Tooth brushing area identification method and device

Abstract

The embodiment of the invention provides a tooth brushing area identification method and device. The method comprises the following steps: acquiring inertial measurement unit (IMU) data and preset sensor data of a toothbrush, wherein a preset sensor is used for measuring a distance; respectively processing the IMU data and the preset sensor data to obtain the processed IMU data and the processed preset sensor data; and identifying a tooth brushing area of the user based on the processed IMU data and the processed preset sensor data. Processing based on the acquired IMU (Inertial Measurement Unit) data of the toothbrush and the preset sensor data to obtain the processed IMU data and the processed preset sensor data; and identifying a tooth brushing area of the user based on the processed IMU data and the processed preset sensor data. By adopting the means, the left-right-middle area recognition rate of the intelligent partition can be quickly improved, and the tooth brushing area can be recognized.

Description

Technical Field

[0001] This application relates to the technical field of intelligent products, and particularly to a method and device for identifying brushing areas. Background Art

[0002] The partitioning of smart toothbrushes can be traced back to the 1980s when electric toothbrushes began to gain popularity. The earliest electric toothbrushes had only one speed and one brush head, without partitioning functions. Later, with the development of technology, smart toothbrushes gradually emerged. Smart toothbrushes can automatically adjust the speed and intensity of the brush head according to different regions and tooth types. Modern smart toothbrushes can connect to a smartphone application and automatically adjust the speed, intensity, and time of the brush head according to the user's oral health condition and personal preferences. Some smart toothbrushes can also use sound cues, vibrations, and light displays to help users better control the brushing time and method.

[0003] The main purpose of toothbrush partitioning is to enable people to be more targeted and effective when brushing their teeth, ensuring that every tooth is thoroughly cleaned and promoting better oral health. Toothbrush partitioning mainly uses artificial intelligence algorithms to identify the teeth being brushed by the user, mainly including left, right, up, down, and occlusal surfaces. Each surface includes inner, outer, and molar surfaces. Depending on the complexity of the algorithm, there are several industry partitioning schemes, such as 4, 6, 8, 12, and 16.

[0004] Brushing area detection, as one of the important functions of smart toothbrushes, not only enhances the entertainment of brushing but also effectively prevents missed brushing and protects oral health. However, due to the different brushing methods of each person, the same set of brushing area algorithms may not be applicable to all users. Based on traditional IMU sensors, it is impossible to determine the internal oral position reference, and the starting brushing surface is mainly guessed by probability, unable to achieve 100% recognition. Especially for the upper and lower molar surfaces and the opposite inner and outer sides, the actual postures are basically the same, and the actual recognition rate is very low. Moreover, during complex brushing processes, the algorithm can only judge the position through context fusion. The algorithm learns through user habits by experts and can only cover the common habits of most people, and the measured recognition rates are all very low, affecting the intelligent experience of users. Summary of the Invention

[0005] The embodiments of this application provide a method and device for identifying brushing areas, which can solve the identification of the three major areas of left - right - middle and improve the intelligent recognition rate of brushing areas.

[0006] In a first aspect, the embodiments of this application provide a method for identifying brushing areas, including:

[0007] Obtaining inertial measurement unit (IMU) data of the toothbrush and preset sensor data, where the preset sensor is used to measure distance;

[0008] Process the IMU data and the preset sensor data respectively to obtain the processed IMU data and the processed preset sensor data;

[0009] Based on the processed IMU data and the processed preset sensor data, identify the user's brushing area.

[0010] In the embodiment of the present application, based on the acquired inertial measurement unit (IMU) data and preset sensor data of the toothbrush, they are processed to obtain the processed IMU data and the processed preset sensor data; and then based on the processed IMU data and the processed preset sensor data, the user's brushing area is identified. By adopting this means, combining the IMU data and the distance sensor data can quickly improve the recognition rate of the intelligent partition left - right - middle area, and thus contribute to the identification of the brushing area.

[0011] This distance measurement can be, for example, measuring the distance between the toothbrush head and the teeth or skin, etc. Exemplarily, the preset sensor is located at the toothbrush head, but of course it can also be located at other positions, and this solution does not limit this.

[0012] In a possible implementation manner, the step of identifying the user's brushing area based on the processed IMU data and the processed preset sensor data includes:

[0013] Perform fusion processing on the processed IMU data and the processed preset sensor data to obtain the fused data;

[0014] Based on the fused data, perform processing to obtain the user's brushing area.

[0015] Based on the IMU data and the distance sensor data, the recognition rate of the intelligent partition left - right - middle area can be quickly improved, and thus it is helpful for identifying the brushing area.

