Oral treatment device for interproximal gaps

Abstract

There is provided an oral treatment device for use in treating an oral cavity of a user. The oral treatment device comprises an image sensor equipment operable to generate an image dataset representing a portion of the oral cavity of the user, a treatment delivery system operable to deliver a treatment to an interproximal gap in the oral cavity of the user in response to receiving a treatment control signal, and a controller. The controller is configured to: receive a sequence of generated image datasets from the image sensor equipment; upon receiving each image dataset, apply a gap detection algorithm to the image dataset, the gap detection algorithm configured to detect an interproximal gap in the portion of the oral cavity represented in the image dataset; and, based on an interproximal gap being detected for N of the image datasets consecutively, output a treatment control signal to the treatment delivery system. There is also provided a computer-implemented method of operating an oral treatment device, and a computer program comprising instructions which, when executed by a controller cause the controller to execute a computer-implemented method.

Description

[0001] ORAL TREATMENT DEVICE FOR INTERPROXIMAL GAPS

[0002] BACKGROUND

[0003] Oral treatment devices are used to provide treatment to the oral cavity (i.e. the mouth) of a user. Examples of such devices include toothbrushes (which may be manual or electric), oral irrigators, interdental cleaning devices, flossing devices, etc.

[0004] In some known cases, oral treatment devices (also referred to as “oral care devices”, or “oral treatment appliances”) can provide a flossing functionality in addition to other functionalities such as tooth brushing. For example, a fluid delivery system may be incorporated into an electric toothbrush, and may be used to deliver a burst of working fluid for interproximal (or interdental) cleaning. Such a fluid delivery system may include a nozzle arranged on the head of the device and used for jetting the working fluid into an interproximal gap between teeth, e.g. to dislodge food matter that is in the gap, and a fluid reservoir for storing the working fluid on the device.

[0005] However, the flexibility and / or versatility of known oral treatment devices is limited. This in turn may limit the ability of known devices to deliver treatments in an optimal manner. For example, known oral treatment devices generally rely on a user to use the device correctly, and this may not always occur.

[0006] Efficient use of working fluid may be a particular consideration where the oral treatment device includes an on-board fluid reservoir having a fixed capacity. Using and / or wasting more working fluid requires a more frequent replenishment of the fluid reservoir. In some cases, effective treatment is not achieved even with repeated attempts.

[0007] SUMMARY

[0008] According to a first aspect of the present disclosure, there is provided an oral treatment device for use in treating an oral cavity of a user, the oral treatment device comprising: image sensor equipment operable to generate an image dataset representing a portion of the oral cavity of the user; a treatment delivery system operable to deliver a treatment to an interproximal gap in the oral cavity of the user in response to receiving a treatment control signal; a controller configured to: receive a sequence of generated image datasets from the image sensor equipment; upon receiving each image dataset, apply a gap detection algorithm to the image dataset, the gap detection algorithm configured to detect an interproximal gap in the portion of the oral cavity represented in the image dataset; and, based on an interproximal gap being detected for N of the image datasets consecutively, output a treatment control signal to the treatment delivery system.

[0009] It will be appreciated that “interproximal” may mean interdental, or situated between two adjacent teeth.

[0010] It will further be appreciated that “N” may represent an integer number, which may be greater than 1. By outputting the treatment control signal based on an interproximal gap being detected for N of the image datasets consecutively, the treatment may be delivered more accurately to the interproximal gap, and / or inaccurate delivery of the treatment may be inhibited.

[0011] Each image dataset may correspond to a respective image frame.

[0012] An output of the gap detection algorithm may indicate whether there is an interproximal gap in the portion of the oral cavity represented in the image dataset. As such, the controller may be configured to identify whether there is an interproximal gap in a portion of the oral cavity using an output of the gap detection algorithm.

[0013] The gap detection algorithm may include an object detection algorithm, for example a trained object detection algorithm. The object detection algorithm may include a machine learning algorithm, such as a convolutional neural network (CNN).

[0014] The gap detection algorithm may be configured to detect an interproximal gap in a region- of-interest (ROI) of the portion of the oral cavity. That is, an output of the gap detection algorithm may indicate whether there is an interproximal gap in a ROI of the portion of the oral cavity represented in the image dataset. The ROI may correspond to a target of the treatment delivery system. That is, the treatment delivery system may be operable to deliver the treatment to an interproximal gap in the ROI. Thus, an interproximal gap being detected for N of the image datasets consecutively may correspond to an interproximal gap being detected in the ROI for N of the image datasets consecutively. In this way, treatment may be accurately delivered to a detected interproximal gap.

[0015] The gap detection algorithm may be configured to determine location data indicating a location of the interproximal gap. The gap detection algorithm may be configured to output the location data. As such, the gap detection algorithm may additionally or alternatively be referred to as a gap locator algorithm. In this way, the gap detection algorithm may be configured to detect whether an interproximal gap is in a ROI of the portion of the oral cavity and / or a location of the interproximal gap as x, y co-ordinates in the ROI of the oral cavity.

[0016] In some examples, the gap detection algorithm may be configured to determine the location data using a sliding window. In such examples, the location data may be determined by detecting the presence of the interproximal gap within the sliding window. The sliding window may pass across the image, defining sub-regions of the image, and a determination may be made on whether a gap exists in each sub-region of the image. This may allow the interproximal gap to not only be detected, but localised, e.g., by determining a sub-region of the image which contains the gap.

[0017] In some examples, the oral treatment device may further comprise an inertial measurement unit (IMU), and the controller may be configured to receive one or more IMU datasets from the IMU, which may each include data indicative of a position and / or movement of the oral treatment device. Each IMU dataset may be associated with a corresponding image dataset, for example, such datasets may include data sensed or received at substantially the same time.

[0018] The gap detection algorithm may be configured to determine the location data for an interproximal gap, for example, from an IMU dataset. The IMU dataset may be associated with the image dataset which represents the portion of the oral cavity in which the interproximal gap is detected.

[0019] The oral treatment device may further comprise a user interface operable to output an alert to the user in response to receiving an alert control signal. In such examples, the controller may be configured to, based on an interproximal gap being detected for M of the image dataset(s) consecutively, output an alert control signal to the user interface, wherein N may be greater than M. As discussed in further detail below, M may be equal to 1. Thus, the controller may be configured to, based on an interproximal gap being detected, output an alert control signal to the user interface. Additionally, or alternatively, in such examples the controller may be configured to, based on the interproximal gap being detected for less than N of the image datasets consecutively, output the alert control signal. For example, the controller may be configured to output the alert control signal only when the interproximal gap is detected for less than N of the image datasets consecutively (thus, the controller may be configured to stop outputting the alert control signal when the interproximal gap is detected for N or more of the image datasets).

