A tooth brushing area recognition method, recognition device and electronic device

Abstract

The application provides a tooth brushing area identification method, an identification device and an electronic device. The identification method comprises the following steps: acquiring spatial axis acceleration and spatial axis angular velocity corresponding to a current moment of a tooth brushing device in a tooth brushing process in a target oral cavity; determining whether an angular velocity standard deviation corresponding to the spatial axis angular velocity meets an area switching condition; if yes, updating a posture angle; if not, determining a tooth brushing movement direction corresponding to the current moment according to posture angle data corresponding to a previous moment adjacent to the current moment among moments meeting the area switching condition; and determining a tooth brushing area corresponding to the current moment of the tooth brushing device according to a tooth brushing device orientation corresponding to the current moment determined by the spatial axis acceleration and the tooth brushing movement direction. Through the above method, the calculation amount of the tooth brushing device in the tooth brushing area identification process is reduced, and the area identification accuracy is improved.

Description

Technical Field

[0001] This application relates to the field of area recognition technology, and in particular to a method, device and electronic device for recognizing brushing areas. Background Technology

[0002] With the improvement of people's living standards, dental diseases have become very common. For example, periodontal disease, gingivitis, and cavities are mostly the result of bacteria depositing on the tooth surface. If brushing is not done properly, bacteria will accumulate on the tooth surface, forming plaque, damaging tooth enamel and causing gingivitis, thus leading to cavities and gum disease. Therefore, thoroughly cleaning teeth while brushing daily can effectively reduce plaque and prevent oral diseases. The American Dental Association recommends the Bass brushing technique, which requires brushing at least twice a day for two minutes each time. With the introduction and promotion of smart toothbrushes, people's hands are freed up, and the total brushing time is standardized. However, most people do not allocate brushing time evenly to each tooth, resulting in some teeth not being thoroughly cleaned. Comprehensive brushing area monitoring can effectively monitor the brushing quality of all teeth.

[0003] Currently, brushing motion recognition based on inertial sensors is the main research direction, primarily including deep learning, classification, and pose estimation methods. Among these, deep learning algorithms are computationally intensive and complex to engineer, making them difficult to apply to smart toothbrush chips. Furthermore, due to the limited space in the oral cavity and the small range of toothbrush movement, and the need for classifying brushing motions across multiple areas, it is difficult to build accurate models, resulting in poor accuracy for small-scale movements using classification methods. Additionally, when using accelerometers for pose estimation to measure a user's brushing posture, the stability and accuracy of posture recognition are poor. Summary of the Invention

[0004] In view of this, the purpose of this application is to provide a method, device, and electronic device for identifying brushing areas. By acquiring the spatial axis acceleration and angular velocity of the brushing device during brushing in the target oral cavity, a pre-built neural network model is used to identify the orientation of the brushing device and determine whether a brushing area switching action has occurred. When the brushing area is switched, the posture angle is updated. When the brushing area is maintained, the brushing motion direction is determined based on the posture angle. By combining the orientation of the brushing device, the brushing motion direction in the oral cavity, and the spatial axis acceleration, the brushing area of ​​the target oral cavity where the brushing device is located is identified. This reduces the computational load when the brushing device identifies the brushing area, thereby improving the accuracy of the brushing device's area recognition.

[0005] This application provides a method for identifying brushing areas, the method comprising:

[0006] Acquire the spatial axis acceleration and spatial axis angular velocity at the current moment during the brushing process of the brushing device in the target oral cavity;

[0007] Based on the standard deviation of the angular velocity corresponding to the spatial axis angular velocity, determine whether the standard deviation of the angular velocity satisfies the region switching condition;

[0008] When the standard deviation of the angular velocity at the current moment meets the region switching condition, the attitude angle is updated based on the spatial axis acceleration and the spatial axis angular velocity.

[0009] When the standard deviation of the angular velocity at the current moment does not meet the region switching condition, the brushing motion direction of the brushing device at the current moment is determined based on the attitude angle data corresponding to the previous moment adjacent to the current moment among the moments that meet the region switching condition.

[0010] Based on the orientation of the brushing device at the current moment, determined by the spatial axis acceleration, and the direction of brushing motion, the brushing area corresponding to the brushing device at the current moment is determined.

[0011] This application embodiment also provides a tooth brushing area recognition device, the recognition device comprising:

[0012] The data acquisition module is used to acquire the spatial axis acceleration and spatial axis angular velocity at the current moment during the brushing process of the brushing device in the target oral cavity;

[0013] The condition judgment module is used to determine whether the standard deviation of the angular velocity corresponding to the angular velocity of the spatial axis satisfies the region switching condition.

[0014] The attitude update module is used to update the attitude angle based on the spatial axis acceleration and the spatial axis angular velocity when the standard deviation of the angular velocity at the current moment meets the region switching condition.

[0015] The direction determination module is used to determine the brushing motion direction of the brushing device at the current moment based on the attitude angle data corresponding to the previous moment adjacent to the current moment when the standard deviation of the angular velocity at the current moment does not meet the region switching conditions.

[0016] The region determination module is used to determine the brushing region corresponding to the brushing device at the current moment based on the brushing device orientation and the brushing motion direction determined by the spatial axis acceleration.

[0017] This application also provides an electronic device, including: a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor communicates with the memory via the bus. When the machine-readable instructions are executed by the processor, the steps of the brushing area recognition method described above are performed.

[0018] The brushing area identification method, identification device, and electronic device provided in this application include: acquiring the spatial axis acceleration and spatial axis angular velocity corresponding to the current moment during the brushing process of the brushing device in the target oral cavity; determining whether the standard deviation of the angular velocity corresponding to the spatial axis angular velocity satisfies the area switching condition; when the standard deviation of the angular velocity corresponding to the current moment satisfies the area switching condition, updating the attitude angle based on the spatial axis acceleration and the spatial axis angular velocity; when the standard deviation of the angular velocity corresponding to the current moment does not satisfy the area switching condition, determining the brushing motion direction of the brushing device at the current moment based on the attitude angle data corresponding to the previous moment adjacent to the current moment among the moments that satisfy the area switching condition; and determining the brushing area corresponding to the brushing device at the current moment based on the brushing device orientation determined by the spatial axis acceleration and the brushing motion direction.

[0019] Compared with existing technologies that use inertial sensors for brushing motion recognition, including deep learning, classification, and attitude estimation, this method uses the spatial axis acceleration and angular velocity of the brushing device during brushing in the target oral cavity. A pre-built neural network model is then used to identify the orientation of the brushing device and determine whether a brushing area switching action has occurred. When the brushing area switches, the attitude angle is updated; when the brushing area is maintained, the brushing motion direction is determined based on the attitude angle. By combining the brushing device's orientation, the brushing motion direction in the oral cavity, and the spatial axis acceleration, the brushing area of ​​the target oral cavity where the brushing device is located is identified. This reduces the computational load when the brushing device identifies the brushing area, thereby improving the accuracy of the brushing device's area recognition.