[0016] In a possible implementation manner, the step of performing processing based on the fused data to obtain the user's brushing area includes:

[0017] Input the fused data into a preset model for processing to obtain the user's brushing area.

[0018] In this example, by adding a millimeter - wave radar sensor to the toothbrush head and combining AI technology, a set of solutions for the user to accurately identify the brushing area without feeling is provided.

[0019] In a possible implementation manner, the step of processing the IMU data and the preset sensor data respectively to obtain the processed IMU data and the processed preset sensor data includes:

[0020] Truncate, zero-fill and delete the abnormal data in the IMU data and the preset sensor data respectively to obtain the processed IMU data and the processed preset sensor data; and / or,

[0021] Perform data augmentation on the IMU data and the preset sensor data respectively to obtain the processed IMU data and the processed preset sensor data.

[0022] Based on the preprocessing of the acquired data, the reliability of the data can be improved, thereby enhancing the accuracy of brushing area recognition.

[0023] In one possible implementation, the method further includes:

[0024] Perform time delay calibration on the inertial measurement unit IMU and the preset sensor.

[0025] In one possible implementation, the preset sensor is at least one of the following sensors:

[0026] Millimeter wave radar (radar) sensor, contact sensor, photoelectric sensor, acoustic sensor.

[0027] In one possible implementation, the preset model is a time series model.

[0028] In a second aspect, an embodiment of the present application provides a brushing area recognition device, including:

[0029] An acquisition module, configured to acquire inertial measurement unit IMU data of a toothbrush and preset sensor data, where the preset sensor is used to measure distance;

[0030] A preprocessing module, configured to process the IMU data and the preset sensor data respectively to obtain the processed IMU data and the processed preset sensor data;

[0031] A processing module, configured to recognize a brushing area of a user based on the processed IMU data and the processed preset sensor data.

[0032] In one possible implementation, the processing module is configured to:

[0033] Perform fusion processing on the processed IMU data and the processed preset sensor data to obtain fused data;

[0034] Perform processing based on the fused data to obtain the brushing area of the user.

[0035] In one possible implementation, the processing module is further configured to:

[0036] Input the fused data into a preset model for processing to obtain the brushing area of the user.

[0037] In one possible implementation, the preprocessing module is configured to:

[0038] Truncate, fill with zeros, and delete the abnormal data in the IMU data and the preset sensor data respectively to obtain the processed IMU data and the processed preset sensor data; and / or,

[0039] Perform data augmentation on the IMU data and the preset sensor data respectively to obtain the processed IMU data and the processed preset sensor data.

[0040] In one possible implementation, the processing module is further configured to:

[0041] Perform time delay calibration on the inertial measurement unit (IMU) and the preset sensor.

[0042] In one possible implementation, the preset sensor is at least one of the following sensors:

[0043] Millimeter wave radar sensor, contact sensor, photoelectric sensor, acoustic wave sensor.

[0044] In one possible implementation, the preset model is a time series model.

[0045] In a third aspect, an embodiment of the present application provides a brushing area recognition device, including a processor and a memory; wherein, the memory is used to store program codes, and the processor is used to call the program codes to execute the method according to any item in the first aspect.

[0046] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, which stores instructions that, when executed by a processor, implement the method according to any item in the first aspect.

[0047] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program that, when executed, implements the method according to any item in the first aspect.

[0048] For the technical solutions provided in the second to fifth aspects of the present application, the beneficial effects of some embodiments can refer to the beneficial effects of the technical solutions in the first aspect, which will not be elaborated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The following will briefly introduce the drawings used in the description of the embodiments.

[0050] Figure 1aIt is a schematic structural diagram of a brushing area recognition system provided by an embodiment of the present application;

[0051] Figure 1b It is a schematic diagram of a toothbrush provided by an embodiment of the present application;

[0052] Figure 2 It is a schematic flowchart of a brushing area recognition method provided by an embodiment of the present application;

[0053] Figure 3 It is a schematic diagram of brushing area recognition provided by an embodiment of the present application;

[0054] Figure 4 It is a schematic flowchart of a brushing area recognition method provided by an embodiment of the present application;

[0055] Figure 5 It is a schematic structural diagram of a brushing area recognition device provided by an embodiment of the present application;

[0056] Figure 6 It is a schematic structural diagram of another brushing area recognition device provided by an embodiment of the present application. Detailed implementation manners

[0057] The embodiments of the present application will be described below with reference to the accompanying drawings in the embodiments of the present application. The terms used in the implementation manners part of the embodiments of the present application are only used to explain the specific embodiments of the present application, and are not intended to limit the present application.

