a quadrant or sextant of the user's oral cavity; and a tooth surface selected from a list including buccal, lingual, and occlusal surfaces. Thus, there may be 18 distinct oral regions corresponding to six oral sextants, each having three tooth surfaces. In an alternative embodiment, the plurality of oral regions includes more than 18 oral regions.

[0134] By using the IMU signal as input to a trained non-linear classification algorithm, the oral region where the head (120) is located can be identified without requiring user input. Thus, the device (100) can autonomously identify how the user uses the device (100) and adapt accordingly. For example, one or more operating settings of the device (100) can be controlled based on the identified oral region. Additionally, notifications can be provided to the user regarding the location of the head (120) of the device (100) within the oral cavity, how much time is spent in each region, etc. This information can also be used to determine whether the oral region where the head (120) is located has been previously visited during the current oral processing session. This information not only provides direct user feedback but can also facilitate the creation of a behavioral profile indicating the user's usage trends of the device (100), based on, for example, the time spent in each oral region, whether there are any missed oral regions, etc. In addition, using a trained algorithm allows the position of the head (120) to be determined more accurately and / or reliably compared to when the trained algorithm is not used. That is, the spatial resolution for determining the position of the head (120) is improved by using a trained algorithm. Furthermore, a non-linear classification algorithm can be used to distinguish factors that cannot be linearly separated. Therefore, by using a non-linear classification algorithm to obtain classification data, the classification data can be determined more accurately and / or reliably.

[0135] In the embodiments, the classification algorithm includes a machine learning algorithm. Such machine learning algorithms can be improved through experience and / or training (e.g., increasing the accuracy and / or confidence of classification).

[0136] In an embodiment, the oral processing device includes a machine learning agent. The machine learning agent includes a classification algorithm. Thus, the classification algorithm may be located on the oral processing device (100). Since oral region identification is performed on the device (100), there is no need to transmit and / or receive data with other devices, so the latency is reduced compared to the case where the classification algorithm is not located on the device (100). Therefore, oral regions can be identified more quickly, so the time required to take corrective action and / or provide output through a user interface can be reduced. In an alternative embodiment, the classification algorithm is located on a remote device. Such a remote device may have more processing resources than, for example, the oral processing device (100).

[0137] In an embodiment, the oral processing device (100) is controlled to deliver processing to the user's oral cavity based on classification data. Accordingly, the operation performed in item 830 may include delivering processing to the user's oral cavity.

[0138] In an embodiment in which an oral treatment device includes a fluid delivery system (220) for delivering a working fluid to a user's oral cavity, a control signal for controlling the delivery of the working fluid based on classification data may be output to the fluid delivery system (220). Accordingly, the operation performed in item 830 may include the control of the delivery of the working fluid by the fluid delivery system (220). In an embodiment, the control signal may operate to prevent the delivery of the working fluid based on classification data. This improves the efficiency and / or accuracy of the fluid delivery system (220) by delivering (or not delivering) the treatment considering the determined position within the oral cavity of the device (100) head (120).

[0139] In an embodiment, the user interface (250) provides an output based on classification data. Accordingly, an action performed in item 830 may include providing an output through the user interface (250). For example, such an output may include a notification informing the user to spend more time in a specific oral area to improve processing delivery using the device (100).

[0140] In an embodiment, the user interface (250) provides output while processing the user's oral cavity using the oral processing device (100). By having the user interface (250) provide output while using the device (100) rather than after the oral processing session is completed, feedback can be provided more quickly. For example, the output can be provided by the user interface (250) in substantial real-time. Accordingly, the user can adjust their behavior, such as taking corrective measures while using the device (100), thereby improving the effectiveness of the processing delivery.

[0141] In an embodiment, the user interface (250) provides an output after processing the user's oral cavity using the oral processing device (100). 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) over the oral processing session can be analyzed, and feedback on the entire session can then be provided to the user (e.g., advising the user to spend more time processing specific oral areas). This feedback encourages the user to adjust their behavior in subsequent sessions.

[0142] In the embodiments, the output provided by the user interface includes auditory, visual, and / or tactile outputs. For example, the output may be provided through a display, a speaker, and / or a haptic actuator.

[0143] In an embodiment, the user interface is included in a remote device, and a signal is output to the remote device so that the user interface provides an output. The user interface on this remote device may be more versatile than the user interface on the oral processing device (100) itself, which is handheld and / or has limited space for the user interface.