[0020] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0021] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 A flowchart illustrating a method for identifying brushing areas provided in an embodiment of this application;

[0023] Figure 2 This is a schematic diagram of the architecture of a neural network model provided in an embodiment of this application;

[0024] Figure 3 This is a schematic diagram of a brushing area in a target oral cavity provided in an embodiment of this application;

[0025] Figure 4 This is a schematic diagram illustrating the recognition effect of a brushing area provided in an embodiment of this application;

[0026] Figure 5 This is a schematic diagram of the structure of a toothbrushing area recognition device provided in an embodiment of this application;

[0027] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. Based on the embodiments of this application, every other embodiment obtained by those skilled in the art without inventive effort falls within the scope of protection of this application.

[0029] Research has revealed that current research focuses on brushing motion recognition based on inertial sensors, primarily employing deep learning, classification, and pose estimation methods. However, deep learning algorithms are computationally intensive and complex to implement, making them difficult to apply to smart toothbrush chips. Furthermore, the limited space in the oral cavity and the small range of toothbrush movement, coupled with the need for classifying brushing motions across multiple areas, makes it challenging to establish accurate models, resulting in poor accuracy for small-scale movements using classification methods. Additionally, accelerometer-based pose estimation for user brushing posture measurement exhibits poor stability and accuracy in identifying brushing postures.

[0030] Based on this, this application provides a method for identifying brushing areas. By acquiring the spatial axis acceleration and spatial axis angular velocity of the brushing device during brushing in the target oral cavity, a pre-built neural network model is used to identify the orientation of the brushing device and determine whether a brushing area switching action has occurred. When the brushing area is switched, the posture angle is updated. When the brushing area is maintained, the brushing motion direction is determined based on the posture angle. By combining the orientation of the brushing device, the brushing motion direction in the oral cavity, and the spatial axis acceleration, the brushing area of ​​the target oral cavity where the brushing device is located is identified. This reduces the amount of computation when the brushing device identifies the brushing area, thereby improving the accuracy of the brushing device's area identification.

[0031] Please see Figure 1 , Figure 1 This is a flowchart illustrating a method for identifying brushing areas provided in an embodiment of this application. Figure 1 As shown in the embodiments of this application, the method for identifying brushing areas includes:

[0032] S101. Obtain the spatial axis acceleration and spatial axis angular velocity at the current moment during the brushing process of the brushing device in the target oral cavity.

[0033] It should be noted that brushing devices are devices that can be used to brush teeth in the target oral cavity, such as electric toothbrushes, smart toothbrushes, dental irrigators, and water flossers.

[0034] In this step, in response to the brushing action of the brushing device in the target oral cavity, the spatial axis acceleration and spatial axis angular velocity of the brushing device at the current moment during the brushing process are acquired by the sensing module set in the brushing device.

[0035] In one possible embodiment of this application, the spatial axis acceleration includes: horizontal axis acceleration, vertical axis acceleration, and vertical axis acceleration; the spatial axis angular velocity includes: horizontal axis angular velocity, vertical axis angular velocity, and vertical axis angular velocity. Corresponding to a spatial rectangular coordinate system, the horizontal axis, vertical axis, and vertical axis are the X-axis, Y-axis, and Z-axis, respectively. At time k, the spatial axis acceleration is (f... x.k ,f y,k ,f z,k ), the spatial axis angular velocity is (w x,k ,w y,k ,w z,k ).

[0036] The sensing module installed in the toothbrush device can be detached or fixed in connection with the device; the sensing module includes an inertial measurement unit (IMU), or data acquisition devices such as a three-axis accelerometer and a three-axis gyroscope.

[0037] S102. Determine whether the standard deviation of the angular velocity corresponding to the spatial axis angular velocity satisfies the region switching condition.

[0038] It should be noted that when identifying the brushing area, it is necessary to determine whether the current brushing action involves area switching. In order to update the posture data of the brushing action when the area is switched, and to determine the specific brushing area when the area is not switched.

[0039] In this step, in specific implementation, firstly, based on the horizontal axis angular velocity, vertical axis angular velocity, and vertical axis angular velocity of the brushing device at the current moment, the mean value of the spatial axis angular velocity of the brushing device at the current moment is determined; then, using a preset standard deviation calculation formula, the standard deviation of the angular velocity of the brushing device at the current moment is determined; finally, based on the numerical relationship between the standard deviation of the angular velocity and the standard deviation threshold, it is determined whether the standard deviation of the angular velocity at the current moment meets the area switching condition.

[0040] In a possible implementation of this application, step S102 may include:

[0041] S1021. Based on the horizontal axis angular velocity, vertical axis angular velocity, and vertical axis angular velocity of the brushing device at the current moment, the average value of the spatial axis angular velocity of the brushing device at the current moment is determined.

[0042] In this step, the mean value of the spatial axis angular velocity of the brushing device at the current moment is determined by using the mean value calculation formula, based on the horizontal axis angular velocity, vertical axis angular velocity, and vertical axis angular velocity of the brushing device at the current moment, which are included in the spatial axis angular velocity.

[0043] Specifically, the formula for calculating the mean of the spatial axis angular velocity is shown below.

[0044]

[0045] in, The mean angular velocity of the brushing device's spatial axis at the current time (time k); w x,k w y,k w z,k These are the horizontal (X-axis) angular velocity, vertical (Y-axis) angular velocity, and vertical (Z-axis) angular velocity at the current time (k time), respectively.

[0046] S1022. Based on the mean of the horizontal axis angular velocity, the vertical axis angular velocity, the vertical axis angular velocity, and the spatial axis angular velocity, the standard deviation of the angular velocity of the toothbrush device at the current moment is determined using a preset standard deviation calculation formula.

[0047] In this step, the mean values ​​of the horizontal axis angular velocity, vertical axis angular velocity, and spatial axis angular velocity at the current moment are substituted into the preset standard deviation calculation formula to calculate and determine the standard deviation of the angular velocity of the brushing device at the current moment.

[0048] Specifically, the preset standard deviation calculation formula is shown below.

[0049]

[0050] Where σ is the standard deviation of the angular velocity of the brushing device at the current moment; The mean angular velocity of the brushing device's spatial axis at the current time (time k); w x,k w y,k w z,k These are the horizontal (X-axis) angular velocity, vertical (Y-axis) angular velocity, and vertical (Z-axis) angular velocity at the current time (k time), respectively.

[0051] S1023. Based on the numerical relationship between the standard deviation of the angular velocity and the standard deviation threshold, determine whether the standard deviation of the angular velocity meets the region switching conditions.

[0052] In this step, the calculated standard deviation of angular velocity is compared with the standard deviation threshold to determine the numerical relationship between the standard deviation of angular velocity and the standard deviation threshold. Then, when the standard deviation of angular velocity is greater than the standard deviation threshold, it is determined that the standard deviation of angular velocity meets the area switching condition; when the standard deviation of angular velocity is less than or equal to the standard deviation threshold, it is determined that the standard deviation of angular velocity does not meet the area switching condition.

[0053] In one possible implementation of this application, the standard deviation threshold is a calibrated value of the standard deviation of the angular velocity when the brushing action switches areas, set based on experience from testing experiments of the brushing device.

[0054] Here, by determining whether the standard deviation of the angular velocity meets the region switching condition, it is further determined whether the brushing action posture performed by the brushing device at the current moment is switching the brushing region.

[0055] Specifically, the brushing action posture corresponding to the area switching condition is represented as follows.