[0058] For ease of understanding, the following examples give explanations of relevant concepts for reference. As described below:

[0059] 1. Brushing area division: The main purpose of toothbrush area division is to make people more targeted and effective when brushing their teeth, so that each tooth can be cleaned thoroughly and people's teeth can be healthier.

[0060] Brushing area division mainly uses artificial intelligence algorithms to identify the teeth that the user brushes, mainly including left and right, up and down, and occlusal surfaces. The single surface includes inner, outer, and molar surfaces. According to the complexity of the algorithm, there are several industry division schemes, such as 4, 6, 8, 12, and 16. Specifically, as shown in Table 1:

[0061] Table 1

[0062]

[0063] 2. An Inertial Measurement Unit (IMU) is a device used to measure the three-axis attitude angles (or angular rates) and accelerations of an object. Generally, an IMU includes a three-axis gyroscope, a three-axis accelerometer, and a three-axis magnetometer. Among them, the accelerometer detects the acceleration signals of the object on the independent three axes of the carrier coordinate system, while the gyroscope detects the angular velocity signals of the carrier relative to the navigation coordinate system, measures the angular velocity and acceleration of the object in three-dimensional space, and calculates the attitude of the object based on this.

[0064] 3. Millimeter-wave radar sensor: The millimeter-wave radar sensor uses millimeter waves. Generally, millimeter waves refer to the frequency range of 30 - 300 GHz (wavelength of 1 - 10 mm). Among them, 24 GHz radar sensors and 77 GHz radar sensors are mainly used for automotive anti-collision. The wavelength of millimeter waves is between centimeter waves and light waves, so millimeter waves have the advantages of both microwave guidance and optoelectronic guidance. Compared with centimeter-wave radar, millimeter-wave radar has the characteristics of small size, easy integration, and high spatial resolution. Compared with optical sensors such as cameras, infrared, and lasers, millimeter-wave radar has strong ability to penetrate fog, smoke, and dust, strong anti-interference ability, and has the characteristics of all-weather (except heavy rain) and all-time.

[0065] The above exemplary description of the concept can be applied to the embodiments below.

[0066] The following will combine with the drawings to introduce the system architecture of the embodiments of the present application in detail. Please refer to Figure 1a , Figure 1a is a schematic diagram of a toothbrushing area recognition system applicable to the embodiments of the present application. The system includes a terminal 101 and a toothbrush 102.

[0067] Among them, the terminal 101 can also be called a terminal device, user equipment (UE), mobile station, mobile terminal, etc. The terminal can be widely applied to various scenarios, for example, device-to-device (D2D), vehicle to everything (V2X) communication, machine-type communication (MTC), Internet of Things (IoT), virtual reality, augmented reality, industrial control, autonomous driving, remote medical treatment, smart grid, smart furniture, smart office, smart wearables, smart transportation, smart city, etc. The terminal can be a mobile phone, a tablet computer, a computer with wireless transceiver function, a wearable device, a vehicle, a drone, a helicopter, an airplane, a ship, a robot, a robotic arm, a smart home device, etc. The embodiments of the present application do not limit the specific technologies and specific device forms adopted by the terminal.

[0068] Toothbrush 102 usually has multiple modes, such as cleaning mode, massage mode, and rinsing mode, etc. Modern smart toothbrushes can be connected to a smartphone application to automatically adjust the speed, intensity, and time of the brush head according to the user's oral health condition and personal preferences. Some smart toothbrushes can also help users better control the brushing time and method through sound prompts, vibrations, and light displays, etc.

[0069] Exemplarily, the connection between the terminal 101 and the toothbrush 102 can be wireless, for example, through WIFI, Bluetooth, etc. Of course, other methods can also be adopted, and this solution does not limit this.

[0070] As Figure 1b shown, a millimeter-wave antenna is provided on the toothbrush head, and distance measurement can be achieved based on millimeter waves. Of course, sensors such as millimeter-wave antennas can also be set at other positions of the toothbrush, such as the back, etc., and this solution does not limit this.

[0071] It should be noted that the brushing area recognition system can also only include a toothbrush, and a calculation module, a display module, or a voice or other prompt module is provided on the toothbrush body so that the user can know the area where they are brushing their teeth.

[0072] The architecture of the embodiments of the present application has been described above. Next, the methods of the embodiments of the present application will be introduced in detail.

