Tooth brushing monitoring method, intelligent toothbrush and product

Abstract

The invention provides a tooth brushing monitoring method, an intelligent toothbrush and a product, and relates to the technical field of intelligent toothbrushes, and the method comprises the following steps: monitoring the posture and track of the toothbrush in a tooth brushing process in real time through a preset gyroscope module; in combination with the action sequence of the toothbrush postures and the tracks, the tooth brushing duration of each preset tooth area is obtained; according to the tooth brushing duration, calculating the coverage degree of each tooth area during tooth brushing; and converting the coverage degree into an RBG gray value, and displaying the coverage degree of each tooth area during tooth brushing on a predetermined display interface through the gray value. The problem that in the prior art, the tooth brushing cleaning effect is poor due to the fact that it is difficult to quantify the tooth brushing coverage degree of each tooth area through the tooth brushing duration of different tooth areas is solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent toothbrushes, in particular to a tooth brushing monitoring method, an intelligent toothbrush and a product. BACKGROUND

[0002] Oral health is an important part of human health, and scientific and effective tooth brushing is a key means to maintain oral health. At present, although intelligent toothbrush products with basic monitoring functions have appeared on the market, the core monitoring capabilities of these products are mostly focused on macro indicators such as brushing time and brushing force, and it is difficult to quantitatively evaluate the fine effect of the brushing process.

[0003] In the prior art, the action of the toothbrush on different tooth regions in the brushing process, such as the left upper posterior tooth region and the right lower anterior tooth region, cannot be accurately identified, and the actual brushing time of each tooth region cannot be further counted. This technical limitation makes it impossible for the user and the product to determine whether there are problems such as missed brushing and insufficient brushing time in a certain area during the brushing process. For example, the user may focus on cleaning the anterior tooth region and ignore the posterior tooth region, or the brushing time in a certain area is much shorter than the standard time required for effective cleaning, but the existing monitoring scheme cannot determine the coverage degree through the brushing time of each region and feed back to the user. SUMMARY

[0004] Embodiments of the present application provide a tooth brushing monitoring method, an intelligent toothbrush and a product, which aim to solve the problem that the prior art cannot quantitatively evaluate the coverage degree of each tooth region during brushing through the brushing time of different tooth regions, resulting in poor cleaning effect of tooth brushing.

[0005] To achieve the above-mentioned purpose, in a first aspect, the present application provides a tooth brushing monitoring method for monitoring the brushing process using an intelligent toothbrush, wherein the intelligent toothbrush comprises a pre-installed gyroscope module, and the tooth brushing monitoring method comprises the following steps: The toothbrush posture and trajectory during the brushing process are monitored in real time by the gyroscope module to obtain a motion sequence of the toothbrush posture and trajectory; the toothbrush posture is characterized by the angle of the toothbrush handle axis relative to a predetermined reference coordinate system; Based on the motion sequence of the toothbrush posture and trajectory, the brushing time of each predetermined tooth region is obtained, comprising the following steps: The effective brushing cumulative time of the toothbrush posture reaching a predetermined toothbrush posture condition during the brushing process is obtained; The effective brushing cumulative time is distributed to each tooth region according to the trajectory to obtain the brushing time of each tooth region; According to the brushing time, the coverage degree of each tooth region during brushing is calculated; The coverage degree is converted into an RBG gray value, and the coverage degree of each tooth region during brushing is displayed on a predetermined display interface through the gray value.

[0006] Further, the predetermined tooth regions include an upper left region, an upper right region, a lower left region, and a lower right region.

[0007] Further, the coverage degree is calculated by the following formula: , In the formula, The coverage degree is represented by T, which represents the brushing duration.

[0008] Further, the RBG gray value is calculated by the following formula: , In the formula, The gray value is represented by G.

[0009] Further, when the gyroscope module detects that the posture of the toothbrush exceeds a predetermined motion threshold from a stationary state, the toothbrush is automatically powered on to wake up.

[0010] Further, different colors are displayed on the predetermined display interface according to the brushing force on each tooth region during brushing, including: The duration of the brushing force exceeding the predetermined force threshold is recorded as the overpressure duration; When the overpressure duration is not higher than a predetermined first duration threshold, a first color is displayed; When the overpressure duration is higher than the predetermined first duration threshold and lower than a predetermined second duration threshold, a second color is displayed; When the overpressure duration is not lower than the predetermined second duration threshold, a third color is displayed.

[0011] Further, power consumption management is also based on the running state of the toothbrush, including: When the toothbrush is in a working state, the gyroscope module is run for monitoring, and data is transmitted through Bluetooth; When the toothbrush is in a sleep state, the radio frequency is cut off and the RTC clock is turned off; When the toothbrush is in a transportation mode, only the wake-up pin is retained.

[0012] Further, based on the average brushing duration of the historical period, the next brushing duration is predicted by the following formula: , , ,

[0013]

[0014] , In the formula, represents the average brushing time of the previous n times of tooth brushing, is the kth brushing time in the previous n times of tooth brushing; is the predicted n+1th brushing time, i.e. the next brushing time; A represents a sequence set of the selected sample number n, T A is a sequence set of the brushing time corresponding to A; Cov is a covariance function; Var is a variance function; mean is a mean value function; represents the slope; represents the intercept; When the next brushing time is higher than the predetermined brushing time threshold, the brushing time threshold is increased by S seconds.