[0056]

[0057] Wherein, mode is the brushing action posture corresponding to the area switching condition; move is when the angular velocity standard deviation meets the area switching condition (angular velocity standard deviation σ is greater than the standard deviation threshold σTH), that is, the brushing action posture is switching the brushing area; keep is when the angular velocity standard deviation does not meet the area switching condition, that is, the brushing action posture is maintaining the original action posture and does not switch the brushing area.

[0058] In a possible implementation of this application, step S1023 may include:

[0059] S10231. Compare the standard deviation of the angular velocity with the standard deviation threshold to determine the numerical relationship between the standard deviation of the angular velocity and the standard deviation threshold.

[0060] In this step, the standard deviation of angular velocity is compared with the standard deviation threshold to determine whether the standard deviation of angular velocity is greater than the standard deviation threshold, and then to determine whether the standard deviation of angular velocity meets the area switching conditions.

[0061] S10232. When the numerical relationship is that the standard deviation of the angular velocity is greater than the standard deviation threshold, it is determined that the standard deviation of the angular velocity satisfies the region switching condition.

[0062] In this step, when the standard deviation of angular velocity is greater than the standard deviation threshold, it is determined that the standard deviation of angular velocity meets the area switching condition, that is, the brushing action posture performed by the brushing device at the current moment is switching the brushing area.

[0063] S10233. When the numerical relationship is that the standard deviation of the angular velocity is less than or equal to the standard deviation threshold, it is determined that the standard deviation of the angular velocity does not meet the region switching condition.

[0064] In this step, when the numerical relationship is that the standard deviation of angular velocity is less than or equal to the standard deviation threshold, it is determined that the standard deviation of angular velocity does not meet the area switching condition. That is, the brushing device maintains its original brushing posture at the current moment and does not switch the brushing area.

[0065] S103. When the standard deviation of the angular velocity at the current moment meets the region switching condition, the attitude angle is updated based on the spatial axis acceleration and the spatial axis angular velocity.

[0066] In this step, if the standard deviation of the angular velocity at the current moment meets the region switching condition, the attitude angle data of the brushing action posture of the brushing device needs to be updated using the spatial axis acceleration and spatial axis angular velocity.

[0067] In practice, firstly, based on the horizontal, vertical, and axial accelerations of the brushing device at the current moment, the initial attitude angle data for the current moment is determined. Then, based on the initial attitude angle data, the initial quaternion for the current moment is obtained. Next, based on the initial quaternion and the antisymmetric matrix of the angular velocity corresponding to the spatial axis angular velocity, the quaternion for the current moment is obtained using a preset attitude error expression. Finally, based on the quaternion for the current moment, the attitude angle data for the current moment is obtained.

[0068] In one possible implementation of this application, the attitude angle data includes, but is not limited to, the roll angle, the pitch angle, and the yaw angle.

[0069] In a possible implementation of this application, step S103 may include:

[0070] S1031. Based on the horizontal axis acceleration, vertical axis acceleration and vertical axis acceleration of the brushing device at the current moment, which are included in the spatial axis acceleration, determine the initial attitude angle data corresponding to the current moment.

[0071] In this step, based on the horizontal, vertical, and longitudinal accelerations of the brushing device at the current moment, the initial roll angle and initial pitch angle values ​​at the current moment are determined using preset initial roll angle calculation formulas and initial pitch angle calculation formulas, respectively; then, combined with the preset initial heading angle value, the initial attitude angle data at the current moment is determined.

[0072] In one possible implementation of this application, the initial heading angle The angle value is set to 150°, but is not limited to 150°, and can also be other angle values; the initial heading angle value is specifically set according to the actual application requirements of the brushing device, and this application will not limit it here.

[0073] Specifically, the preset initial roll angle calculation formula is shown below.

[0074]

[0075] Where γ0 is the initial roll angle value; f x,k and f z,k These represent the horizontal and vertical accelerations of the brushing device at the current moment (time k).

[0076] Specifically, the preset initial pitch angle calculation formula is shown below.

[0077]

[0078] Where θ0 is the initial pitch angle; f y,k Let g be the vertical acceleration of the brushing device at the current time (time k); g is the gravitational acceleration of the area where the brushing device is located.

[0079] S1032. Based on the initial attitude angle data, obtain the initial quaternion corresponding to the current moment.

[0080] In this step, based on the initial roll angle, initial pitch angle, and initial heading angle included in the initial attitude angle data, the initial quaternion corresponding to the current time is obtained using the preset correspondence between the initial attitude angle data and the initial quaternion.

[0081] Specifically, the correspondence between the preset initial attitude angle data and the initial quaternion is shown below.

[0082]

[0083] Where q0 is the initial quaternion corresponding to the current moment; λ1, λ2, λ3 and λ4 are the elements corresponding to the matrix expression of the initial quaternion; γ0 is the initial roll angle; θ0 is the initial pitch angle. This is the initial heading angle value.

[0084] S1033. Perform recursive transformation on the initial quaternion to obtain the quaternion corresponding to the current time, and obtain the attitude angle data corresponding to the current time that satisfies the area switching condition based on the quaternion corresponding to the current time, so as to update the attitude angle.

[0085] In this step, in specific implementation, firstly, an antisymmetric matrix of angular velocity is established based on the spatial axis angular velocity corresponding to the current moment; then, using the preset attitude error expression and the antisymmetric matrix of angular velocity, the initial quaternion is recursively transformed to obtain the quaternion corresponding to the current moment; finally, based on the quaternion corresponding to the current moment, the attitude angle data corresponding to the current moment that satisfies the area switching condition is obtained.

[0086] In a possible implementation of this application, step S1033 may include:

[0087] S10331. Based on the spatial axis angular velocity, establish the antisymmetric matrix of the angular velocity at the current moment.

[0088] In this step, an angular velocity matrix corresponding to the current moment is established based on the horizontal axis angular velocity, vertical axis angular velocity, and vertical axis angular velocity respectively; then, the angular velocity matrix is ​​antisymmetric to establish an antisymmetric angular velocity matrix corresponding to the current moment.

[0089] S10332. Based on the angular velocity antisymmetric matrix, the initial quaternion at the current moment is recursively transformed using a preset attitude error expression to obtain the quaternion corresponding to the current moment.

[0090] In this step, the antisymmetric matrix of the angular velocity at the current moment is substituted into the preset attitude error expression, and a recursive transformation is performed starting from the initial quaternion (q0) at the current moment to obtain the quaternion (q) at the current moment.k ).

[0091] Specifically, the preset attitude error expression is shown below.

[0092]

[0093] in, The time derivative of a quaternion; [w k(t) [×] is the antisymmetric matrix of the angular velocity at the current time (time k).

[0094] S10333. Based on the quaternion corresponding to the current time, obtain the attitude angle data corresponding to the current time that satisfies the area switching conditions, so as to update the attitude angle.

[0095] In this step, the quaternion corresponding to the current moment is first converted into a matrix expression; then, the transformation matrix is ​​obtained based on the matrix expression of the quaternion corresponding to the current moment; finally, the attitude angle data corresponding to the current moment that satisfies the area switching condition is obtained based on the transformation matrix.