[0144] In an embodiment, the oral processing device (100) includes a user interface (250). By providing a user interface (250) on the oral processing device (100), the need for communication between different devices can be avoided, so that output can be generated more quickly and received more quickly by the user compared to the case where the user interface (250) is not included on the oral processing device (100). Additionally, providing a user interface (250) on the oral processing device (100) can increase the likelihood that the user will receive feedback immediately. For example, the user may not be in the same location as the remote device while using the oral processing device (100), and therefore the user may not be able to immediately see or hear notifications on the remote device.

[0145] In an embodiment, a user interface [e.g., on the device (100) or a remote device] provides an output including a notification informing the user to position the head (120) of the oral processing device (100) in a pre-set oral region. This notification is provided when the oral processing session starts. By providing this notification to the user, the non-linear classification algorithm recognizes the starting position of the head (120) [i.e., the oral region where the head (120) is located at the start of the session]. This can be used as a constraint for the classification algorithm and thus increase the accuracy and / or reliability of the algorithm in determining the subsequent oral position of the head (120).

[0146] In an embodiment, the classification algorithm is modified using signals received from the IMU (240). That is, the classification algorithm can be trained and / or further trained using signals generated by the IMU (240). Modifying the classification algorithm can improve the accuracy and / or reliability of the algorithm through experience and / or more training data. Additionally, as the classification algorithm is modified, the classification algorithm can be tailored to the user. By dynamically retraining the classification algorithm using the generated IMU signals as training data, the classification algorithm can identify the oral region where the head (120) of the device (100) is located with greater reliability.

[0147] In an embodiment, the classification data is stored in memory (260). Accordingly, the data can be used later [e.g., for analysis after processing and / or for generating a behavioral profile for the user's device (100) usage]. In an embodiment, the classification data is output for transmission to a remote device (e.g., a user device such as a mobile phone, tablet, laptop, personal computer, etc.).

[0148] In an embodiment, training data is received from a remote device. Training data may be received from a network (e.g., 'cloud'). Such training data may include IMU data and / or classification data associated with other users. Such training data may include, for example, crowd-sourced data. In an embodiment, such training data has a greater amount than IMU data and / or classification data obtained by directly using the oral processing device (100). Modifying the classification algorithm using training data from a remote device can increase the accuracy and / or reliability of the classification algorithm compared to the case where such training data is not used.

[0149] FIG. 9 illustrates a method (900) of operating an oral processing device according to an embodiment. The method (900) may be used to operate the oral processing device (100) described above with reference to FIG. 1a, 1b, and 2. In the embodiment of FIG. 9, the oral processing device (100) includes a head for use in processing a user's oral cavity. In this embodiment, the oral processing device (100) also includes an IMU (240) and an image sensor device (230). In the embodiment of FIG. 9, the image sensor device (230) includes an intraoral image sensor device. In the embodiment, the method (900) is performed at least partially by a controller (210).

[0150] In step 910, using the IMU (240), a signal is generated according to the position and / or movement of the head of the oral processing device (100) relative to the user's oral cavity.

[0151] In step 920, image data representing at least a portion of the user's oral cavity is generated using image sensor equipment (230). It will be understood that steps 910 and 920 may be performed substantially simultaneously or sequentially in either order.

[0152] In step 930, the generated signal and generated image data are processed using a classification algorithm trained to determine the intraoral position of the head (120) of the oral processing device (100).

[0153] In step 940, the oral processing device (100) is controlled to perform an action based on a determined position within the oral cavity.

[0154] By using IMU signals and image data as inputs to a trained classification algorithm, the intraoral position of the device (100) head (120) can be determined without requiring user input. Thus, the device (100) can autonomously identify how the user uses the device (100) and adapt accordingly. This allows the device (100) to be controlled more intelligently. For example, one or more operating settings of the device (100) can be controlled according to the determined intraoral position. Additionally, using image data in combination with IMU data allows for more accurate determination of the intraoral position of the head (120) compared to cases where image data and / or IMU data are not used. For example, using image data in combination with IMU data improves the spatial resolution for determining the intraoral position.

[0155] In an embodiment, the oral cavity comprises a plurality of oral regions. In this embodiment, generated signal and generated image data are processed to identify the oral region where the head (120) is located among the plurality of oral regions. The oral processing device (100) is controlled to perform an action based on the identified oral region. In an embodiment, as previously discussed, a given oral region among the plurality of oral regions represents: a quadrant or sextate of the oral cavity; and a tooth surface selected from a list including the buccal, lingual, and occlusal surfaces. Through this, the user can receive notifications, for example, about where the head (120) of the device (100) is located in the oral cavity, how much time is spent in each oral region, etc. This information can also be used to determine whether the oral region where the head (120) is located has been previously visited during the current oral processing session. This information not only provides direct user feedback but can also facilitate the creation of a behavioral profile indicating the user's usage tendencies of the device (100), for example, based on the time spent in each oral region, whether there are any missed oral regions, etc.