[0020] As such, a user may be alerted in real time when the oral treatment device is positioned over an interproximal gap. The alert may prompt the user to stop the oral treatment device over the interproximal gap, or to slow down or maintain their movement of the oral treatment device, such that the treatment may be delivered more accurately to the interproximal gap. Without the prompt of an alert, a user may typically move the oral treatment device too quickly for accurate or effective treatment of interproximal gaps. Users may move the oral treatment device too quickly for the device to detect a gap and subsequently deliver the treatment to the gap. Thus, when the treatment is delivered the oral treatment device may be misaligned with the gap, and / or the treatment may be delivered too late. Thus, the user being alerted before the treatment is delivered (e.g., by N being greater than M) according to the present disclosure may result in the treatment being delivered more accurately to the interproximal gap.

[0021] In one or more examples, if the oral treatment device is moved at an appropriate speed, each gap may be detected in the ROI from 5 or more consecutive image datasets. Outputting the alert may better ensure that a user uses the oral treatment device effectively. Further, by outputting the alert a user may be trained to use the oral treatment device effectively, such that even if the oral treatment device were to operate in a mode in which alert control signals are not output, the user may continue to use the device effectively.

[0022] In one or more examples, the controller may be configured to output the alert control signal based on the interproximal gap being detected for at least M of the image dataset(s) consecutively. For example, the controller may be configured to output the alert control signal based on the interproximal gap being detected for at least M, and less than N of the image datasets consecutively. As an example, the controller may be configured to output the alert control signal only after the interproximal gap has been detected in more than one (in other words, M > 1) image datasets consecutively. This alert control signal may be outputted before the treatment control signal is outputted.

[0023] In some cases an alert may be output to the user repeatedly until the treatment is delivered, for example when M and N are non-consecutive numbers. In other words, the controller may be further configured to output the alert control signal more than once prior to the output of the treatment control signal. As an example, if M is 2 and N is 5, then the alert may be output to the user thrice, where the first alert may be output after the interproximal gap has been detected in 2 consecutive image datasets, the second alert may be output after the interproximal gap has been detected in 3 consecutive image datasets, the third alert may be output after the interproximal gap has been detected in 4 consecutive image datasets. The treatment may then be delivered after the interproximal gap has been detected in 5 consecutive image datasets.

[0024] In some cases, the delivery of the treatment may prompt the user to move the oral treatment device onto the next interproximal gap.

[0025] It will be appreciated that “M” may represent an integer number. In one or more examples, N may be any integer number greater than 1. For example, N may be 2 or more, or 3 or more. Thus, the controller may be configured to output the treatment control signal based on an interproximal gap being detected for 3 of the image datasets consecutively, for example.

[0026] In one or more examples, M may be an integer number less than 3. For example, M may be 1 or 2. Thus, the controller may be configured to output the alert control signal based on an interproximal gap being detected for 2 of the image datasets consecutively, for example. An interproximal gap being detected for 1 image dataset consecutively may refer to an interproximal gap being detected for 1 image dataset.

[0027] In particular, in one or more embodiments M may be 1 and N may be 2, for example. In other embodiments, M may be 2 and N may be 3, for example.

[0028] Such values of N and / or M may ensure that the treatment is applied more accurately to the interproximal gap. For example, these values may ensure that a user maintaining or adjusting their movement of the oral delivery device can result in the treatment being applied accurately to the interproximal gap. If N is too small, after the alert is output a user may not have time to adjust their movement of the oral delivery device before the treatment is delivered. If N is too large, treatment may only be delivered to a small number of interproximal gaps, because a user may be less likely to hold the oral delivery device over the interproximal gap for N consecutive image datasets.

[0029] In one or more examples, the controller may be configured to stop outputting an alert control signal in response to an interproximal gap not being detected, or in response to an absence of an interproximal gap being detected. The gap detection algorithm may be configured to detect an absence of an interproximal gap, which may correspond to a tooth, for example. Thus, the alert may not be output if the oral treatment device is not positioned over an interproximal gap. In this way, a user may understand whether or not the oral treatment device is over an interproximal gap. For example, a first alert control signal may be output after the gap is detected in a first image dataset and a second alert control signal may be output after the gap is detected in a second image dataset. If no gap is detected in a third image dataset, no alert control signal may be output. If a gap is detected in the subsequent image dataset, this subsequent image dataset may be considered as a first image dataset for the purpose of determining when to output the treatment control signal to the treatment delivery system.

[0030] In one or more examples, the controller may be configured to output a stop control signal to the user interface in response to an interproximal gap not being detected or in response to an absence of an interproximal gap being detected. The user interface may be configured to stop outputting the alert in response to receiving the stop control signal. Thus, the alert may not be output if the oral treatment device is not positioned over an interproximal gap. In this way, a user may understand whether or not the oral treatment device is over an interproximal gap.

[0031] In one or more examples, the oral treatment device may include a counter. The counter may be configured to count a number of image datasets for which an interproximal gap is detected. The controller may include the counter, or the controller may be configured to communicate with the counter. The controller may be configured to increase the count of the counter based on an interproximal gap being detected. For example, the controller may be configured to increase the count of the counter by an integer number, such as one, based on an interproximal gap being detected. In this way, the controller may be configured to identify a number of image datasets for which an interproximal gap is detected.

[0032] The controller may be configured to identify whether the counter has a count of N. The controller may be configured to identify whether the counter has a count of N or more.

[0033] The controller may be configured to output the alert control signal and / or the treatment control signal based on the count of the counter.

[0034] The controller may be configured to output the treatment control signal in response to identifying that the counter has a count of N, or has a count of N or more. In this way, the controller may be configured to output the treatment control signal based on an interproximal gap being detected for N of the image datasets consecutively. The controller may be configured to output the alert control signal in response to identifying that the counter has a count of M, or has a count of at least M. In this way, the controller may be configured to output the alert control signal based on an interproximal gap being detected for M of the image dataset(s) consecutively.

[0035] The controller may be configured to output the alert control signal in response to identifying that the counter has a count of less than N. In this way, the controller may be configured to output the alert control signal based on an interproximal gap being detected for less than N of the image datasets consecutively.

[0036] The controller may be configured to, in response to identifying that the counter has a count of less than N, output the alert control signal and / or increase the count of the counter. The count may be increased by an integer number, such as one.

[0037] In one or more examples, the controller may be configured to, in response to identifying that the counter has a count of N, or a count of N or more, re-set the count of the counter to zero. In this way, the oral delivery device may be inhibited from delivering treatment twice to a given interproximal gap. Further, the oral delivery device may output an alert after delivery of the treatment when it is positioned over another interproximal gap.

[0038] The counter may be configured to count a number of consecutive image datasets for which an interproximal gap is detected. In one or more examples, the controller may be configured to re-set the count of the counter to zero in response to an interproximal gap not being detected or in response to an absence of an interproximal gap being detected. In this way, treatment may be inhibited from being delivered as soon as the oral delivery device detects another interproximal gap, for example. As such, the treatment may be delivered more accurately to the interproximal gap, and / or inaccurate delivery of the treatment may be inhibited.