[0096] Specifically, the four-element matrix expression corresponding to the current moment is shown below.

[0097]

[0098] Where, q k λ is the quaternion corresponding to the current time step. k1 , λ k2 , λ k3 and λ k4 These are the elements in the matrix expression of the quaternion at the current time.

[0099] Furthermore, the expression for the transformation matrix is ​​obtained from the matrix expression of the quaternion corresponding to the current moment, as shown below.

[0100]

[0101] Where C is the transformation matrix; C ij λ is the matrix element in the i-th row and j-th column of the transformation matrix; k1 , λ k2 , λ k3 and λ k4 These are the elements in the matrix expression of the quaternion at the current time.

[0102] Furthermore, the attitude angle data corresponding to the current moment that satisfies the area switching conditions is obtained according to the transformation matrix. The attitude angle data corresponding to the current moment includes the angle values ​​of the roll angle, pitch angle, and yaw angle corresponding to the current moment.

[0103] Specifically, the expression for the roll angle value at the current moment is as follows.

[0104]

[0105] Where, γ k C is the roll angle value corresponding to the current time (time k); 13 For "2(λ) k2 λ k4 -λ k1 λ k3 )”;C 33 for λ k1 , λ k2 , λ k3 and λ k4 These are the elements in the matrix expression of the quaternion at the current time.

[0106] Furthermore, the expression for the pitch angle value corresponding to the current moment is shown below.

[0107]

[0108] Where, θ k C is the pitch angle value corresponding to the current time (time k); 21 For "2(λ) k2 λ k3 -λ k1 λ k4 )”;C 22 for C 23 For "2(λ) k4 λ k3 +λ k1 λ k2 )”;λ k1 , λ k2 , λ k3 and λ k4 These are the elements in the matrix expression of the quaternion at the current time.

[0109] Furthermore, the expression for the heading angle value corresponding to the current moment is shown below.

[0110]

[0111] in, C is the heading angle value corresponding to the current time (time k); 21 For "2(λ) k2 λ k3 -λ k1 λ k4 )”;C22 for λ k1 , λ k2 , λ k3 and λ k4 These are the elements in the matrix expression of the quaternion at the current time.

[0112] S104. When the standard deviation of the angular velocity corresponding to the current moment does not meet the region switching condition, the brushing motion direction of the brushing device at the current moment is determined based on the attitude angle data corresponding to the previous moment adjacent to the current moment among the moments that meet the region switching condition.

[0113] In this step, in specific implementation, firstly, among the moments that meet the area switching conditions, the previous moment adjacent to the current moment is selected, and the angle value of the heading angle in the attitude angle data corresponding to that moment is determined; then, the angle value of the heading angle is subtracted from the initial heading angle value to determine the angle value of the heading deflection angle corresponding to the current moment; finally, based on the heading deflection angle threshold range to which the angle value of the heading deflection angle belongs, the brushing motion direction of the brushing device corresponding to the current moment is determined.

[0114] In a possible implementation of this application, step S104 may include:

[0115] S1041. The angle value of the heading angle in the attitude angle data corresponding to the previous time adjacent to the current time in the time that meets the area switching conditions is calculated by subtracting the angle value of the initial heading angle in the initial attitude angle data to determine the angle value of the heading deflection angle corresponding to the current time.

[0116] In this step, during implementation, for the time that meets the area switching conditions, the previous time adjacent to the current time is selected from multiple times that meet the conditions; then, the angle value of the heading angle corresponding to that time is determined to be the angle value of the heading angle corresponding to the current time; finally, the angle value of the heading angle corresponding to the current time is subtracted from the angle value of the initial heading angle to determine the angle value of the heading deflection angle corresponding to the current time.

[0117] Specifically, the expression for calculating the heading angle value at the current moment is as follows.

[0118]

[0119] in, This is the angle value of the heading angle corresponding to the current time (time k); The heading angle value corresponding to the current time (time k) is the heading angle value of the previous time adjacent to the current time among the times that meet the area switching conditions; This is the initial heading angle value.

[0120] S1042. Determine the heading angle threshold range to which the heading angle value belongs.

[0121] In this step, the angle value of the heading angle corresponding to the current moment is compared with the first heading angle threshold interval, the second heading angle threshold interval, and the third heading angle threshold interval to determine the heading angle threshold interval to which the angle value of the heading angle corresponding to the current moment belongs.

[0122] Here, based on the experience of testing toothbrush devices, a first heading angle threshold and a second heading angle threshold are set; wherein, the first heading angle threshold is less than the second heading angle threshold.

[0123] Furthermore, based on the first and second heading angle thresholds, a heading angle threshold range is determined. Specifically, the first heading angle threshold range is the range where the heading angle value is less than the first heading angle threshold; the second heading angle threshold range is the range where the heading angle value is greater than the second heading angle threshold; and the third heading angle threshold range is the range where the heading angle value is greater than or equal to the first heading angle threshold and less than or equal to the second heading angle threshold.

[0124] S1043. When the angle value of the heading angle belongs to the first heading angle threshold range, the brushing motion direction of the brushing device at the current moment is determined to be to the left.

[0125] In this step, when the angle value of the heading angle falls within the first heading angle threshold range, that is, when the angle value of the heading angle is less than the first heading angle threshold range, the brushing motion direction of the brushing device at the current moment is determined to be to the left.

[0126] S1044. When the angle value of the heading angle belongs to the second heading angle threshold range, the brushing motion direction of the brushing device at the current moment is determined to be to the right.

[0127] In this step, when the angle value of the heading angle falls within the second heading angle threshold range, that is, when the angle value of the heading angle is greater than the value range of the second heading angle threshold, the brushing motion direction of the brushing device at the current moment is determined to be to the right.

[0128] S1045. When the angle value of the heading angle belongs to the third heading angle threshold range, the brushing motion direction of the brushing device at the current moment is determined to be moving towards the center.

[0129] In this step, when the angle value of the heading angle falls within the third heading angle threshold range, that is, the angle value of the heading angle is greater than or equal to the first heading angle threshold and less than or equal to the second heading angle threshold, the brushing motion direction of the brushing device at the current moment is determined to be towards the center.

[0130] Specifically, the expression for the brushing motion direction of the brushing device at the current moment is shown below.

[0131]

[0132] Where TO represents the brushing motion direction of the brushing device at the current moment; LEFT indicates that the brushing motion direction is to the left; RIGHT indicates that the brushing motion direction is to the right; and MID indicates that the brushing motion direction is to the center. This is the first heading angle threshold; This is the second heading angle threshold; This is the angle value of the heading angle corresponding to the current time (time k).

[0133] S105. Based on the orientation of the brushing device at the current moment, determined by the spatial axis acceleration, and the direction of brushing motion, determine the brushing area corresponding to the brushing device at the current moment.

[0134] In this step, in practice, firstly, based on the spatial axis acceleration, the orientation of the brushing device at the current moment is determined using a pre-built neural network model; then, based on the orientation of the brushing device and the direction of brushing motion, the brushing area corresponding to the brushing device at the current moment is determined.