[0156] In an embodiment, the oral cavity comprises a plurality of teeth, and the generated signal and generated image data are processed to identify the tooth adjacent (e.g., closest) to the head (120) of the oral processing device (100) among the plurality of teeth. The oral processing device (100) is controlled to perform an action based on the identified tooth. Thus, the position of the head (120) of the device (100) within the oral cavity is determined on a per-tooth level. Accordingly, user feedback may be provided, for example, by informing the user of a specific tooth that requires additional processing. In this way, a more granular and / or customized level of feedback (e.g., with higher spatial resolution) may be provided compared to the case where the tooth adjacent to the head (120) of the device (100) is not identified.

[0157] In the embodiment, the generated signal and generated image data are processed to identify adjacent gaps between adjacent teeth in the user's oral cavity. The oral processing device (100) is controlled to perform actions based on the identified adjacent gaps. Thus, adjacent gaps can be automatically detected during use of the device (100) based on IMU signals and image data. In some cases, the user may not be aware that a specific gap exists, but the gap can still be detected by the device (100) based on IMU signals and image data. As a result of gap detection, measures can be taken, such as informing the user of the gap location and controlling the device (100) to deliver processing to the gap. In this way, the position of the device (100) head (120) in the oral cavity is determined per gap level. Therefore, the method described herein has a higher spatial resolution than other methods. In the embodiment, identifying the gap is a separate process from identifying the oral region where the head (120) is located. For example, it may first be determined that the head (120) is in close proximity to the gap between adjacent teeth, and additionally determined that the head (120) is in a specific oral region (i.e., area) of the mouth. This facilitates the identification of the location of the detected gap.

[0158] In the embodiments, the classification algorithm includes a machine learning algorithm. Such machine learning algorithms can be improved through experience and / or training (e.g., increasing the accuracy and / or confidence of classification).

[0159] In an embodiment, the oral processing device (100) includes a machine learning agent, and the machine learning agent includes a classification algorithm. Thus, the classification algorithm may be located on the oral processing device (100). Since there is no need to transmit and / or receive data with other devices when the classification algorithm is not located on the device (100), the latency is reduced compared to the case where the classification algorithm is not located on the device (100). Therefore, the oral location can be determined more quickly, so the time required to take correction measures and / or to provide output through a user interface can be reduced. In an alternative embodiment, the classification algorithm is located on a remote device, for example, a device having more processing resources than the oral processing device (100).

[0160] In the embodiment, the classification algorithm is modified using generated signal and / or generated image data. That is, the classification algorithm can be trained and / or further trained using the generated signal and / or generated image data. By modifying the classification algorithm, the accuracy and / or reliability of the algorithm can be improved through experience and / or by using more training data. That is, the confidence level of the determined intraoral location can be increased. Additionally, as the classification algorithm is modified, the classification algorithm can be tailored to the user. By dynamically retraining the classification algorithm using the generated signal and / or generated image data as training data, the classification algorithm can determine the intraoral location of the head (120) of the device (100) with greater reliability.

[0161] In an embodiment, the oral processing device (100) is controlled to deliver processing to the user's oral cavity based on a determined location within the oral cavity. Accordingly, the operation performed in item 940 may include the delivery of processing by the device (100).

[0162] In an embodiment in which an oral processing device (100) includes a fluid delivery system (220) for delivering a working fluid into a user's oral cavity, a control signal for controlling the delivery of the working fluid based on a determined oral cavity position is output to the fluid delivery system (220). Accordingly, the operation performed in item 940 may include the control of the fluid delivery system (220). For example, the oral cavity position may be used to determine whether to trigger a burst of the working fluid. This improves the efficiency and / or accuracy of the fluid delivery system (220) by delivering (or not delivering) processing in consideration of the determined oral cavity position of the device (100) head (120).

[0163] In an embodiment, the user interface (250) provides an output based on a determined oral position. Accordingly, the action performed in item 940 may include providing an output through the user interface (250). In an embodiment, the user interface (250) provides an output while processing the user's oral cavity using the oral processing device (100). By having the user interface (250) provide an output while using the device (100) rather than after the oral processing session is completed, feedback can be provided more quickly. For example, the output can be provided by the user interface (250) in substantially real time. Accordingly, the user can adjust their behavior, such as taking corrective measures while using the device (100), thereby improving the effectiveness of the processing delivery.