[0039] In one or more examples, the controller may be configured to, in response to an interproximal gap being detected for an image dataset, identify whether the detected interproximal gap is the same interproximal gap as a previously detected interproximal gap from, or represented in, a previous image dataset.

[0040] In one or more examples, the previously detected interproximal gap is from an immediately preceding, or consecutive, image dataset. That is, in one or more examples the controller is configured to, in response to an interproximal gap being detected for an image dataset, identify whether the detected interproximal gap is the same interproximal gap as a previously detected interproximal gap from an immediately preceding, or consecutive, image dataset.

[0041] As such, it may be ensured that the interproximal gap being detected for consecutive image datasets is the same interproximal gap. In this way, inaccurate delivery of the treatment may be inhibited.

[0042] In one or more examples, the controller may be configured to, based on an identification of the same interproximal gap being detected for N of the image datasets consecutively, output the treatment control signal. As such, treatment may only be delivered if the same interproximal gap is detected for N of the image datasets consecutively. In this way, inaccurate delivery of the treatment may be inhibited. For example, if a user moves the oral treatment device at a speed such that different interproximal gaps are detected from consecutive image datasets, treatment may not be delivered.. This absence of treatment may serve as a form of feedback to the user to train the user to move the oral treatment device more slowly.

[0043] In one or more examples, the controller may be configured to, based on an identification of the same interproximal gap being detected for M of the image dataset(s) consecutively, output the alert control signal. Additionally, or alternatively, the controller may be configured to, based on an identification of the same interproximal gap being detected for less than N of the image datasets consecutively, output the alert control signal. As such, an alert may only be output if the same interproximal gap is detected for at least two of the image datasets consecutively. In this way, poor alignment by a user of the oral treatment device with an interproximal gap may be inhibited. Thus, inaccurate delivery of the treatment may be inhibited. For example, if a user moves the oral treatment device at a speed such that two different interproximal gaps are detected from two consecutive image datasets, no alert may be output and this may serve as a form of feedback to the user to train the user to move the oral treatment device more slowly.

[0044] In examples where the oral delivery device includes a counter, the controller may be configured to, based on an identification that the detected interproximal gap is the same interproximal gap as the previously detected interproximal gap, (for example from the immediately preceding image dataset) increase the count of the counter. The count may be increased by an integer number, such as 1. Thus, the counter may be configured to count a number of consecutive image datasets for which the same interproximal gap is detected. As such, the controller may be configured to operate (e.g., to output signals such as the treatment control signal and the alert signal) based on the number of consecutive image datasets for which the same interproximal gap is detected.

[0045] The controller may be configured to, in response to an identification that the detected interproximal gap is the same interproximal gap as the previously detected interproximal gap (for example from the immediately preceding image dataset), identify whether the count of the counter is N, or N or more. In this way, the controller may be configured to output the treatment control signal based on an interproximal gap being detected for N of the image datasets consecutively, and / or the controller may be configured to output the alert control signal based on an interproximal gap being detected for less than N of the image datasets consecutively.

[0046] As mentioned above, the controller may be configured to, in response to identifying that the counter has a count of N, or a count of N or more, output the treatment control signal and / or re-set the count of the counter. As further mentioned above, the controller may be configured to, in response to identifying that the counter has a count of less than N, output the alert control signal and / or increase the count of the counter, by 1, for example.

[0047] In one or more examples, the controller may be configured to, in response to an identification that the detected interproximal gap is not the same interproximal gap as the previously detected interproximal gap (for example from the immediately preceding image dataset), stop outputting the alert control signal, and / or to output a stop control signal to the user interface. As such, an alert may only be output if the same interproximal gap is detected for at least two of the image datasets consecutively. In this way, poor alignment by a user of the oral treatment device with an interproximal gap may be inhibited. Thus, inaccurate delivery of the treatment may be inhibited. For example, if a user moves the oral treatment device at a speed such that two different interproximal gaps are detected from two consecutive image datasets, no alert may be output and this may serve as a form of feedback to the user to train the user to move the oral treatment device more slowly.

[0048] In one or more examples, the controller may be configured to, in response to an identification that the detected interproximal gap is not the same interproximal gap as the previously detected interproximal gap (for example from the immediately preceding image dataset), re-set the count of the counter to zero. In this way, the controller may be configured to identify a number of consecutive image datasets for which the same interproximal gap is detected. As such, treatment may only be delivered if the same interproximal gap is detected for N of the image datasets consecutively. In this way, inaccurate delivery of the treatment may be inhibited. For example, if a user moves the oral treatment device at a speed such that two different interproximal gaps are detected from two consecutive image datasets, no treatment may be delivered and thus, this may serve as feedback to the user to train the user to move the oral treatment device more slowly.

[0049] In one or more examples, the controller may be configured to identify whether the detected interproximal gap is a new interproximal gap, that is, whether the detected interproximal gap is a different interproximal gap to one or more previously detected interproximal gaps for which a treatment control signal has been output. In one or more examples, such previous image datasets containing these previously detected and treated interproximal gaps may be non-consecutive with the current image dataset. That is, such previous image datasets may not immediately precede the current image dataset.

[0050] The controller may be configured to output the treatment control signal and / or the alert control signal only if the detected interproximal gap is identified as being a new interproximal gap, in other words, identified as being different from the previously treated interproximal gaps. As such, repeated treatments of the same gap during a single oral treatment session may be reduced and / or avoided. This may allow for a more efficient use of the oral treatment device.

[0051] For example, the controller may be configured to, in response to an interproximal gap being detected, identify whether the detected interproximal gap is a new interproximal gap. The controller may be configured to, in response to an identification that the detected interproximal gap is a new interproximal gap, identify whether the detected interproximal gap is the same interproximal gap as any one of previously detected and treated interproximal gaps. The controller may be configured to, in response to an identification that the detected interproximal gap is not a new interproximal gap, re-set the count of the counter to zero and / or output the stop control signal.

[0052] The controller may be configured to store one or more of the image datasets, from which interproximal gaps are detected, in a memory for use in subsequent comparison of interproximal gaps.

[0053] In one or more examples, the controller may be configured to, upon receiving each image dataset, apply a moving direction detection algorithm to the image dataset. The moving direction detection algorithm may be configured to calculate a movement parameter of, or associated with, the image dataset. The moving direction detection algorithm may be configured to calculate a movement parameter of, or associated with, the image dataset with respect to a previous image dataset (for example the immediately preceding image dataset). The movement parameter may correspond to a movement vector, for example, which may correspond to a movement trajectory.

[0054] Identifying whether the detected interproximal gap is the same interproximal gap as a previously detected interproximal gap may be based on the movement parameter. That is, identifying whether the detected interproximal gap is the same interproximal gap as a previously detected interproximal gap may comprise identifying, based on the movement parameter, whether the detected interproximal gap is the same interproximal gap as the previously detected interproximal gap. In this way, an identification of whether the detected interproximal gap is the same gap as an interproximal gap from an immediately preceding image dataset may be carried out. Similarly, in this way, an identification of whether the detected interproximal gap is a new gap may be carried out.