[0135] In one possible implementation of this application, the target oral cavity is divided into 16 brushing areas, so that the brushing device can identify the 16 brushing areas in the target oral cavity; for details, please refer to Figure 3 , Figure 3 This is a schematic diagram of a brushing area in a target oral cavity provided in an embodiment of this application. Figure 3 As shown, the brushing areas of the target oral cavity are as follows: maxillary anterior teeth (au); mandibular anterior teeth (ad); maxillary left molar (b); mandibular left molar (c); maxillary right molar (d); mandibular right molar (e); maxillary left occlusal surface (f); maxillary anterior hyoid bone (g); maxillary right occlusal surface (h); mandibular left occlusal surface (i); mandibular anterior hyoid bone (j); mandibular right occlusal surface (k); medial side of maxillary left molar (l); medial side of mandibular left molar (m); medial side of maxillary right molar (n); medial side of mandibular right molar (o).

[0136] Furthermore, in practical application, the 16 brushing areas of the target oral cavity are classified into 6 oral cavity areas: upper left area (b, f, l); upper right area (d, h, n); upper front area (au, g); lower left area (c, i, m); lower right area (e, k, o); and lower front area (ad, j).

[0137] In a possible implementation of this application, step S105 may include:

[0138] S1051. Input the spatial axis acceleration into the pre-built neural network model to determine the orientation of the brushing device at the current moment.

[0139] In this step, the horizontal, vertical, and longitudinal accelerations corresponding to the current moment are input into a pre-built neural network model, and the orientation of the brushing device at the current moment is determined by the output of the neural network model.

[0140] The orientation of the brushing device includes any one of the following: upward (U), downward (D), leftward (L), rightward (R), upward inward (IU), and downward inward (ID).

[0141] In one possible implementation of this application, the neural network model includes, but is not limited to, a multi-layer perceptron (MLP) model; the neural network model is constructed through the following steps.

[0142] Step A: Collect brushing data from multiple test subjects using a sensor module; wherein the brushing data includes triaxial acceleration data and triaxial angular velocity data, etc.; the sensor module may be an IMU.

[0143] Step B: According to the different orientations of the brushing devices, classify and process the brushing data, and determine the processed brushing data as the training set for the neural network model.

[0144] Step C: Construct the neural network architecture of the neural network model; the neural network architecture includes hidden layers and output layers.

[0145] Here, the hidden layer includes at least two neuron nodes; the neural network architecture can be adjusted according to the actual application and usage scenario.

[0146] Step D: Train the neural network model using the training set data in the training set to construct a neural network model for determining the orientation of the toothbrush device.

[0147] For details, please refer to Figure 2 , Figure 2 This is a schematic diagram of the architecture of a neural network model provided in an embodiment of this application. Figure 2 As shown, the neural network model includes a hidden layer and an output layer. The horizontal axis acceleration, vertical axis acceleration and vertical axis acceleration corresponding to the current moment are input into the hidden layer, and the output layer can output the orientation of the brushing device at the current moment.

[0148] S1052. When the toothbrush device is facing upwards or downwards, the brushing area is determined according to the matching relationship between the orientation of the toothbrush device and the direction of the brushing movement.

[0149] In this step, with the brushing device facing upwards, when the brushing motion is to the left, the brushing area is determined to be the left occlusal surface of the maxilla; when the brushing motion is to the right, the brushing area is determined to be the right occlusal surface of the maxilla. With the brushing device facing downwards, when the brushing motion is to the left, the brushing area is determined to be the left occlusal surface of the mandible; when the brushing motion is to the right, the brushing area is determined to be the right occlusal surface of the mandible.

[0150] Specifically, when the brushing device is oriented upwards or downwards, the expression for determining the brushing area is as follows.

[0151]

[0152] Wherein, sur represents the brushing area; U indicates that the brushing device is facing upwards; D indicates that the brushing device is facing downwards; LEFT indicates that the brushing motion is to the left; RIGHT indicates that the brushing motion is to the right; f represents the maxillary left occlusal surface; h represents the maxillary right occlusal surface; i represents the mandibular left occlusal surface; and k represents the mandibular right occlusal surface.

[0153] S1053. When the toothbrush device is facing left or right, the brushing area is determined according to the matching relationship between the toothbrush device orientation and the toothbrush movement direction, as well as the vertical axis acceleration corresponding to the current moment.

[0154] In this step, in specific implementation, firstly, the acceleration threshold interval corresponding to the brushing area to which the vertical axis acceleration belongs at the current moment is determined; then, if the brushing device is facing left or right, the matching relationship between the brushing device orientation and the brushing motion direction is determined; finally, based on the matching relationship, if the acceleration threshold interval corresponding to the brushing area to which the vertical axis acceleration belongs meets the requirements, the brushing area is determined.

[0155] In a possible implementation of this application, step S1053 may include:

[0156] S10531. When the toothbrush device is facing left or right, determine the acceleration threshold interval corresponding to the brushing area to which the vertical axis acceleration at the current moment belongs.

[0157] In this step, when the brushing device is facing left or right, the acceleration threshold range to which the vertical axis acceleration belongs is determined based on the acceleration threshold range corresponding to the brushing area.

[0158] Specifically, when the brushing device is facing left, the maxillary right molar region corresponds to the maxillary right molar threshold, and the first acceleration threshold interval is the interval where the vertical axis acceleration is greater than the maxillary right molar threshold; the mandibular right molar region corresponds to the mandibular right molar threshold, and the second acceleration threshold interval is the interval where the vertical axis acceleration is less than the mandibular right molar threshold; the maxillary left molar medial region corresponds to the maxillary left molar medial threshold, and the third acceleration threshold interval is the interval where the vertical axis acceleration is greater than the maxillary left molar medial threshold; the mandibular left molar medial region corresponds to the mandibular left molar medial threshold, and the fourth acceleration threshold interval is the interval where the vertical axis acceleration is less than the mandibular left molar medial threshold.

[0159] Furthermore, with the brushing device facing to the right, the maxillary anterior tooth region corresponds to the maxillary anterior tooth threshold, and the fifth acceleration threshold interval is the interval where the vertical axis acceleration is greater than the maxillary anterior tooth threshold; the mandibular anterior tooth region corresponds to the mandibular anterior tooth threshold, and the sixth acceleration threshold interval is the interval where the vertical axis acceleration is less than the mandibular anterior tooth threshold; the maxillary left molar region corresponds to the maxillary left molar threshold, and the seventh acceleration threshold interval is the interval where the vertical axis acceleration is greater than the maxillary left molar threshold; the mandibular left molar region corresponds to the mandibular left molar threshold, and the eighth acceleration threshold interval is the interval where the vertical axis acceleration is less than the mandibular left molar threshold; the maxillary right molar medial region corresponds to the maxillary right molar medial threshold, and the ninth acceleration threshold interval is the interval where the vertical axis acceleration is greater than the maxillary right molar medial threshold; the mandibular right molar medial region corresponds to the mandibular right molar medial threshold, and the tenth acceleration threshold interval is the interval where the vertical axis acceleration is less than the mandibular right molar medial threshold.

[0160] S10532. Determine the brushing area based on the matching relationship between the orientation of the brushing device and the direction of the brushing motion, and the acceleration threshold range to which the vertical axis acceleration belongs.