[0164] In an embodiment, the user interface (250) provides an output after processing the user's oral cavity using the oral processing device (100). 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 can be analyzed over the oral processing session, and then feedback on the entire session can be provided to the user. In an embodiment, the user interface (250) provides an output both during and after use of the device (100).

[0165] In the embodiments, the output provided by the user interface includes auditory, visual, and / or tactile outputs. For example, the output may be provided through a display, a speaker, and / or a haptic actuator.

[0166] In an embodiment, the user interface is included in a remote device (e.g., a user device such as a mobile phone). In this embodiment, a signal is output to the remote device so that the user interface provides an output. The user interface on this remote device may be more multifunctional than the user interface on the oral processing device (100) itself.

[0167] In an embodiment, the oral processing device (100) includes a user interface (250). By providing a user interface (250) on the oral processing device (100), the need for communication between different devices can be avoided, so that output can be generated more quickly and received more quickly by the user compared to the case where the user interface (250) is not included on the oral processing device (100). Additionally, providing a user interface (250) on the oral processing device (100) can increase the likelihood of the user receiving feedback more quickly.

[0168] In an embodiment, data representing a determined intraoral location is output for storage in memory (260). Accordingly, the data may be used later [e.g., for post-processing analysis and / or for generating a behavioral profile for the user's device (100) usage]. In an embodiment, data representing a determined intraoral location is output for transmission to a remote device (e.g., user device).

[0169] In an embodiment, the determined intraoral position of the device (100) head (120) is used as part of an adjacent gap detection and processing process, such as one or more methods described above with reference to FIGS. 3 through 6. In an embodiment, the determined intraoral position of the head (120) is used, for example, in a plaque detection process using qualitative plaque fluorescence.

[0170] FIG. 10 illustrates a method (1000) of operating an oral processing device according to an embodiment. The method (1000) can be used to operate the oral processing device (100) described above with reference to FIG. 1a, 1b, and 2. In the embodiment of FIG. 10, the oral processing device (100) includes an IMU (240). The IMU (240) can be operated to output a signal according to the movement of the oral processing device (100). In the embodiment, the method (1000) is performed at least partially by a controller (210).

[0171] In step 1010, a signal indicating the movement of the oral processing device (100) to the user's oral cavity is received.

[0172] 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 processing device (100) is moving according to a preset type of movement.

[0173] In step 1030, the oral processing device (100) is controlled to perform an action using classification data.

[0174] By using the signal from the IMU (240) as input to a classification algorithm, the current type of movement of the device (100) can be recognized. Thus, the device (100) can autonomously identify how the user is moving the device (100) and adapt accordingly. This allows the device (100) to be controlled more intelligently. For example, one or more operating settings of the device (100) can be controlled according to the identified behavior. This allows the settings of the device (100) to correspond more closely to how the user uses the device (100). When using a trained algorithm, the type of movement can be classified more accurately and / or reliably compared to when a trained algorithm is not used.

[0175] In an embodiment, the movement of the oral treatment device (100) according to a preset movement type interferes with the treatment of the user's oral cavity using the oral treatment device (100). Therefore, it can be determined when the device (100) is being moved in a manner that reduces the likelihood of successful treatment by the device (100). Based on this determination, the user may be warned and / or the device (100) may be controlled. For example, in an embodiment, the preset movement type includes a scrubbing movement. The scrubbing movement includes rapid back-and-forth movement. This type of movement interferes with the effective delivery of some treatment (e.g., delivery of working fluid to adjacent gaps between teeth). Therefore, by determining whether the device (100) is being moved in this manner, corrective measures may be taken by the user who receives a notification from the device (100) that the movement type is interfering with effective treatment, or by the device (100) itself (e.g., by controlling the delivery of treatment).

[0176] In an embodiment, in response to classification data indicating that the oral processing device (100) is moving according to a preset type of movement, processing delivery by the oral processing device (100) in the user's oral cavity is prevented. Accordingly, the operation performed in item 1030 may include the prevention of processing delivery. As previously discussed, if the device (100) moves according to a preset type of movement, it interferes with (i.e., has a negative effect on) effectively processing the user's oral cavity using the device (100). Therefore, by preventing processing delivery when it is determined that the device (100) is moving according to a preset type, the device (100) can be operated more efficiently. That is, if it is determined that the probability of successful processing is relatively low due to the way the device (100) moves, processing delivery is not attempted.