[0055] For example, if a calculated movement vector corresponds to substantially zero, this may indicate that the detected interproximal gap is the same interproximal gap as the previously detected interproximal gap.

[0056] In one or more examples, the moving direction detection algorithm may include an optical flow algorithm. Accordingly, the moving direction detection algorithm may be applied to the image dataset and the previous image dataset.

[0057] As mentioned above, in one or more examples, the oral treatment device may further comprise an inertial measurement unit (IMU), and the controller may be configured to receive one or more IMU datasets from the IMU, which may each include data indicative of a position and / or movement of the oral treatment device. Each IMU dataset may be associated with a corresponding image dataset, for example, such datasets may include data sensed or received at substantially the same time.

[0058] The moving direction detection algorithm may be applied to an IMU dataset associated with the image dataset. As an example, the moving direction detection algorithm may be applied to an IMU dataset associated with the image dataset, as well as to the image dataset.

[0059] In some examples, the moving direction detection algorithm may be configured to determine the movement parameter by extracting one or more image features from the image dataset and using the extracted one or more image features to determine the movement parameter. This may improve the accuracy of the calculated movement vector or movement trajectory, for example. In some examples, the moving direction detection algorithm may be configured to extract the one or more image features using a feature extraction algorithm. Features extracted using a feature extraction algorithm may be used to more accurately detect and localise an interproximal gap from an image dataset. The feature extraction algorithm may comprise one or more of the following algorithms: Shi- Tomasi Comer Detector algorithm, Harris Corner detection, Scale-Invariant Feature Transform, BRIEF (Binary Robust Independent Elementary Features), or ORB (Oriented FAST and Rotated BRIEF). For example, the Shi-Tomasi Corner Detector algorithm may provide for good feature extraction. The moving direction detection algorithm may be configured to extract the one or more image features using at least one of: an edge detector, a corner detector, and a blob extractor. Extracting image features using such methods may provide a more accurate movement trajectory or movement vector of interproximal gaps compared to other methods.

[0060] As discussed, the controller may be configured to carry out steps, such as receiving each image dataset, applying the gap detection algorithm, and outputting the treatment control signal, which may correspond to the steps of a method. The controller may be configured to carry out the steps of the method in a loop, such that following certain endpoint steps, the method starts again from a first step. The first step may include receiving an image dataset. The endpoint steps may include re-setting the count of the counter to zero, outputting the treatment control signal, outputting the alert control signal, and or / outputting the stop control signal.

[0061] In one or more examples, the controller may further be configured to record a log, the log including, for each interproximal gap detected, an indication of whether the treatment was delivered to the interproximal gap. The controller may further be configured to output a treatment profile containing information from the log.

[0062] It will be appreciated that “each interproximal gap detected” may refer to each different interproximal gap detected. For example, the controller may be configured to, for each new interproximal gap identified, record an indication of the interproximal gap, which may be included in the log. The controller may be configured to, each time a treatment delivery signal is output, record an indication of the delivery of the treatment, which may be included in the log. As such, a treatment profile may be output to a user indicating the information on the delivery of the treatment. In this way, a user may gain an understanding of how effectively their oral cavity and / or interproximal gaps have been treated. For example, the treatment profile may indicate how many interproximal gaps were treated and / or which interproximal gaps were treated.

[0063] In one or more examples, the log may further include, for each interproximal gap detected, a location of the gap. As described above, the gap detection algorithm may be configured to determine location data indicating a location of the interproximal gap. The gap detection algorithm may be configured to output location data for the interproximal gap, which may indicate a zone in the oral cavity of the user. As such, a user may gain an understanding of areas within their oral cavity which may require additional treatment, for example.

[0064] The treatment profile may correspond to a 3D treatment profile. The treatment profile may relate to a given oral treatment session.

[0065] The controller may be configured to output the treatment profile to a display of the oral treatment device, for example, and / or to an external device, such as a mobile device.

[0066] In one or more examples, the oral treatment device may include a toothbrush.

[0067] The image sensor equipment may comprise a camera, such as an intraoral camera.

[0068] The oral treatment device may comprise a head, and the image sensor equipment may be at least partially comprised in the head. Since the head of the device may be for delivering the treatment inside the oral cavity of the user, arranging the image sensor equipment at least partially in the head may allow for the inside of the oral cavity to be imaged, without requiring a separately mounted camera (i.e. a camera that is mounted separately from the head).

[0069] The oral treatment device may comprise a handle, and the image sensor equipment may alternatively be at least partially comprised in the handle. By arranging the image sensor equipment at least partially in the handle of the device, on-device space may be managed more efficiently. The head of the device may be relatively small compared to the handle, and including the image sensor equipment in the head may require architectural and / or structural changes to the head, which may be relatively complex and / or expensive. Further, the head of the device may be separable from the handle and is disposable, and it may be desired for a user to replace the head periodically after use. Arranging the image sensor equipment at least partially in the handle, as opposed to entirely in the head, may thus reduce the cost of replacement parts.

[0070] Th user interface may be at least partially comprised in the handle. Similarly to the image sensor equipment described above, by arranging the user interface at least partially in the handle of the device, on-device space may be managed more efficiently. Further, arranging the user interface at least partially in the handle, as opposed to the head, may reduce the cost of replacement parts.

[0071] The user interface may comprise a speaker. Accordingly, the alert may correspond to a sound, such as a short music tone. The alert may correspond to a voice alert, which may prompt a user to stop or continue moving, for example.

[0072] In one or more examples, the treatment delivery system may correspond to a fluid delivery system. The fluid delivery system may comprise a fluid reservoir for storing the working fluid. Accordingly, the treatment delivered to the interproximal gap may be a working fluid.

[0073] In one or more examples, the controller may be operable in a plurality of modes. In a training mode, the controller may be operable to output the alert control signal to the user interface. In an automatic mode controller may not be operable to output the alert control signal to the user interface. As such, in the training mode where alerts are output to a user, the user may be trained to use the oral treatment device effectively, such that in the automatic mode, in which alerts are not output, the user may continue to use the device effectively. According to a second aspect of the present disclosure, there is provided a computer- implemented method of operating an oral treatment device for use in treating an oral cavity of a user.

[0074] The oral treatment device may comprise image sensor equipment operable to generate an image dataset representing a portion of the oral cavity of the user, and a treatment delivery system operable to deliver a treatment to an interproximal gap in the oral cavity of the user in the oral cavity of the user in response to receiving a treatment control signal.

[0075] Th computer-implemented method may comprise receiving a sequence of generated image datasets from the image sensor equipment, upon receiving each image dataset, applying a gap detection algorithm to the image dataset, the gap detection algorithm configured to detect an interproximal gap in the portion of the oral cavity represented in the image dataset, and, based on an interproximal gap being detected for N of the image datasets consecutively, outputting a treatment control signal to the treatment delivery system.