[0073] Referring to Figure 2 shown, it is a schematic flowchart of a method for recognizing a brushing area provided by an embodiment of the present application. Optionally, this method can be applied to the aforementioned brushing area recognition system, for example Figure 1a shown brushing area recognition system. As Figure 2 shown, the method for recognizing a brushing area can include steps 201-203. It should be understood that for the convenience of description, this application describes in the order of 201-203, and does not aim to limit that it must be executed in the above order. The embodiments of the present application do not limit the execution sequence, execution time, execution times, etc. of the above one or more steps. The following describes the execution subjects of steps 201-203 as a mobile phone, and the present application is equally applicable to other execution subjects. Steps 201-203 are specifically as follows:

[0074] 201. Obtain the inertial measurement unit (IMU) data of the toothbrush and the preset sensor data, where the preset sensor is used to measure distance.

[0075] For example, the mobile phone obtains corresponding data from the IMU and the preset sensor. Among them, the IMU data is the attitude data of the toothbrush.

[0076] Exemplarily, the preset sensor is at least one of the following sensors: a millimeter wave radar sensor, a contact sensor, a photoelectric sensor, and an acoustic wave sensor. For example, the preset sensor is set on the brush head of a toothbrush. Based on the preset sensor, the distance between the toothbrush and the teeth or skin can be measured. Figure 3 As shown, for example, the distance between the toothbrush and the teeth / skin can be measured based on a millimeter wave radar sensor. Figure 3 As shown in the leftmost diagram in the figure, based on the measured distance between the toothbrush and the teeth or skin, if it is within the range of 1-3 cm, the area is determined to be the inner side of the teeth. Figure 3 As shown in the middle schematic diagram, based on the measured distance between the toothbrush and the skin, if it is less than or equal to 1 cm, the area is determined to be the outer side of the teeth (the skin-shielded side). Figure 3 As shown in the rightmost schematic diagram, based on the measured distance between the toothbrush and the teeth or skin, if it is within 3 cm, that is, the teeth are not blocked, then the area is determined to be the front teeth.

[0077] This example determines the position in the oral cavity based on the distance between the toothbrush and the teeth or skin, etc., and can distinguish between the inside, outside, and middle, thereby realizing an auxiliary position differentiation function.

[0078] In a possible implementation, before acquiring the above data, the inertial measurement unit IMU and the preset sensor are also subjected to delay calibration. Before measuring, each sensor can be calibrated first. For example, it can be achieved through hardware common clock, or pre-calibration, etc. In this way, the time consistency of the acquired data can be guaranteed, thereby improving the reliability of the data.

[0079] 202. Process the IMU data and the preset sensor data respectively to obtain processed IMU data and processed preset sensor data.

[0080] In a possible implementation, abnormal data in the IMU data and the preset sensor data are truncated, padded with zeros and deleted respectively to obtain processed IMU data and processed preset sensor data.

[0081] For example, invalid data and singular values ​​in the acquired data are judged and filtered out. Specifically, abnormal sensor data frames are truncated and zero-filled. For example, if the actual acceleration of the brushing scene is preset to [-15g, 10g] and the distance is [0, 5cm], then data that does not meet this condition is abnormal data.

[0082] Based on this processing, the model can be made more generalizable.

[0083] In another possible implementation, data augmentation is respectively performed on the IMU data and the preset sensor data to obtain the processed IMU data and the processed preset sensor data. For example, data can be randomly discarded, pinned, and then multiple sensors are merged into multiple-channel data, etc.

[0084] Based on this augmentation process, the generalization of the model can be improved.

[0085] In yet another possible implementation, the abnormal data in the IMU data and the preset sensor data are respectively truncated, filled with zeros and deleted, and data augmentation is performed, thereby obtaining the processed IMU data and the processed preset sensor data.

[0086] For the introduction of this part, reference can be made to the above records and will not be elaborated here.

[0087] Based on the above preprocessing, data with better quality can be obtained, thereby improving the generalization of the model.

[0088] 203. Based on the processed IMU data and the processed preset sensor data, identify the user's brushing area.

[0089] In one possible implementation, fusion processing is performed on the processed IMU data and the processed preset sensor data to obtain the fused data. Furthermore, based on the fused data, processing is performed to obtain the user's brushing area.

[0090] This fusion processing can, for example, be to merge multi-dimensional data into one-dimensional data. Or, it can also be to splice the above-mentioned various data, etc. This solution does not limit this.

[0091] Based on the comprehensive processing of the attitude data obtained from the IMU and the distance data obtained from the preset sensor, the user's brushing area can be identified, and then it can be prompted to the user so that the user can know the areas that have not been brushed, etc.