[0177] In an embodiment, the oral processing device (100) is controlled to deliver processing into the user's oral cavity in response to classification data indicating that the oral processing device (100) is not moving according to a preset type of movement. Thus, when it is determined that the device (100) is not moving according to a preset type of movement [e.g., when it is determined that the device (100) is not moving in a scrubbing motion], processing delivery may be triggered. Accordingly, if it is determined that the device (100) is moving according to a preset type of movement, processing delivery may be prevented, and if it is determined that the device (100) is not moving according to a preset type of movement, processing delivery may be triggered (or allowed to be triggered). Accordingly, the type of movement of the device (100) is used as a condition for determining whether to perform processing delivery.

[0178] In an embodiment, the device (100) is controlled to deliver treatment into the user's oral cavity in response to classification data indicating that the device (100) is moving according to an additional preset motion type. In an example where the preset motion type includes a scrubbing motion, the additional preset motion type may include, for example, no motion or 'gentle' gliding motions that differ from the scrubbing motion. Thus, to improve the efficiency and / or effect of treatment delivery, the user may be discouraged from using the preset motion type and encouraged to use the additional preset motion type.

[0179] In an embodiment in which an oral treatment device (100) includes a fluid delivery system (220) for delivering a working fluid to the user's oral cavity, a control signal for controlling the delivery of the working fluid based on classification data is output to the fluid delivery system (220). Thus, the operation performed in item 1030 may include the control of the fluid delivery system (220). For example, if it is determined that the device (100) is moving according to a preset type of movement, the delivery of the working fluid may be prevented. The user may move the device (100) in a manner that interferes with the accurate and / or reliable delivery of the working fluid to a target (e.g., adjacent gaps between adjacent teeth). For example, if the device (100) moves too fast (e.g., scrubbing motion), the likelihood that the fluid delivery system (220) will spray the working fluid to the actual intended location (e.g., adjacent gaps) is lower. This may be a particular consideration if the application area of ​​the fluid jet is relatively small (i.e., concentrated). This means that as the target is missed, the working fluid is more likely to be wasted, and effective processing is less likely to occur (at least without repeated fluid injection attempts). By controlling the fluid delivery system (220) based on whether the device (100) moves according to a preset type of movement, the accuracy and / or efficiency of the fluid delivery system (220) is increased, and the amount of working fluid used or wasted is reduced.

[0180] In an embodiment, the method of FIG. 10 is performed in conjunction with an image-based adjacent gap detection and processing process (e.g., the method of FIG. 4 described above). In this embodiment, when the device (100) moves in a scrubbing motion, the detection of adjacent gaps may be hindered due to the excessively fast movement of the image sensor equipment (230). Even if the gap is successfully detected, the scrubbing motion may impair the accuracy of the fluid delivery system (220) in spraying the working fluid into the detected gap. Therefore, the performance of the adjacent gap detection and processing process is improved by selectively preventing processing delivery when it is determined that the device (100) is moving according to a preset type of movement.

[0181] In an embodiment, features are extracted from a received IMU signal substantially in real time, that is, during use of the device (100). A sliding window may be applied to the IMU signal to extract features (e.g., one or more average values) from the signal. These extracted features are input into a trained classification algorithm, which determines whether the device (100) is moving according to a preset type of movement. In an embodiment, the IMU (240) includes a 6-axis IMU that provides accelerometer and gyroscope data. In an alternative embodiment, only either the accelerometer data or the gyroscope data is provided by the IMU (240).

[0182] In an embodiment, the IMU signal is sampled at a preset sampling rate to be analyzed by a trained classification algorithm. The sampling rate may be preset based on the available computing resources of the device (100), whether the analysis is performed on a remote device rather than on the device (100) itself, etc. For example, sampling the IMU signal at a relatively low frequency may be less computationally expensive than sampling the IMU signal at a relatively high frequency. However, sampling the IMU signal at a low frequency may increase the delay time between signal acquisition and control of the device (100) and / or decrease the accuracy of motion type determination by the classification algorithm. Therefore, a trade-off may be made between performance and processing resources when determining the sampling rate of the IMU signal.

[0183] In an embodiment, a user interface provides an output in response to classification data indicating that the oral processing device (100) is moving according to a preset type of movement. For example, the device (100) may include the user interface (250) described above with reference to FIG. 2, and the user interface (250) may provide an output. Thus, the operation performed in item 1030 may include providing an output through the user interface (250). By providing an output to the user, the user may be notified that the device (100) is moving in a manner that interferes with effective processing using the device (100), thereby inducing the user to take corrective measures. In an embodiment, the output provided by the user interface (250) includes auditory, visual, and / or tactile outputs. For example, the output provided through the user interface (250) may include flashing light, audio tone, and / or vibration.