[0076] In one or more examples, the oral treatment device may further comprise a user interface operable to output an alert to the user in response to receiving an alert control signal.

[0077] In such examples, the computer-implemented method may further comprise, based on an interproximal gap being detected for M of the image dataset(s) consecutively, outputting an alert control signal to the user interface, wherein N may be greater than M. Additionally, or alternatively, the computer-implemented method may comprise, based on the interproximal gap being detected for less than N of the image datasets consecutively, outputting the alert control signal.

[0078] It will be appreciated that the computer-implemented method according to the second aspect may include any one or more of the optional features set out above with respect to the first aspect. According to a third aspect of the present disclosure, there is provided a computer program comprising instructions which, when executed by a controller cause the controller to execute a computer-implemented method according to the second aspect.

[0079] BRIEF DESCRIPTION OF THE DRAWINGS

[0080] Figures 1A and IB are perspective views of an oral treatment device according to embodiments;

[0081] Figure 1C is a plan view of an oral treatment device according to embodiments;

[0082] Figure 2 is a schematic diagram of an oral treatment device according to embodiments;

[0083] Figure 3 is a flow diagram showing a method of operating an oral treatment device according to embodiments.

[0084] Figure 4 is a flow diagram showing a method of operating an oral treatment device according to embodiments.

[0085] DETAILED DESCRIPTION

[0086] Figures 1A and IB show perspective views of an oral treatment device 100 according to embodiments. Figure 1C shows a plan view of the oral treatment device 100. The oral treatment device 100, and / or components thereof, may be used to implement the methods described herein. In the embodiments shown in Figures 1A-1C, the oral treatment device 100 comprises a toothbrush. In embodiments, the oral treatment device 100 comprises an electric toothbrush. In embodiments, the device 100 comprises an ultrasonic toothbrush. The oral treatment device 100 may comprise other types of device in alternative embodiments. For example, the device 100 may comprise a flossing device, an oral irrigator, an interproximal cleaning device, an oral care monitoring device, or any combination of such. An oral care monitoring device is configured to monitor the oral health of a user and provide the user with feedback accordingly. The oral treatment device 100 comprises a handle 110 and a head 120. The handle 110 forms the main body of the device 100, and may be gripped by a user during use of the device 100. In the embodiments shown in Figures 1A-1C, the handle 110 comprises a user actuation element 112. The user actuation element 112 comprises a user operable button configured to be depressible by the user when the user is holding the handle 110. In one or more embodiments, the handle 110 comprises a display (not shown), which may be positioned so as to be visible to the user during use of the oral treatment device 100.

[0087] In the embodiments shown in Figures 1A-1C, the head 120 comprises a plurality of bristles 122 for performing a tooth brushing function. In alternative embodiments, the head 120 does not comprise bristles. For example, in one or more other embodiments the oral treatment device 100 comprises a dedicated fluid delivery device, e.g. for cleaning gaps between adjacent teeth, and / or for delivering a cleaning or whitening medium to the teeth of the user. In the embodiments shown in Figures 1A-1C, the oral treatment device 100 comprises a stem 130 which connects the handle 110 to the head 120. The stem 130 is elongate in shape, which serves to space 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 detachable from the handle 110.

[0088] The oral treatment device 100 comprises a treatment delivery system for delivering a treatment to the oral cavity of the user. In the embodiments shown in Figures 1A-1C, the treatment delivery system comprises a fluid delivery system, it being understood that other types of dental and / or oral treatment delivery systems may be used in other embodiments. The fluid delivery system is arranged to deliver bursts of working fluid to the oral cavity. In embodiments, the working fluid comprises a liquid, e.g. water. In alternative embodiments, the working fluid comprises a gas and / or a powder. The working fluid may be delivered to an interproximal gap between adjacent teeth to dislodge obstructions, e.g. food matter such as prosciutto or other cured meats, located in the gap. An interproximal gap is a space, or void, between two adjacent teeth, and / or may be an area surrounding a point of contact of adjacent teeth. The interproximal gap may be defined as the area bounded by a plane which is tangential to the lingual side surface of two adjacent teeth, and the region between the teeth.

[0089] Additionally, or alternatively, the working fluid may be delivered to the gum line of the user, e.g. to treat inflammations or infections of the gums. In alternative embodiments, the treatment delivery system is configured to deliver a whitening fluid, and / or to remove plaque from the teeth of the user.

[0090] In the embodiments shown in Figures 1A-1C, the oral treatment device 100 comprises a fluid reservoir 114 for storing working fluid. The fluid reservoir 114 is arranged in 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 embodiments, the fluid reservoir 114 Is detachable from the handle 110, e.g. to facilitate replenishment of the working fluid.

[0091] In embodiments, the oral treatment device 100 also comprises a nozzle 124. This is shown in Figure 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 oral cavity of the user during use of the oral treatment device 100. In the embodiments shown in Figures 1A-1C, the bristles 122 are arranged at least partially around the nozzle 124. The nozzle 124 extends along a nozzle axis A, illustrated in Figure 1C. The nozzle axis A is substantially perpendicular to a longitudinal axis Z of the handle 110.

[0092] The nozzle 124 is arranged to receive working fluid from the fluid reservoir 114 and to deliver bursts of working fluid to the oral cavity of a user during use of the device 100. In embodiments, the tip of the nozzle 124 comprises a fluid outlet through which a burst of working fluid is delivered to the oral cavity. Each burst of working fluid may have a volume which is less than 1 millilitre, and in one or more cases less than 0.5 millilitre. The nozzle 124 may also comprise a fluid inlet for receiving working fluid from the fluid reservoir 114. In embodiments, the fluid delivery system comprises a pump assembly (not shown) for drawing working fluid from the fluid reservoir 114 to the nozzle 124. The pump assembly may be arranged within the handle 110. The pump assembly may comprise a pump (e.g. a positive displacement pump) and a drive for driving the pump. In embodiments, the drive comprises a pump motor. Power may be supplied to the pump motor by a battery (e.g. a rechargeable battery).

[0093] In embodiments, the fluid delivery system comprises a control circuit (not shown) for controlling actuation of the pump motor, and hence the control circuit and the pump motor provide a drive for driving the pump. The control circuit may comprise a motor controller which supplies power to the pump motor. The control circuit of the fluid delivery system can receive signals from a controller of the oral treatment device 100, as will be described in more detail below.

[0094] Figure 2 shows a schematic block diagram of the oral treatment device 100, according to embodiments.