[0092] In one possible implementation, by inputting the fused data into a preset model for processing, the user's brushing area is obtained.

[0093] Exemplarily, this preset model can be a time series model. The time series model algorithm is a class of machine learning algorithms used to process time series data. It analyzes and models time series data to predict future values or discover the laws and trends in time series data, etc. Optionally, this preset model includes an encoder and a decoder.

[0094] For example, based on the distance position information and attitude frame data with equal sampling rate collected simultaneously during the motion state, a time series model is used for processing, and the obtained data is consistent with the characteristics of the user's brushing area, which can represent the user's real-time brushing position.

[0095] In this example, by leveraging the flexibility of the Artificial Intelligence (AI) model, end-to-end brushing area recognition can be achieved simply and conveniently.

[0096] Of course, other methods can also be used for processing, and this solution does not limit it.

[0097] In the embodiments of this application, based on the obtained inertial measurement unit (IMU) data of the toothbrush and the preset sensor data, processing is performed to obtain the processed IMU data and the processed preset sensor data; then, based on the processed IMU data and the processed preset sensor data, the user's brushing area is identified. By adopting this means, combining the IMU data and the distance sensor data can quickly improve the recognition rate of the intelligent partition left - middle - right area, which helps to identify the brushing area.

[0098] Refer to Figure 4 As shown, it is a schematic diagram of a brushing area recognition process provided by the embodiments of this application. As Figure 4 shown, the method may include steps 401 - 407, specifically as follows:

[0099] 401. Measurement starts.

[0100] The measurement for brushing area recognition starts.

[0101] 402. Delay calibration.

[0102] First, synchronize multiple sensors.

[0103] Among them, for co - terminal devices such as IMU and, for example, millimeter - wave radar sensors, it is achieved through a hardware common clock or pre - calibrated.

[0104] For multiple sensors across terminal devices, it can be achieved based on low - delay communication, such as a delay less than 1ms, etc.

[0105] 403. Communication synchronization.

[0106] At the same time, it is also necessary to ensure the communication synchronization of multiple sensors, such as the communication with the terminal, etc.

[0107] 404. Multiple sensors collect data simultaneously.

[0108] After the above calibration, data collection begins.

[0109] 405. Determine and delete invalid data and singular values.

[0110] Preprocess the data collected by the above-mentioned sensors.

[0111] For example, align the hardware sampling rate: The device can be pre-calibrated, and across devices, it can be pre-agreed through communication.

[0112] For invalid data, screen and remove it by singular value determination: Truncate and delete abnormal data frames of the sensor, and fill with zeros. For example, in the brushing scenario, the actual acceleration is [-15g, 10g], and the distance is [0, 5cm].

[0113] 406. Data augmentation and connection.

[0114] It also includes data augmentation and connection: The data can be randomly discarded and inserted, and multiple sensors can be merged into multi-channel data.

[0115] 407. Artificial intelligence algorithm.

[0116] Based on the processed data above, it can be fused and then input into the model for processing to identify the brushing area.

[0117] For example, model features: Adopt a time series model, simplify the one-dimensional data model, and include an encoder model and a decoder model.

[0118] Sample features: The distance position information and pose frame data collected simultaneously under the motion state and at the same sampling rate.

[0119] Result features: The data is consistent with the features of the user's brushing area and can represent the user's real-time brushing position.

[0120] Loss function features: For example, it can be cross-entropy loss.

[0121] Based on this example, through simulation, the recognition rate is as high as 80%. As shown in Table 2:

[0122] Table 2

[0123]

[0124] In this example, by adding a millimeter-wave radar sensor to the toothbrush head and combining AI technology, a toothbrush that can achieve non-intrusive and accurate identification of the brushing area can be realized.

[0125] It should be noted that in each embodiment of this application, if there is no special description and logical conflict, the terms and / or descriptions between the embodiments are consistent and can be referenced to each other. The technical features in different embodiments can be combined to form new embodiments according to their inherent logical relationships.

[0126] The method of the embodiments of the present application is elaborated in detail above. Below, an apparatus of the embodiments of the present application is provided. It can be understood that in each apparatus embodiment of the present application, the division of multiple units or modules is only a logical division according to functions and does not limit the specific structure of the apparatus. In specific implementation, some of the functional modules may be further divided into more fine-grained functional modules, and some functional modules may also be combined into one functional module. However, no matter whether these functional modules are divided or combined, the general processes executed by the apparatus are the same. For example, some apparatuses include a receiving unit and a transmitting unit. In some designs, the transmitting unit and the receiving unit may also be integrated into a communication unit, and this communication unit can implement the functions implemented by the receiving unit and the transmitting unit. Generally, each unit corresponds to its own program code (or program instructions). When the program codes corresponding to these units run on the processor, the unit is controlled by the processing unit to execute the corresponding process to implement the corresponding function.