[0184] In an embodiment, the user interface (250) provides output while processing the user's oral cavity using the oral processing device. By having the user interface (250) provide output while using the device (100) rather than after the oral processing session is completed, feedback can be provided more quickly. For example, the output can be provided by the user interface (250) in substantially real time. Accordingly, the user can improve the effectiveness of processing delivery by adjusting their behavior, such as taking corrective measures while using the device (100).

[0185] In an embodiment, the user interface (250) provides an output after processing the user's oral cavity using the oral processing device (100). 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 over the oral processing session, and feedback on the entire session can then be provided to the user. This feedback encourages the user to adjust their behavior in subsequent sessions.

[0186] In an embodiment, user feedback is provided while the device (100) is in use (e.g., substantially in real time) and also after the processing session has ended. For example, the user interface (250) of the device (100) can indicate to the user that the device (100) is moving in an inefficient manner (e.g., with scrubbing motion) during the use of the device (100). Additionally, an additional user interface arranged on a remote device can provide a more detailed analysis of user behavior after the processing session has ended. This allows the user to adjust how they use the device (100) in subsequent sessions.

[0187] In an embodiment, the oral processing device (100) includes a user interface (250). By providing a user interface (250) on the oral processing device (100), the need for communication between different devices can be avoided, so that output can be generated more quickly and received more quickly by the user compared to the case where the user interface is not included on the oral processing device. Additionally, providing a user interface on the oral processing device (100) can increase the likelihood of the user receiving feedback immediately.

[0188] In an embodiment, the user interface is included in a remote device (e.g., a user device). In this embodiment, a signal is output to the remote device so that the user interface provides an output. This signal is, for example, Bluetooth. TM It can be transmitted wirelessly to a remote device through the technology. The user interface on this remote device may be more multifunctional than the user interface on the oral processing device itself. For example, since the oral processing device (100) is generally handheld and may have various other components, the space available for the user interface on the oral processing device (100) may be limited.

[0189] In an embodiment, the classification algorithm is modified using signals received from the IMU (240). That is, the classification algorithm can be trained and / or further trained using the IMU signals. Modifying the classification algorithm can improve the accuracy and / or reliability of the algorithm through experience and / or more training data. That is, the level of confidence regarding the determined type of movement can be increased. Additionally, as the classification algorithm is modified, the classification algorithm can be tailored to the user. For example, an initial classification algorithm may be provided to the device (100), but the initial classification algorithm does not take into account behaviors unique to a given user. For example, the user may move the device (100) in a specific way that differs from other users. By dynamically retraining the classification algorithm using the generated signals as training data, the classification algorithm can more reliably determine whether the device (100) is moving according to a preset type of movement.

[0190] In an embodiment, the classification algorithm is retrained (e.g., modified) using a signal received from the IMU (240), and the retrained classification algorithm is configured to determine whether the oral processing device is being moved according to an additional type of movement different from a preset type of movement. Thus, the classification algorithm is initially trained to detect a first type of movement and can be retrained to detect a second, different type of movement based on user-specific data. In this way, the classification algorithm can be adjusted to suit the behavior of a specific user (e.g., to detect a specific type of movement used by the user).

[0191] In an embodiment, the classification data is stored in memory (260). Accordingly, the data can be used later [e.g., for analysis after processing and / or for generating a behavioral profile for the user's device (100) usage]. In an embodiment, the classification data is output for transmission to a remote device (e.g., user device).

[0192] In an embodiment, training data is received from a remote device. In this embodiment, the classification algorithm is modified using the received training data. The training data may be received from a network (e.g., 'cloud'). This training data may include IMU data and / or classification data associated with other users. This training data may include, for example, crowdsourced data. In an embodiment, this training data has a greater amount than the IMU data and / or classification data obtained by directly using the oral processing device (100). Modifying the classification algorithm using training data from a remote device can increase the accuracy and / or reliability of the classification algorithm compared to the case where this training data is not used.

[0193] In the embodiments, the classification algorithm includes a non-linear classification algorithm. A non-linear classification algorithm can be used to distinguish behaviors that cannot be linearly separated. This may include cases where a user moves the device during use. Therefore, obtaining classification data using a non-linear classification algorithm can determine classification data more accurately and / or reliably compared to using a linear classification algorithm or function.