[0095] The oral treatment device 100 comprises a controller 210. The controller 210 is operable to perform various data processing and / or control functions according to embodiments, as will be described in more detail below. The controller 210 may comprise one or more components. The one or more components may be implemented in hardware and / or software. The one or more components may be co-located or may be located remotely from each other in the oral treatment device 100. The controller 210 may be embodied as one or more software functions and / or hardware modules. In embodiments, the controller 210 comprises one or more processors 210a configured to process instructions and / or data. Operations performed by the one or more processors 210a may be carried out by hardware and / or software. The controller 210 may be used to implement the methods described herein. In embodiments, the controller 210 is operable to output control signals for controlling one or more components of the oral treatment device 100, as will be described in more detail below. In embodiments, the oral treatment device 100 comprises a fluid delivery system 220. The fluid delivery system 220 is operable to deliver working fluid to the oral cavity of the user, as described above with reference to Figures 1A-1C. In embodiments, the fluid delivery system 200 comprises a nozzle for ejecting working fluid, and a fluid reservoir for storing working fluid in the oral treatment device, such as the nozzle 124 and fluid reservoir 114 described above. The fluid delivery system 220 is operable to receive control signals from the controller 210, thereby allowing the controller 210 to control the delivery of working fluid by the fluid delivery system 220. For example, the controller 210 may output a control signal, which may be referred to as a treatment control signal, which is received by a control circuit of the fluid delivery system 220, which causes the control circuit of the fluid delivery system 220 to actuate a pump motor, which in turn causes working fluid to be pumped from the fluid reservoir to the nozzle where it is ejected into the oral cavity of the user. Additionally, or alternatively, the controller 210 may output a control signal which is received by a control circuit of the fluid delivery system 220, which causes the control circuit of the fluid delivery system 220 to prevent the working fluid from being delivered via the nozzle. In alternative embodiments, the oral treatment device 100 does not comprise a fluid reservoir. That is, working fluid may be delivered from outside the oral treatment device 100 (e.g. via a dedicated fluid delivery channel) to be ejected via the nozzle, without being stored in the oral treatment device 100.

[0096] In embodiments, the oral treatment device 100 comprises image sensor equipment 230. The image sensor equipment 230 comprises one or more image sensors. Examples of such image sensors include, but are not limited to, charge-coupled devices, CCDs, and activepixel sensors such as complementary metal-oxide-semiconductor, CMOS, sensors. In embodiments, the image sensor equipment comprises intraoral image sensor equipment. For example, the image sensor equipment may comprise an intraoral camera. Intraoral image sensor equipment (e.g. an intraoral camera) is operable to be used at least partially inside the oral cavity of the user, in order to generate image data representing the oral cavity of the user. For example, the image sensor equipment 230 may be at least partially arranged on the head 120 of the oral treatment device 100, which is arranged to be inserted into the oral cavity of the user. In embodiments, the image sensor equipment 230 comprises one or more processors. The controller 210 is operable to receive image data from the image sensor equipment 230. The image data output from the sensor equipment 230 may be used to control the oral treatment device 100. In embodiments, the controller 210 is operable to control the operation of the image sensor equipment 230.

[0097] In embodiments such as those shown in Figure 2, the oral treatment device 100 comprises an inertial measurement unit, IMU 240. In such embodiments, the controller 210 is operable to receive datasets from the IMU 240, the datasets including data indicative of position and / or movement of the oral treatment device 100. In embodiments, the IMU 240 comprises an accelerometer, a gyroscope and a magnetometer. Each of the accelerometer, gyroscope and magnetometer has three axes, or degrees of freedom (x, y, z). As such, the IMU 240 may comprise a 9-axis IMU. In alternative embodiments, the IMU 240 comprises an accelerometer and a gyroscope, but does not comprise a magnetometer. In such embodiments, the IMU 240 comprises a 6-axis IMU. A 9- axis IMU may produce more accurate measurements than a 6-axis IMU, due to the additional degrees of freedom. However, a 6-axis IMU may be preferable to a 9-axis IMU in one or more scenarios. For example, one or more oral treatment devices may cause and / or encounter magnetic disturbances during use. Heating, magnetism and / or magnetic inductance on the device and / or other magnetic disturbances can affect the behaviour of the magnetometer. As such, in one or more cases, a 6-axis IMU is more reliable and / or accurate than a 9-axis IMU. The IMU 240 is configured to output data indicating accelerometer and gyroscope signals (and in some embodiments magnetometer signals). In embodiments, the IMU 240 is arranged in the head 120 of the oral treatment device 100. In alternative embodiments, the IMU 240 is arranged in the handle 110 of the oral treatment device 100. In embodiments, the oral treatment device 100 comprises a plurality of IMUs 140. For example, a first IMU 240 may be arranged in the head 120 and a second IMU 240 may be arranged in the handle 110.

[0098] In one or more embodiments, the oral treatment device 100 comprises a contact member 245. The contact member 245 is operable to be in contact with teeth of the user during use of the oral treatment device 100, as will be 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 comprise the nozzle of the fluid delivery system 220, e.g. the nozzle 124 described above with reference to Figures 1 A-1C.

[0099] In one or more embodiments, the oral treatment device 100 comprises a user interface 250. The user interface 250 may comprise an audio and / or visual interface, for example. In embodiments, the user interface 250 comprises a display (for example a touch-screen display).

[0100] In one or more embodiments, the user interface 250 comprises an audio output device such as a speaker. In embodiments, the user interface 250 comprises a haptic feedback generator configured to provide haptic feedback to a user. The controller 210 is operable to control the user interface 250, e.g. to cause the user interface 250 to provide output for a user, as will be described in further detail below.

[0101] As mentioned above, in one or more embodiments, the oral treatment device 100 includes a user actuation element 112. The controller 210 is operable to receive data, e.g. based on user input, via the user actuation element 112.

[0102] The oral treatment device 100 also comprises a memory 260. The memory 260 is operable to store various data according to embodiments. The memory may comprise at least one volatile memory, at least one non-volatile memory, and / or at least one data storage unit. The volatile memory, non-volatile memory and / or data storage unit may be configured to store computer-readable information and / or instructions for use / execution by the controller 210.

[0103] The oral treatment device 100 may comprise more, fewer and / or different components in alternative embodiments. In particular, at least some of the components of the oral treatment device 100 shown in Figures 1A-1C and / or 2 may be omitted (e.g. may not be required) in one or more embodiments. 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 one or more embodiments. In embodiments, the oral treatment device 100 comprises additional components not shown, e.g. a power source such as a battery. Figure 3 shows a method 300 of operating an oral treatment device, according to one or more embodiments. The method 300 may be used to operate the oral treatment device 100 described above with reference to Figures 1A, IB and 2. In the embodiments of Figure 3, the oral treatment device 100 comprises the treatment delivery system, the image sensor equipment 230 and the user interface 250. The treatment delivery system is configured to deliver the treatment to an interproximal gap in response to receiving a treatment control signal. The user interface 250 is configured to output an alert to a user in response to receiving an alert control signal. In embodiments, the controller 210 is configured to perform at least part of the method 300.

[0104] In a first step 310, an image dataset representing a portion of the oral cavity of the user is received from the image sensor equipment 230.