[0127] The embodiments of the present application also provide an apparatus for implementing any of the above methods. For example, a toothbrushing area recognition apparatus is provided, which includes units (or means) for implementing each step executed by the mobile phone in any of the above methods.

[0128] For example, with reference to Figure 5 As shown, it is a schematic structural diagram of a toothbrushing area recognition apparatus provided by the embodiments of the present application. This toothbrushing area recognition apparatus is used to implement the aforementioned toothbrushing area recognition method, for example Figure 2 the toothbrushing area recognition method shown.

[0129] As Figure 5 shown, the apparatus may include an acquisition module 501, a preprocessing module 502, and a processing module 503, specifically as follows:

[0130] The acquisition module 501 is used to acquire inertial measurement unit (IMU) data of the toothbrush and preset sensor data, and the preset sensor is used to measure distance;

[0131] The preprocessing module 502 is used to process the IMU data and the preset sensor data respectively to obtain processed IMU data and processed preset sensor data;

[0132] The processing module 503 is used to identify the user's toothbrushing area based on the processed IMU data and the processed preset sensor data.

[0133] In a possible implementation manner, the processing module 503 is used to:

[0134] Perform fusion processing on the processed IMU data and the processed preset sensor data to obtain fused data;

[0135] Process the fused data to obtain the brushing area of the user.

[0136] In a possible implementation, the processing module 503 is further configured to:

[0137] Input the fused data into a preset model for processing to obtain the brushing area of the user.

[0138] In a possible implementation, the preprocessing module 502 is configured to:

[0139] Truncate, fill with zeros, and delete the abnormal data in the IMU data and the preset sensor data respectively to obtain the processed IMU data and the processed preset sensor data; and / or,

[0140] Perform data augmentation on the IMU data and the preset sensor data respectively to obtain the processed IMU data and the processed preset sensor data.

[0141] In a possible implementation, the processing module 503 is further configured to:

[0142] Perform time delay calibration on the inertial measurement unit IMU and the preset sensor.

[0143] In a possible implementation, the preset sensor is at least one of the following sensors:

[0144] Millimeter wave radar sensor, contact sensor, photoelectric sensor, acoustic sensor.

[0145] In a possible implementation, the preset model is a time series model.

[0146] For the introduction of each of the above modules, reference may be made to the records in the foregoing method embodiments, which will not be elaborated here.

[0147] In the embodiments of the present application, based on the acquired inertial measurement unit IMU data and preset sensor data of the toothbrush, the processed IMU data and the processed preset sensor data are obtained; and then based on the processed IMU data and the processed preset sensor data, the brushing area of the user is identified. By adopting this means, combining the IMU data and the distance sensor data can quickly improve the recognition rate of the intelligent partition left - middle - right area, and thus help to identify the brushing area.

[0148] It should be understood that the division of each unit in the above-mentioned toothbrushing area recognition device is only a division of logical functions. In actual implementation, it can be fully or partially integrated into a physical entity, or physically separated. In addition, the units in the toothbrushing area recognition device can be implemented in the form of a processor calling software; for example, the toothbrushing area recognition device includes a processor, the processor is connected to a memory, and instructions are stored in the memory. The processor calls the instructions stored in the memory to implement any of the above methods or the functions of each unit of the device. The processor is, for example, a general-purpose processor, such as a central processing unit (CPU) or a microprocessor, and the memory is a memory inside or outside the device. Alternatively, the units in the device can be implemented in the form of a hardware circuit, and the functions of some or all of the units can be implemented by designing the hardware circuit. The hardware circuit can be understood as one or more processors; for example, in one implementation, the hardware circuit is an application-specific integrated circuit (ASIC), and the functions of some or all of the above units are implemented by designing the logical relationship of the components in the circuit; again, in another implementation, the hardware circuit can be implemented by a programmable logic device (PLD). Taking a field programmable gate array (FPGA) as an example, it can include a large number of logic gate circuits, and the connection relationship between the logic gate circuits is configured through a configuration file to implement the functions of some or all of the above units. All units of the above device can be fully implemented in the form of a processor calling software, or fully implemented in the form of a hardware circuit, or partially implemented in the form of a processor calling software, and the remaining part is implemented in the form of a hardware circuit.