[0161] In this step, when the brushing device is facing left or right, the brushing area is determined based on the matching relationship between the brushing device orientation and the brushing motion direction, and whether the acceleration threshold range to which the vertical axis acceleration belongs meets the corresponding conditions.

[0162] Specifically, when the brushing device is facing left, the expression for determining the brushing area is as follows.

[0163]

[0164] Wherein, sur represents the brushing area; L indicates the brushing device is facing left; LEFT indicates the brushing motion is to the left; RIGHT indicates the brushing motion is to the right; th d ,th e ,th l ,th m These are the threshold values ​​for the maxillary right molar, mandibular right molar, maxillary left molar medial border, and mandibular left molar medial border, respectively; d, e, l, and m represent the maxillary right molar region, mandibular right molar region, maxillary left molar medial border, and mandibular left molar medial border, respectively.

[0165] Specifically, when the toothbrush is facing right, the expression for determining the brushing area is as follows.

[0166]

[0167] Wherein, sur represents the brushing area; R indicates the brushing device is facing right; LEFT indicates the brushing motion is to the left; RIGHT indicates the brushing motion is to the right; MID indicates the brushing motion is to the center; th au ,th ad ,th b ,th c ,th n ,th o These are the threshold values ​​for the maxillary anterior teeth, mandibular anterior teeth, maxillary left molar, mandibular left molar, maxillary right molar medial border, and mandibular right molar medial border, respectively; au, ad, b, c, n, and o represent the maxillary anterior teeth region, mandibular anterior teeth region, maxillary left molar region, mandibular left molar region, maxillary right molar medial border, and mandibular right molar medial border, respectively.

[0168] S1054. When the brushing device is oriented towards the inside of the upper front teeth or the inside of the lower front teeth, the brushing area is determined according to the preset orientation area correspondence.

[0169] In this step, when the brushing device is oriented towards the inside of the upper front teeth, the brushing area is determined to be the maxillary anterior hyoid bone region; when the brushing device is oriented towards the inside of the lower front teeth, the brushing area is determined to be the mandibular anterior hyoid bone region.

[0170] Furthermore, based on the 16 brushing areas of the target oral cavity and the 6 oral cavity areas classified in actual application, the oral cavity area to be brushed by the brushing device at the current moment is determined based on the specific brushing areas identified.

[0171] For details, please refer to Figure 4 , Figure 4 This is a schematic diagram illustrating the recognition effect of a brushing area provided in an embodiment of this application. Figure 4 As shown in the figure, the horizontal axis represents brushing time in seconds; the vertical axis represents the brushing area at the current moment; the three curves in the figure include: surface represents the identified brushing area; udlr represents the detection result of the orientation of the brushing device; and angle represents the integral angle of the data acquisition gyroscope.

[0172] Among them, such as Figure 4 As shown, the correspondence between each brushing area and the number is as follows: 0 represents the target oral cavity area; 1 represents the maxillary anterior teeth area; 2 represents the mandibular anterior teeth area; 3 represents the maxillary left molar area; 4 represents the mandibular left molar area; 5 represents the maxillary right molar area; 6 represents the mandibular right molar area; 7 represents the maxillary right occlusal surface area; 8 represents the maxillary anterior hyoid bone area; 9 represents the maxillary left occlusal surface area; 10 represents the mandibular right occlusal surface area; 11 represents the mandibular anterior hyoid bone area; 12 represents the mandibular left occlusal surface area; 13 represents the maxillary left molar medial area; 14 represents the mandibular left molar medial area; 15 represents the maxillary right molar medial area; 16 represents the mandibular right molar medial area.

[0173] For example, such as Figure 4 As shown, the test sequence for the brushing areas is 0-1-2-3-4-5-6-12-10-9-7-8-11-14-13-15-16-1-0; the actual recognition result is 0-1-2-3-4-5-6-12-10-7-7-8-11-14-13-15-16-1-0; in the test including 19 brushing areas, 18 brushing areas were correctly identified, with a detection accuracy rate of 94.74%.

[0174] The brushing area recognition method provided in this application uses the spatial axis acceleration and spatial axis angular velocity of the brushing device during the brushing process in the target oral cavity to identify the orientation of the brushing device using a pre-built neural network model, and determines whether a brushing area switching action has occurred. When the brushing area is switched, the posture angle is updated, and when the brushing area is maintained, the brushing motion direction is determined based on the posture angle. By combining the orientation of the brushing device, the brushing motion direction in the oral cavity, and the spatial axis acceleration, the brushing area of ​​the target oral cavity where the brushing device is located is identified. This reduces the amount of computation when the brushing device recognizes the brushing area, thereby improving the accuracy of the brushing device's area recognition.

[0175] Please see Figure 5 , Figure 5 This is a schematic diagram of the structure of a toothbrushing area recognition device provided in an embodiment of this application. Figure 5As shown, the identification device 500 includes:

[0176] The data acquisition module 510 is used to acquire the spatial axis acceleration and spatial axis angular velocity at the current moment during the brushing process of the brushing device in the target oral cavity;

[0177] The condition judgment module 520 is used to determine whether the standard deviation of the angular velocity corresponding to the angular velocity of the spatial axis satisfies the area switching condition.

[0178] The attitude update module 530 is used to update the attitude angle based on the spatial axis acceleration and the spatial axis angular velocity when the standard deviation of the angular velocity corresponding to the current moment meets the region switching condition;

[0179] The direction determination module 540 is used to determine the brushing motion direction of the brushing device at the current moment based on the attitude angle data corresponding to the previous moment adjacent to the current moment in the moments that meet the region switching conditions when the standard deviation of the angular velocity corresponding to the current moment does not meet the region switching conditions.

[0180] The region determination module 550 is used to determine the brushing region corresponding to the brushing device at the current moment based on the brushing device orientation and the brushing movement direction determined by the spatial axis acceleration.

[0181] Furthermore, when the condition judgment module 520 determines whether the standard deviation of the angular velocity corresponding to the spatial axis angular velocity satisfies the region switching condition, the condition judgment module 520 is used to:

[0182] Based on the horizontal axis angular velocity, vertical axis angular velocity, and vertical axis angular velocity of the brushing device at the current moment, the average value of the spatial axis angular velocity of the brushing device at the current moment is determined.

[0183] Based on the mean values ​​of the horizontal axis angular velocity, the vertical axis angular velocity, the vertical axis angular velocity, and the spatial axis angular velocity, the standard deviation of the angular velocity of the toothbrush device at the current moment is determined using a preset standard deviation calculation formula.

[0184] Based on the numerical relationship between the standard deviation of the angular velocity and the standard deviation threshold, determine whether the standard deviation of the angular velocity meets the area switching conditions.

[0185] Furthermore, when the condition judgment module 520 determines whether the standard deviation of the angular velocity satisfies the region switching condition based on the numerical relationship between the standard deviation of the angular velocity and the standard deviation threshold, the condition judgment module 520 is used to:

[0186] The standard deviation of the angular velocity and the standard deviation threshold are compared to determine the numerical relationship between the standard deviation of the angular velocity and the standard deviation threshold;

[0187] When the numerical relationship is such that the standard deviation of the angular velocity is greater than the standard deviation threshold, it is determined that the standard deviation of the angular velocity satisfies the region switching condition;

[0188] When the numerical relationship is such that the standard deviation of the angular velocity is less than or equal to the standard deviation threshold, it is determined that the standard deviation of the angular velocity does not meet the region switching condition.