[0105] Upon receiving the image dataset, in a second step 320 it is detected whether there is an interproximal gap in a ROI of the portion of the oral cavity represented in the image dataset. This may be achieved by applying a gap detection algorithm to the image dataset, as described in further detail below with reference to Figure 4. If an interproximal gap is not detected, the method proceeds to a re-set step 330, in which the user interface 250 is stopped from outputting the alert. Specifically, a stop control signal is output to the user interface 250 which stops the user interface 250 outputting the alert. Following the re-set step 330, the method 300 starts again at the first step 310 and receives another image dataset. On the other hand, if an interproximal gap is detected, the method 300 proceeds to a third step 340.

[0106] In the third step 340, in response to detecting the interproximal gap, it is identified whether the interproximal gap is the same interproximal gap as a previously detected interproximal gap represented in an immediately preceding image dataset. In other words, it is determined whether the same interproximal gap has been detected for two consecutive image frames. This may be achieved by applying a moving direction detection algorithm to the image dataset, as described in further detail below with reference to Figure 4. If it is identified that the detected interproximal gap is not the same interproximal gap as the previously detected interproximal gap the method 300 proceeds to the re-set step 330. If, on the other hand, it is identified that the detected interproximal gap is the same interproximal gap as the previously detected interproximal gap, the method proceeds to a fourth step 350.

[0107] In the fourth step 350, in response to identifying that the same interproximal gap has been detected for two consecutive image frames, it is identified whether the same interproximal gap has been detected for N of the image datasets consecutively. This may be achieved by taking into account the count of a counter, as described in further detail below with reference to Figure 4. If it is identified that the same interproximal gap has been detected for N or more of the image datasets consecutively, the method 300 proceeds to a treatment delivery step 360, in which treatment is delivered to the interproximal gap of the user. Specifically, a treatment control signal is output to the treatment delivery system, which causes the treatment delivery system to output the treatment. Following the treatment delivery step 360, the method 300 proceeds to the re-set step 330, and subsequently starts again at the first step 310. On the other hand, if it is identified that the same interproximal gap has been detected for less than N of the image datasets consecutively, the method 300 proceeds to an alert step 370 in which an alert is output to the user via the user interface 250. Specifically, an alert control signal is output to the user interface 250, which causes the user interface 250 to output the alert. The alert prompts the user to stop moving the oral treatment device 100. Following the alert step 370, the method 300 starts again from the first step 310. As such, after a certain number of loops through the method 300 with the oral treatment device stationary over the interproximal gap, the same interproximal gap will be detected for N of the image datasets consecutively, and the treatment will be accurately output to the interproximal gap.

[0108] Evidently, a requirement that a same interproximal gap is detected for two consecutive frames includes a requirement that an interproximal gap is detected for M of the image datasets consecutively, where M is 2. Thus, in the example shown in Figure 3, the alert step 370 is only carried out if an interproximal gap is detected for 2 of the datasets consecutively due to the third step 340. However, in other examples, the alert may be output immediately in response to an interproximal gap being detected. That is, in other examples, an alert may be output immediately in response to an interproximal gap being detected for M of the image dataset(s) consecutively, where M is 1. For example, the alert step 370 may follow immediately from the second step 320 in response to a gap being detected. In other examples, an alert may only be output based on an interproximal gap being detected for M of the image datasets consecutively, where M is greater than 2, for example. In such examples, the third step 350 may further include identifying whether the same interproximal gap has been detected for M of the image datasets consecutively, as well as identifying whether the same interproximal gap has been detected for N of the image datasets consecutively. Then, if it is identified in the third step 350 that the same interproximal gap has been detected for at least M, and less than N of the image datasets consecutively, the method may proceed to the alert step 370.

[0109] Turning back to the method 300 shown in Figure 3, the method 300 may be conducted in a loop, such that following the re-set step 330 and the alert step 370, the method starts again from the first step 310. Following the treatment delivery step 360, the method proceeds to the re-set step 330 and subsequently starts again from the first step 310. As such, according to the method 300, a sequence of image datasets are received from the image sensor equipment 230.

[0110] In one or more examples, the method 300 may further include a step, which may be carried out between the first step 310 and the second step 320 of the method 300 shown in Figure 3 for example, of identifying whether the detected interproximal gap is a new interproximal gap which has not previously been treated in the oral treatment session. Such an identification may be made using a moving direction detection algorithm to compare the detected interproximal gap to one or more previously detected interproximal gaps, to which treatment has previously been delivered, from a respective one or more previous image datasets. For example, the moving direction detection algorithm may be applied to the image dataset and to the one or more previous image datasets. The moving direction detection algorithm may include an optical flow algorithm configured to calculate a movement vector of the image dataset with respect to a previous image dataset. The movement vector may then be used to identify whether the interproximal gap is the same interproximal gap as the previously detected interproximal gap, or whether the interproximal gap is a new interproximal gap. If the detected interproximal gap is identified as a new interproximal gap, the method may proceed to the third step 340. If the detected interproximal gap is identified as not being a new interproximal gap, the method may proceed to the re-set step 330.

[0111] In one or more examples, the method 300 may further include recording a log including, for each interproximal gap detected, an indication of whether the treatment was delivered to the interproximal gap. For example, the method 300 may include, each time a new interproximal gap is identified, recording an indication of the interproximal gap, which may be included in the log. The treatment delivery step 360 may include recording an indication of the delivery of the treatment, which may be included in the log. The method 300 may further include, after the treatment session, outputting a treatment profile containing information from the log, which may thus include information on a plurality of interproximal gaps.

[0112] Figure 4 shows a method 400 of operating an oral treatment device, according to embodiments, which may correspond to a specific form of the method 300 shown in Figure 3. In the embodiments of Figure 4, the oral treatment device 100 further comprises a counter, which may be form part of the controller 210, configured to count a number of consecutive image datasets for which the same interproximal gap is detected. In embodiments, the controller 210 is configured to perform at least part of the method 400.

[0113] In a first step 410, an image dataset representing a portion of the oral cavity of the user is received from the image sensor equipment 230.

[0114] In a second step 420, a gap detection algorithm is applied to the image dataset. The gap detection algorithm is configured to detect an interproximal gap in the portion of the oral cavity represented in the image dataset. Thus, an output of the gap detection algorithm indicates whether there is an interproximal gap in a ROI of the portion of the oral cavity represented in the image dataset. Accordingly, in a third step 430, it is identified whether there is an interproximal gap in a ROI of the portion of the oral cavity using an output of the gap detection algorithm. If an interproximal gap is not detected, the method 400 proceeds to a re-set step 440, in which a count of the counter is set to zero. The re-set step 440 further includes stopping the user interface 250 from outputting an alert. Specifically, a stop control signal is output to the user interface 250 which stops the user interface 250 outputting the alert. Thus, the alert is not output if the oral treatment device 100 is not positioned over an interproximal gap. Following the re-set step 440, the method 400 starts again from the first step 410. On the other hand, if an interproximal gap is detected, the method proceeds to a fourth step 450.