[0149] Referring to Figure 6 As shown, it is a schematic diagram of the hardware structure of another toothbrushing area recognition device provided by an embodiment of the present application. As Figure 6 shown, the toothbrushing area recognition device 600 (the device 600 can specifically be a computer device) includes a memory 601, a processor 602, a communication interface 603, and a bus 604. Among them, the memory 601, the processor 602, and the communication interface 603 are communicatively connected to each other through the bus 604.

[0150] The memory 601 can be a read only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM).

[0151] The memory 601 may store a program. When the program stored in the memory 601 is executed by the processor 602, the processor 602 and the communication interface 603 are used to execute the respective steps of the toothbrushing area recognition method according to the embodiments of the present application.

[0152] The processor 602 is a circuit with signal processing capabilities. In one implementation, the processor 602 may be a circuit with instruction reading and running capabilities, such as a central processing unit (CPU), a microprocessor, a graphics processing unit (GPU) (which can be understood as a type of microprocessor), or a digital signal processor (DSP), etc. In another implementation, the processor 602 may implement certain functions through the logical relationship of a hardware circuit, and the logical relationship of this hardware circuit is fixed or can be reconfigured. For example, the processor 602 is a hardware circuit implemented by an ASIC or a programmable logic device (PLD), such as an FPGA. In a reconfigurable hardware circuit, the process of the processor loading a configuration document to implement the configuration of the hardware circuit can be understood as the process of the processor loading instructions to implement the functions of some or all of the above units. In addition, it may also be a hardware circuit designed for artificial intelligence, which can be understood as a type of ASIC, such as a neural network processing unit (NPU), a tensor processing unit (TPU), a deep learning processing unit (DPU), etc. The processor 602 is used to execute relevant programs to implement the functions required by the units in the toothbrushing area recognition device according to the embodiments of the present application, or to execute the toothbrushing area recognition method according to the method embodiments of the present application.

[0153] It can be seen that each unit in the above device may be one or more processors (or processing circuits) configured to implement the above method. For example: CPU, GPU, NPU, TPU, DPU, microprocessor, DSP, ASIC, FPGA, or a combination of at least two of these processor forms.

[0154] In addition, each unit in the above device may be integrated in whole or in part, or may be independently implemented. In one implementation, these units are integrated together and implemented in the form of a system-on-a-chip (SOC). The SOC may include at least one processor for implementing any of the above methods or the functions of each unit of the device. The types of the at least one processor may be different. For example, it includes a CPU and an FPGA, a CPU and an artificial intelligence processor, a CPU and a GPU, etc.

[0155] The communication interface 603 uses a transceiver device such as, but not limited to, a transceiver to implement communication between the device 600 and other devices or communication networks. For example, data can be obtained through the communication interface 603.

[0156] The bus 604 may include a path for transmitting information between various components of the device 600 (for example, the memory 601, the processor 602, the communication interface 603).

[0157] It should be noted that although Figure 6 the illustrated device 600 only shows a memory, a processor, and a communication interface, in the specific implementation process, those skilled in the art should understand that the device 600 also includes other devices necessary for normal operation. At the same time, according to specific needs, those skilled in the art should understand that the device 600 may also include hardware devices for implementing other additional functions. In addition, those skilled in the art should understand that the device 600 may also only include the devices necessary for implementing the embodiments of the present application, and do not necessarily include Figure 6 all the devices shown in

[0158] The embodiments of the present application also provide a computer-readable storage medium, in which a computer program is stored, and the computer program is used to implement one or more steps in the toothbrushing area recognition method as described in the foregoing embodiments.

[0159] The embodiments of the present application also provide a computer program product, when the computer program product runs on a computer, it causes the computer to execute one or more steps in the toothbrushing area recognition method as described in the foregoing embodiments.

[0160] Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the above-described systems, devices, and units can refer to the corresponding step processes in the foregoing method embodiments, and will not be elaborated here.

[0161] It should be understood that in the description of the present application, unless otherwise specified, " / " indicates that the objects associated before and after are in an "or" relationship, for example, A / B can represent A or B; wherein A and B can be singular or plural. Also, in the description of the present application, unless otherwise specified, "multiple" refers to two or more than two. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, wherein a, b, c can be single or multiple. In addition, in order to facilitate the clear description of the technical solutions of the embodiments of the present application, in the embodiments of the present application, the words "first", "second", etc. are used to distinguish the same items or similar items with substantially the same functions and effects. Those skilled in the art can understand that the words "first", "second", etc. do not limit the quantity and execution order, and the words "first", "second", etc. do not limit them to be necessarily different. Meanwhile, in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a concrete manner for ease of understanding.