[0189] Furthermore, when the attitude update module 530 updates the attitude angle based on the spatial axis acceleration and the spatial axis angular velocity when the standard deviation of the angular velocity at the current moment meets the region switching condition, the attitude update module 530 is used to:

[0190] Based on the horizontal, vertical, and longitudinal accelerations of the brushing device at the current moment, which are included in the spatial axis acceleration, the initial attitude angle data at the current moment is determined.

[0191] Based on the initial attitude angle data, obtain the initial quaternion corresponding to the current moment;

[0192] The initial quaternion is recursively transformed to obtain the quaternion corresponding to the current time. Based on the quaternion corresponding to the current time, the attitude angle data corresponding to the current time that meets the area switching conditions is obtained for attitude angle update.

[0193] Furthermore, when the attitude update module 530 performs recursive transformation on the initial quaternion to obtain the quaternion corresponding to the current time, and obtains the attitude angle data corresponding to the current time that satisfies the region switching condition based on the quaternion corresponding to the current time for attitude angle update, the attitude update module 530 is used for:

[0194] Based on the spatial axis angular velocity, establish the antisymmetric matrix of the angular velocity at the current moment;

[0195] Based on the angular velocity antisymmetric matrix, the initial quaternion at the current moment is recursively transformed using a preset attitude error expression to obtain the corresponding quaternion attitude number at the current moment.

[0196] Based on the quaternion corresponding to the current time, obtain the attitude angle data corresponding to the current time that satisfies the area switching conditions, and then update the attitude angle.

[0197] Furthermore, when the direction determination module 540 determines the brushing motion direction of the brushing device at the current moment based on the attitude angle data corresponding to the previous moment adjacent to the current moment among the moments that satisfy the region switching conditions, the direction determination module 540 is used to:

[0198] The angle value of the heading angle in the attitude angle data corresponding to the previous time adjacent to the current time is subtracted from the angle value of the initial heading angle in the initial attitude angle data to determine the angle value of the heading deflection angle corresponding to the current time.

[0199] Determine the heading angle threshold range to which the heading angle value belongs;

[0200] When the angle value of the heading angle is within the first heading angle threshold range, the brushing motion direction of the brushing device at the current moment is determined to be to the left.

[0201] When the angle value of the heading angle is within the second heading angle threshold range, the brushing motion direction of the brushing device at the current moment is determined to be to the right.

[0202] When the angle value of the heading angle belongs to the third heading angle threshold range, the brushing motion direction of the brushing device at the current moment is determined to be towards the center.

[0203] Furthermore, when the region determination module 550 determines the brushing area corresponding to the brushing device at the current moment based on the brushing device orientation determined by the spatial axis acceleration and the brushing movement direction, the region determination module 550 is used to:

[0204] The spatial axis acceleration is input into a pre-built neural network model to determine the orientation of the brushing device at the current moment; wherein, the orientation of the brushing device includes any one of: upward, downward, leftward, rightward, upward inward of the anterior teeth, and downward of the anterior teeth.

[0205] When the toothbrush device is facing upwards or downwards, the brushing area is determined according to the matching relationship between the orientation of the toothbrush device and the direction of the brushing movement;

[0206] When the toothbrush device is facing left or right, the brushing area is determined based on the matching relationship between the toothbrush device orientation and the brushing movement direction, as well as the vertical axis acceleration corresponding to the current moment.

[0207] When the brushing device is oriented towards the inside of the upper front teeth or the inside of the lower front teeth, the brushing area is determined according to a preset orientation area correspondence.

[0208] Furthermore, when the area determination module 550 determines the brushing area based on the matching relationship between the orientation of the brushing device and the brushing motion direction, and the vertical axis acceleration corresponding to the current moment, when the brushing device is facing left or right, the area determination module 550 is used to:

[0209] When the toothbrush device is facing left or right, determine the acceleration threshold range corresponding to the brushing area to which the vertical axis acceleration at the current moment belongs;

[0210] The brushing area is determined based on the matching relationship between the orientation of the brushing device and the direction of the brushing motion, and the acceleration threshold range to which the vertical axis acceleration belongs.

[0211] The brushing area recognition device provided in this application embodiment obtains the spatial axis acceleration and spatial axis angular velocity of the brushing device during the brushing process in the target oral cavity, uses a pre-built neural network model to identify the orientation of the brushing device, and determines whether a brushing area switching action has occurred. When the brushing area is switched, the posture angle is updated, and when the brushing area is maintained, the brushing motion direction is determined based on the posture angle. By combining the orientation of the brushing device, the brushing motion direction in the oral cavity, and the spatial axis acceleration, the brushing area of ​​the target oral cavity where the brushing device is located is identified. This reduces the amount of computation when the brushing device recognizes the brushing area, thereby improving the accuracy of the brushing device's area recognition.

[0212] Please see Figure 6 , Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 6 As shown, the electronic device 600 includes a processor 610, a memory 620, and a bus 630.

[0213] The memory 620 stores machine-readable instructions executable by the processor 610. When the electronic device 600 is running, the processor 610 and the memory 620 communicate via the bus 630. When the machine-readable instructions are executed by the processor 610, they can perform the operations described above. Figure 1 The steps of the brushing area recognition method in the illustrated method embodiment are described in detail in the method embodiment, and will not be repeated here.

[0214] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0215] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the shown or discussed mutual couplings, direct couplings, or communication connections may be through some communication interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.

[0216] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0217] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0218] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a processor-executable, non-volatile, computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0219] Finally, it should be noted that the above-described embodiments are merely specific implementations of this application, used to illustrate the technical solutions of this application, and not to limit them. The scope of protection of this application is not limited thereto. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments, or make equivalent substitutions for some of the technical features, within the scope of the technology disclosed in this application. Such modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method of identifying a tooth brushing area, characterized by, The identification method includes: Acquire the spatial axis acceleration and spatial axis angular velocity at the current moment during the brushing process of the brushing device in the target oral cavity; Based on the standard deviation of the angular velocity corresponding to the spatial axis angular velocity, determine whether the standard deviation of the angular velocity satisfies the region switching condition; When the standard deviation of the angular velocity at the current moment meets the region switching condition, the attitude angle is updated based on the spatial axis acceleration and the spatial axis angular velocity. When the standard deviation of the angular velocity at the current moment meets the region switching condition, the attitude angle is updated based on the spatial axis acceleration and the spatial axis angular velocity, including: Based on the horizontal, vertical, and longitudinal accelerations of the brushing device at the current moment, which are included in the spatial axis acceleration, the initial attitude angle data at the current moment is determined. Based on the initial attitude angle data, obtain the initial quaternion corresponding to the current moment; The initial quaternion is recursively transformed to obtain the quaternion corresponding to the current time. Based on the quaternion corresponding to the current time, the attitude angle data corresponding to the current time that meets the area switching conditions is obtained for attitude angle update. The recursive transformation of the initial quaternion to obtain the quaternion corresponding to the current time, and the acquisition of the attitude angle data corresponding to the current time that satisfies the region switching condition based on the quaternion corresponding to the current time for attitude angle update, includes: Based on the spatial axis angular velocity, establish the antisymmetric matrix of the angular velocity at the current moment; Based on the angular velocity antisymmetric matrix, the initial quaternion at the current moment is recursively transformed using a preset attitude error expression to obtain the corresponding quaternion attitude number at the current moment. Based on the quaternion corresponding to the current time, obtain the attitude angle data corresponding to the current time that satisfies the area switching conditions, and then update the attitude angle. When the standard deviation of the angular velocity at the current moment does not meet the region switching condition, the brushing motion direction of the brushing device at the current moment is determined based on the attitude angle data corresponding to the previous moment adjacent to the current moment among the moments that meet the region switching condition. Based on the orientation of the brushing device at the current moment, determined by the spatial axis acceleration, and the direction of brushing motion, the brushing area corresponding to the brushing device at the current moment is determined.