[0115] In the fourth step 450, in response to detecting the interproximal gap, it is identified whether the interproximal gap is the same interproximal gap as a previously detected interproximal gap represented in an immediately preceding image dataset. In other words, it is determined whether the same interproximal gap has been detected for two consecutive image frames. As shown in Figure 4, this is achieved by, in a fifth step 460, applying a moving direction detection algorithm to the image dataset and to an immediately preceding image dataset. The moving direction detection algorithm includes an optical flow algorithm and is configured to calculate a movement vector of the image dataset with respect to the immediately preceding image dataset. The movement vector is used in the fourth step 450 to identify whether the interproximal gap is the same interproximal gap as the previously detected interproximal gap. As shown in Figure 4, the moving direction detection algorithm is applied to the image dataset upon receipt of the image dataset. In one or more examples, the moving direction detection algorithm may additionally or alternatively be applied to an IMU dataset received from an IMU of the oral treatment device, the IMU dataset being associated with the image dataset. Thus, IMU data may additionally, or alternatively be used to calculate a movement vector of the image dataset. If it is identified from the movement vector that the detected interproximal gap is not the same interproximal gap as the previously detected interproximal gap the method 400 proceeds to the re-set step 440. If, on the other hand, it is identified from the movement vector that the detected interproximal gap is the same interproximal gap as the previously detected interproximal gap, the method proceeds to a sixth step 470.

[0116] In the sixth step 470, in response to identifying that the same interproximal gap has been detected for two consecutive image frames, it is identified whether the counter has a count of N of more. In this way, it is identified whether the same interproximal gap has been detected for N of the image datasets consecutively. If it is identified that the count is N or more, the method 400 proceeds to a treatment delivery step 480, in which treatment is delivered to the interproximal gap of the user. Specifically, a treatment control signal is output to the treatment delivery system, which causes the treatment delivery system to output the treatment. In the treatment delivery step 480, the count of the counter is also reset to zero. This inhibits the treatment being delivered immediately again to the interproximal gap. Following the treatment delivery step 480, the method 400 starts again from the first step 410. On the other hand, if it is identified that the count is less than N, the method 400 proceeds to an alert step 490 in which an alert is output to the user via the user interface 250. Specifically, an alert control signal is output to the user interface 250, which causes the user interface 250 to output the alert. The alert prompts the user to stop moving the oral treatment device 100. In the alert step 490, the count of the counter is also increased by 1. Following the alert step 490, the method 400 starts again from the first step 410. As such, after a certain number of loops through the method 400 with the oral treatment device stationary over the interproximal gap, the count of the counter will become N, and the treatment will be accurately output to the interproximal gap.

[0117] Although not shown in Figure 4, the method 400 is conducted in a loop, such that following the re-set step 440, the treatment delivery step 480 and the alert step 490, the method starts again from the first step 410. As such, according to the method 400, a sequence of image datasets are received from the image sensor equipment 230.

Claims

CLAIMS1. An oral treatment device for use in treating an oral cavity of a user, the oral treatment device comprising: image sensor equipment operable to generate an image dataset representing a portion of the oral cavity of the user; a treatment delivery system operable to deliver a treatment to an interproximal gap in the oral cavity of the user in response to receiving a treatment control signal; a controller configured to: receive a sequence of generated image datasets from the image sensor equipment; upon receiving each image dataset, apply a gap detection algorithm to the image dataset, the gap detection algorithm configured to detect an interproximal gap in the portion of the oral cavity represented in the image dataset; and, based on an interproximal gap being detected for N of the image datasets consecutively, output a treatment control signal to the treatment delivery system.

2. An oral treatment device according to claim 1, wherein the oral treatment device further comprises: a user interface operable to output an alert to the user in response to receiving an alert control signal; and wherein the controller is further configured to: based on an interproximal gap being detected for M of the image dataset(s) consecutively, output an alert control signal to the user interface, wherein N is greater than M.

3. An oral treatment device according to claim 2, wherein M is greater than 1 and the controller is further configured to: based on an interproximal gap being detected for at least M and less than N of the image datasets consecutively, output the alert control signal.

4. An oral treatment device according to claim 2 or 3, wherein the controller is further configured to output the alert control signal more than once prior to the output of the treatment control signal.

5. An oral treatment device according to any of the preceding claims, wherein the controller is further configured to: based on an interproximal gap being detected, increase the count of a counter and wherein the alert control signal and the treatment control signal are output based on the count of the counter.

6. An oral treatment device according to claim 5, wherein the controller is further configured to: in response to an interproximal gap being not detected for an image dataset, re-set the count of the counter to zero.

7. An oral treatment device according to claim 5 or 6, wherein the controller is further configured to: in response to the counter having a count of N, re-set the count of the counter to zero.

8. An oral treatment device according to any of the preceding claims, wherein the controller is further configured to: in response to an interproximal gap being detected for an image dataset, identify whether the detected interproximal gap is the same interproximal gap as a previously detected interproximal gap from a previous image dataset.

9. An oral treatment device according to claim 8, wherein the previously detected interproximal gap is detected from an immediately preceding image dataset.

10. An oral treatment device according to claim 9, wherein the controller is further configured to:based on an identification of the same interproximal gap being detected for N of the image datasets consecutively, output the treatment control signal.

11. An oral treatment device according to either claim 9 or claim 10, when dependent on any of claims 5 to 7, wherein the controller is further configured to: in response to an identification that the detected interproximal gap corresponds to the previously detected interproximal gap, increase the count of the counter.

12. An oral treatment device according to any of claims 8 to 11, wherein the controller is configured to: upon receiving each image dataset, apply a moving direction detection algorithm to the image dataset, the moving direction detection algorithm configured to calculate a movement parameter of the image dataset with respect to the previous image dataset.

13. An oral treatment device according to claim 12, wherein identifying whether the detected interproximal gap corresponds to the previously detected interproximal gap comprises identifying, based on the movement parameter, whether the detected interproximal gap corresponds to the previously detected interproximal gap.

14. An oral treatment device according to any of claims 2 to 13, wherein the controller is further configured to: record a log, the log including, for each interproximal gap detected, an indication of whether the treatment was delivered to the interproximal gap; and, output a treatment profile containing information from the log.

15. A computer-implemented method of operating an oral treatment device for use in treating an oral cavity of a user, the oral treatment device comprising: image sensor equipment operable to generate an image dataset representing a portion of the oral cavity of the user; and a treatment delivery system operable to deliver a treatment to an interproximal gap in the oral cavity of the user in the oral cavity of the user in response to receiving a treatment control signal;wherein the computer-implemented method comprises: receiving a sequence of generated image datasets from the image sensor equipment; upon receiving each image dataset, applying a gap detection algorithm to the image dataset, the gap detection algorithm configured to detect an interproximal gap in the portion of the oral cavity represented in the image dataset; and, based on an interproximal gap being detected for N of the image datasets consecutively, outputting a treatment control signal to the treatment delivery system.

16. A computer program comprising instructions which, when executed by a controller cause the controller to execute a computer-implemented method according to claim 15.

Images