[0162] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the division of the unit is only a logical function division, and there may be other division methods in actual implementation, for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. The mutual coupling, direct coupling, or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0163] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0164] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions according to the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions can be transmitted from a website, computer, server, or data center to another website, computer, server, or data center in a wired manner (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wirelessly (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that includes one or more integrated available media. The available medium can be a read-only memory (ROM), a random access memory (RAM), a magnetic medium, such as a floppy disk, a hard disk, a magnetic tape, a magnetic disk, or an optical medium, such as a digital versatile disc (DVD), or a semiconductor medium, such as a solid state disk (SSD), etc.

[0165] As described above, the above are only the specific implementation manners of the embodiments of the present application, but the protection scope of the embodiments of the present application is not limited thereto. Any changes or substitutions within the technical scope disclosed in the embodiments of the present application should be covered by the protection scope of the embodiments of the present application. Therefore, the protection scope of the embodiments of the present application should be subject to the protection scope of the claims.

Claims

1. A method for identifying a brushing area, characterized in that, it includes: Obtaining inertial measurement unit (IMU) data of a toothbrush and preset sensor data, where the preset sensor is used to measure distance; Processing the IMU data and the preset sensor data respectively to obtain processed IMU data and processed preset sensor data; Based on the processed IMU data and the processed preset sensor data, identifying the user's brushing area.

2. The method according to claim 1, characterized in that, the identifying the user's brushing area based on the processed IMU data and the processed preset sensor data includes: Performing fusion processing on the processed IMU data and the processed preset sensor data to obtain fused data; Processing based on the fused data to obtain the user's brushing area.

3. The method according to claim 2, characterized in that, the processing based on the fused data to obtain the user's brushing area includes: Inputting the fused data into a preset model for processing to obtain the user's brushing area.

4. The method according to any one of claims 1 - 3, characterized in that, the processing the IMU data and the preset sensor data respectively to obtain processed IMU data and processed preset sensor data includes: Respectively truncating, filling with zeros and deleting abnormal data in the IMU data and the preset sensor data to obtain processed IMU data and processed preset sensor data; and / or, Performing data augmentation on the IMU data and the preset sensor data respectively to obtain processed IMU data and processed preset sensor data.

5. The method according to any one of claims 1 - 4, characterized in that, the method further includes: Performing time delay calibration on the inertial measurement unit (IMU) and the preset sensor.

6. The method according to any one of claims 1 - 5, characterized in that, the preset sensor is at least one of the following sensors: Millimeter wave radar sensor, contact sensor, photoelectric sensor, acoustic sensor.

7. The method according to claim 3, characterized in that, the preset model is a time series model.

8. A device for identifying a brushing area, characterized in that, it includes: An acquisition module for obtaining inertial measurement unit (IMU) data of a toothbrush and preset sensor data, where the preset sensor is used to measure distance; A preprocessing module for processing the IMU data and the preset sensor data respectively to obtain processed IMU data and processed preset sensor data; A processing module for identifying the user's brushing area based on the processed IMU data and the processed preset sensor data.

9. The device according to claim 8, characterized in that, the processing module is used for: Performing fusion processing on the processed IMU data and the processed preset sensor data to obtain fused data; Process the fused data to obtain the user's brushing area.

10. The apparatus according to claim 9, wherein, the processing module is further configured to: input the fused data into a preset model for processing to obtain the user's brushing area.

11. The apparatus according to any one of claims 8-10, wherein, the preprocessing module is configured to: respectively truncate, fill zeros, and delete abnormal data in the IMU data and the preset sensor data to obtain processed IMU data and processed preset sensor data; and / or, respectively perform data augmentation on the IMU data and the preset sensor data to obtain processed IMU data and processed preset sensor data.

12. The apparatus according to any one of claims 8-11, wherein, the processing module is further configured to: perform time delay calibration on the inertial measurement unit IMU and the preset sensor.

13. The apparatus according to any one of claims 8-12, wherein, the preset sensor is at least one of the following sensors: millimeter wave radar sensor, contact sensor, photoelectric sensor, acoustic wave sensor.

14. The apparatus according to claim 10, wherein, the preset model is a time series model.

15. A brushing area recognition apparatus, wherein, it includes a processor and a memory; wherein, the memory is used to store program codes, and the processor is used to call the program codes to execute the method according to any one of claims 1-7.

16. A computer-readable storage medium, wherein, the computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the method according to any one of claims 1 to 7.

17. A computer program product, wherein, when the computer program product runs on a computer, it causes the computer to execute the method according to any one of claims 1 to 7.

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