2. The method of claim 1, wherein, The step of determining whether the standard deviation of the angular velocity corresponding to the spatial axis angular velocity satisfies the region switching condition includes: Based on the horizontal axis angular velocity, vertical axis angular velocity, and vertical axis angular velocity of the brushing device at the current moment, the average value of the spatial axis angular velocity of the brushing device at the current moment is determined. Based on the mean values ​​of the horizontal axis angular velocity, the vertical axis angular velocity, the vertical axis angular velocity, and the spatial axis angular velocity, the standard deviation of the angular velocity of the toothbrush device at the current moment is determined using a preset standard deviation calculation formula. Based on the numerical relationship between the standard deviation of the angular velocity and the standard deviation threshold, determine whether the standard deviation of the angular velocity meets the area switching conditions.

3. The method of claim 2, wherein, The step of determining whether the standard deviation of the angular velocity meets the region switching conditions based on the numerical relationship between the standard deviation of the angular velocity and the standard deviation threshold includes: The standard deviation of the angular velocity and the standard deviation threshold are compared to determine the numerical relationship between the standard deviation of the angular velocity and the standard deviation threshold; When the numerical relationship is such that the standard deviation of the angular velocity is greater than the standard deviation threshold, it is determined that the standard deviation of the angular velocity satisfies the region switching condition; When the numerical relationship is such that the standard deviation of the angular velocity is less than or equal to the standard deviation threshold, it is determined that the standard deviation of the angular velocity does not meet the region switching condition.

4. The method of claim 1, wherein, When the standard deviation of the angular velocity at the current moment does not meet the region switching condition, the brushing motion direction of the brushing device at the current moment is determined based on the attitude angle data corresponding to the previous moment adjacent to the current moment among the moments that meet the region switching condition, including: The angle value of the heading angle in the attitude angle data corresponding to the previous time adjacent to the current time is subtracted from the angle value of the initial heading angle in the initial attitude angle data to determine the angle value of the heading deflection angle corresponding to the current time. Determine the heading angle threshold range to which the heading angle value belongs; When the angle value of the heading angle is within the first heading angle threshold range, the brushing motion direction of the brushing device at the current moment is determined to be to the left. When the angle value of the heading angle is within the second heading angle threshold range, the brushing motion direction of the brushing device at the current moment is determined to be to the right. When the angle value of the heading angle belongs to the third heading angle threshold range, the brushing motion direction of the brushing device at the current moment is determined to be towards the center.

5. The method according to claim 4, characterized in that, The step of determining the brushing area corresponding to the brushing device at the current moment based on the brushing device orientation and brushing movement direction determined by the spatial axis acceleration includes: The spatial axis acceleration is input into a pre-built neural network model to determine the orientation of the brushing device at the current moment; wherein, the orientation of the brushing device includes any one of: upward, downward, leftward, rightward, upward inward of the anterior teeth, and downward of the anterior teeth. When the toothbrush device is facing upwards or downwards, the brushing area is determined according to the matching relationship between the orientation of the toothbrush device and the direction of the brushing movement; When the toothbrush device is facing left or right, the brushing area is determined based on the matching relationship between the toothbrush device orientation and the brushing movement direction, as well as the vertical axis acceleration corresponding to the current moment. When the brushing device is oriented towards the inside of the upper front teeth or the inside of the lower front teeth, the brushing area is determined according to the preset orientation area correspondence.

6. The method according to claim 5, characterized in that, When the brushing device is oriented to the left or right, the brushing area is determined based on the matching relationship between the orientation of the brushing device and the direction of brushing movement, as well as the vertical acceleration corresponding to the current moment, including: When the toothbrush device is facing left or right, determine the acceleration threshold range corresponding to the brushing area to which the vertical axis acceleration at the current moment belongs; The brushing area is determined based on the matching relationship between the orientation of the brushing device and the direction of the brushing motion, and the acceleration threshold range to which the vertical axis acceleration belongs.

7. A toothbrushing area recognition device, characterized in that, The identification device includes: The data acquisition module is used to acquire the spatial axis acceleration and spatial axis angular velocity at the current moment during the brushing process of the brushing device in the target oral cavity; The condition judgment module is used to determine whether the standard deviation of the angular velocity corresponding to the angular velocity of the spatial axis satisfies the region switching condition. The attitude update module is used to update the attitude angle based on the spatial axis acceleration and the spatial axis angular velocity when the standard deviation of the angular velocity at the current moment meets the region switching condition. The direction determination module is used to determine the brushing motion direction of the brushing device at the current moment based on the attitude angle data of the previous moment adjacent to the current moment when the standard deviation of the angular velocity at the current moment does not meet the region switching conditions. The region determination module is used to determine the brushing region corresponding to the brushing device at the current moment based on the brushing device orientation and the brushing movement direction determined by the spatial axis acceleration. When the attitude update module updates the attitude angle based on the spatial axis acceleration and the spatial axis angular velocity when the standard deviation of the angular velocity at the current moment meets the region switching condition, the attitude update module is used to: Based on the horizontal, vertical, and longitudinal accelerations of the brushing device at the current moment, which are included in the spatial axis acceleration, the initial attitude angle data at the current moment is determined. Based on the initial attitude angle data, obtain the initial quaternion corresponding to the current moment; The initial quaternion is recursively transformed to obtain the quaternion corresponding to the current time. Based on the quaternion corresponding to the current time, the attitude angle data corresponding to the current time that meets the area switching conditions is obtained for attitude angle update. When the attitude update module recursively transforms the initial quaternion to obtain the quaternion corresponding to the current time, and obtains the attitude angle data corresponding to the current time that satisfies the region switching condition based on the quaternion corresponding to the current time for attitude angle update, the attitude update module is used for: Based on the spatial axis angular velocity, establish the antisymmetric matrix of the angular velocity at the current moment; Based on the angular velocity antisymmetric matrix, the initial quaternion at the current moment is recursively transformed using a preset attitude error expression to obtain the corresponding quaternion attitude number at the current moment. Based on the quaternion corresponding to the current time, obtain the attitude angle data corresponding to the current time that satisfies the area switching conditions, and then update the attitude angle.

8. An electronic device, characterized in that, include: The device includes a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor communicates with the memory via the bus. The machine-readable instructions are executed by the processor to perform the steps of the brushing area recognition method as described in any one of claims 1 to 6.

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