[0194] In an embodiment, the classification algorithm includes a machine learning algorithm. Such machine learning algorithms can be improved through experience and / or training (e.g., increasing the accuracy and / or confidence of classification). In an embodiment, the classification algorithm is trained using supervised and / or unsupervised machine learning methods to detect whether the device (100) is moving according to a preset type of movement.

[0195] In an embodiment, the oral processing device (100) includes a machine learning agent, and the machine learning agent includes a classification algorithm. Thus, the classification algorithm may be located on the oral processing device (100). When motion type determination is performed on the device (100), there is no need to transmit and / or receive data with other devices, so the delay time is reduced compared to the case where the classification algorithm is not located on the device (100). Therefore, motion types can be distinguished more quickly, so the time required to take correction measures and / or provide output through a user interface can be reduced.

[0196] It will be understood that any feature described in connection with any one embodiment and / or aspect may be used alone or in combination with other described features, as well as in combination with one or more features of any other embodiment and / or aspect or any combination thereof. For example, it will be understood that a feature and / or step described in connection with a specific method among the methods (300, 400, 500, 600, 700, 800, 900, 1000) may be included instead of or in addition to a feature and / or step described in connection with another method among the methods (300, 400, 500, 600, 700, 800, 900, 1000).

[0197] In an embodiment of the present invention, the automatic operation of the device (100) [e.g., related to any of the methods (300, 400, 500, 600, 700, 800, 1000)] may be overridden by a user of the device (100). For example, the user may want repetitive processing (e.g., additional injection of working fluid) to be delivered to an adjacent gap that has already been processed, while the automatic operation implemented by the controller (210) may prevent such repetitive processing. This may occur, for example, when the first processing of the gap was not successful and / or was unsatisfactory to the user. In an embodiment, the device (100) may override the automatic operation of the device (100) by including a user interface (e.g., a button) to allow the user to force repetitive processing.

[0198] In an embodiment of the present invention, one or more data analysis algorithms are used to control an oral processing device (100) to, for example, detect adjacent gaps, determine the position of the head of the device (100) within the oral cavity, and determine whether the device (100) is being moved according to a preset type of movement. The data analysis algorithm is configured to analyze received data (e.g., image data and / or IMU data) and to generate an output (e.g., is a gap or is not a gap) that can be used as a condition for controlling the device (100). In an embodiment, the data analysis algorithm includes a classification algorithm, for example, a non-linear classification algorithm. In an embodiment, the data analysis algorithm includes a trained classification algorithm as previously described, for example, with reference to FIGS. 3 through 10. However, in an alternative embodiment, the data analysis algorithm includes other types of algorithms, for example, which are not necessarily trained and / or configured to perform classification.

[0199] In an embodiment of the present invention, the oral processing device (100) includes a controller (210). The controller (210) is configured to perform various methods described herein. In an embodiment, the controller (210) includes a processing system. Such a processing system may include one or more processors and / or memory. Each device, component, or function [e.g., image sensor equipment (230), user interface (250), and / or machine learning agent] described in connection with any of the examples described herein may similarly include a processor or be included in a device that includes a processor. One or more aspects of the embodiments described herein include processes performed by the device. In some examples, the device includes one or more processors configured to perform these processes. In this regard, the embodiments may be at least partially implemented by computer software or hardware stored in (non-transient) memory and executable by a processor, or by a combination of tangibly stored software and hardware (and tangibly stored firmware). The embodiments are also extended to computer programs, in particular to computer programs on or within a carrier adapted to execute the embodiments described above. The program may be non-transient source code, object code, or any other non-transient form suitable for use in implementing the processes according to the embodiments. The carrier may be any object or device capable of holding the program, such as RAM, ROM, or optical memory devices.

[0200] One or more processors of the processing system may include a central processing unit (CPU). One or more processors may include a graphics processing unit (GPU). One or more processors may include one or more of a field programmable gate array (FPGA), a programmable logic device (PLD), or a complex programmable logic device (CPLD). One or more processors may include an application-specific integrated circuit (ASIC). Those skilled in the art will understand that, in addition to the examples provided, many other types of devices may be used to provide one or more processors. One or more processors may include multiple processors placed together or multiple processors placed disparately. Operations performed by one or more processors may be executed by one or more of hardware, firmware, and software. It will be understood that the processing system may include more or fewer components than described and / or different components.

[0201] The technology described herein may be implemented in software or hardware, or using a combination of software and hardware. This may include configuring a device to perform and / or support some or all of the technology described herein. At least some aspects of the examples described herein with reference to the drawings include computer processes performed on a processing system or processor, but the examples described herein also extend to computer programs (e.g., computer programs on or within a carrier adapted to execute the examples). A carrier may be any object or device capable of holding a program. A carrier may include a computer-readable storage medium. Examples of tangible computer-readable storage media include, but are not limited to, optical media (e.g., CD-ROM, DVD-ROM, or Blu-ray), flash memory cards, floppy disks, or hard disks, or any other medium capable of storing computer-readable instructions, such as microcode or firmware within at least one ROM or RAM or programmable ROM (PROM) chip.

[0202] In the foregoing description, where integers or elements have known, obvious, or predictable equivalents, such equivalents are incorporated herein by virtue of being individually specified. To determine the true scope of the invention, the claims must be referenced and interpreted as including such equivalents. Furthermore, readers will understand that integers or features described in the invention, for example as desirable, advantageous, or convenient, are optional elements and do not limit the scope of the independent claims. Additionally, it should be understood that such optional integers or features may be advantageous in some embodiments of the invention but may not be included in others as they are undesirable.

Claims

Claim 1 An oral treatment device for use in treating a user’s oral cavity, wherein the oral treatment device comprises: an intraoral image sensor device configured to generate image data representing at least a portion of the user’s oral cavity during use of the oral treatment device by the user; and a controller, wherein the controller comprises: processing the generated image data to determine location data representing the location of an interproximal gap between adjacent teeth within the user’s oral cavity; and controlling the oral treatment device to deliver treatment to the detected interproximal gap based on the location data during the same use of the oral treatment device. Claim 2 The oral treatment device according to claim 1, wherein the oral treatment device includes a fluid delivery system for delivering a working fluid to the user's oral cavity, and the controller is configured to output a control signal to the fluid delivery system to control the delivery of the working fluid based on the position data. Claim 3 In claim 1, the oral processing device comprises a head, and the oral image sensor equipment is at least partially included in the head. Claim 4 In claim 1, the oral processing device comprises a handle, and the oral image sensor equipment is at least partially included in the handle. Claim 5 The oral processing device according to claim 1, wherein the oral processing device comprises a head, and the oral image sensor equipment comprises: a sensor; and an aperture for receiving light and transmitting the light to the sensor—the aperture being included in the head of the oral processing device. Claim 6 In claim 5, the oral treatment device comprises a handle, and the sensor is included in the handle of the oral treatment device. Claim 7 In claim 5, the image sensor equipment comprises a guide channel for guiding light from the aperture to the image sensor, an oral processing device. Claim 8 An oral processing device according to claim 1, wherein the controller is configured to process the generated image data using a sliding window, and the position data is determined by detecting the presence of the adjacent gap within the sliding window. Claim 9 An oral processing device according to claim 1, wherein the controller is configured to process the generated image data by extracting one or more image features from the image data and determining the position data using the extracted one or more image features. Claim 10 In claim 9, the oral processing device, wherein the controller is configured to extract one or more image features using a discrete wavelet transform. Claim 11 In claim 9, the oral processing device is configured such that the controller extracts one or more image features using at least one of an edge detector, a corner detector, and a blob extractor. Claim 12 In claim 1, the controller is configured to process the generated image data using a trained classification algorithm configured to identify adjacent gaps, and the trained classification algorithm is trained prior to the use of the oral processing device. Claim 13 In claim 1, the oral processing device includes a user interface, and the controller is configured to cause the user interface to provide an output according to the location data. Claim 14 In claim 1, the oral processing device comprises a memory, and the controller is configured to store one or more characteristics of the adjacent gap in the memory for use in subsequent processing and / or control of the oral processing device. Claim 15 An oral treatment device according to any one of claims 1 to 14, wherein the oral treatment device comprises a toothbrush. Claim 16 A method of operating an oral processing device for use in processing a user's oral cavity, wherein the oral processing device comprises an intraoral image sensor device and a controller, and the method comprises: using the intraoral image sensor device to generate image data representing at least a portion of the user's oral cavity during use of the oral processing device by the user; processing the generated image data in the controller to determine location data representing the location of adjacent gaps between adjacent teeth in the user's oral cavity; and controlling the oral processing device in the controller to deliver processing to the detected adjacent gaps based on the location data during the same use of the oral processing device. Claim 17 A computer program stored on a non-transient recording medium containing instructions, wherein the computer program stored on a non-transient recording medium configured to perform the method of claim 16.

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