[0015] In a second aspect, the present application provides an intelligent toothbrush, comprising a memory and a processor, wherein the memory stores at least one program, and the at least one program is executed by the processor to realize the tooth brushing monitoring method as described above.

[0016] In a third aspect, the present application provides a computer program product, comprising a computer program, wherein the computer program is executed by a processor to realize the steps of the tooth brushing monitoring method as described above.

[0017] The above technical solution has the following technical effects: The predetermined gyroscope module is used to monitor the toothbrush posture and trajectory in real time during tooth brushing; the brushing time of each predetermined tooth region is obtained by combining the action sequence of the toothbrush posture and trajectory; the coverage degree of each tooth region during tooth brushing is calculated according to the brushing time; the coverage degree is converted into an RBG gray value, and the coverage degree of each tooth region during tooth brushing is displayed on a predetermined display interface through the gray value. The present application solves the problem that the prior art cannot quantify the coverage degree by the brushing time of different tooth regions, resulting in poor tooth brushing cleaning effect.

[0018] In a further embodiment, different colors are displayed on the predetermined display interface according to the brushing strength on each brushing area during the brushing process, including: recording the duration of the brushing strength exceeding the predetermined strength threshold, as the over-pressing duration; when the over-pressing duration is not higher than the predetermined first duration threshold, the first color is displayed; when the over-pressing duration is higher than the predetermined first duration threshold and lower than the predetermined second duration threshold, the second color is displayed; when the over-pressing duration is not lower than the predetermined second duration threshold, the third color is displayed. The present application warns the over-pressing during brushing by quantifying the over-pressing duration, so as to effectively protect the teeth during the brushing process. BRIEF DESCRIPTION OF DRAWINGS

[0019] Figure 1 A flowchart of a brushing monitoring method according to an embodiment of the present application; Figure 2 A structure diagram of an intelligent toothbrush according to an embodiment of the present application. DETAILED DESCRIPTION

[0020] To further illustrate the embodiments, the present application provides accompanying drawings. These drawings are part of the disclosure of the present application, mainly used to illustrate the embodiments, and can be used to explain the operating principle of the embodiments in conjunction with the related description of the specification. Those of ordinary skill in the art should be able to understand other possible implementations and advantages of the present application by referring to these contents. The components in the drawings are not drawn to scale, and similar component symbols are generally used to represent similar components.

[0021] The present application will be further described in conjunction with the accompanying drawings and specific embodiments.

[0022] Embodiment one: Figure 1 A flowchart of a brushing monitoring method according to an embodiment of the present application, as shown in Figure 1 The method of this embodiment is used to monitor the brushing process using an intelligent toothbrush, which includes a pre-installed gyroscope module, including the following steps: The brushing posture and trajectory of the toothbrush during the brushing process are monitored in real time by the predetermined gyroscope module; In a specific implementation, when the gyroscope module monitors that the posture of the toothbrush exceeds the predetermined motion threshold from the static state, the toothbrush is automatically powered on to wake up.

[0023] In a specific implementation, the predetermined motion threshold is the posture change rate of the toothbrush = ± 30° / s.

[0024] In combination with the motion sequence of the toothbrush posture and trajectory, the brushing duration of each predetermined tooth area is obtained; In one implementation, the oral tooth partition strategy divides the tooth surface into 4 main regions based on standard dental partition methods to ensure uniformity and comprehensiveness of brushing coverage. The strategy references global toothbrush monitoring studies and considers the mouth as a 3D model divided into: Region 1: Upper Left Quadrant: includes the inner and outer surfaces, occlusal surfaces, and gum line of the left side of the upper teeth, approximately 8-10 teeth.

[0025] Region 2: Upper Right Quadrant: includes the inner and outer surfaces, occlusal surfaces, and gum line of the right side of the upper teeth, symmetric to Region 1.

[0026] Region 3: Lower Left Quadrant: includes the inner and outer surfaces, occlusal surfaces, and gum line of the left side of the lower teeth.

[0027] Region 4: Lower Right Quadrant: includes the inner and outer surfaces, occlusal surfaces, and gum line of the right side of the lower teeth.

[0028] In one implementation, the recommended total brushing time for each region is 30 seconds, with a total brushing time of 2 minutes to match the guidelines of the ADA (American Dental Association) and the Chinese Stomatological Association, ensuring a plaque removal rate of >90%. If the trajectory overlaps, such as in the overlapping region, the system uses weighted allocation, with the weight based on gyroscope angle data, for example, an angle <45° is allocated to the left side. This strategy addresses the blind spot problem of traditional toothbrushes, improving cleaning efficiency by more than 20%.

[0029] In one implementation, the process of weighted allocation is a step of iterative calculation, which processes the data of each small time period in real time during brushing. Assuming that the total brushing process is divided into many small time slices, such as one slice every 0.01 seconds, the system will check each time slice one by one and determine how to allocate it to adjacent tooth regions such as the left and right sides based on the current angle of the toothbrush. This is like allocating resources: if the toothbrush is exactly on the boundary, half to the left and half to the right; if it is biased to the left, most to the left and a small part to the right. Finally, the brushing time of each region is the accumulation of all related time slices. The specific steps are as follows: Data preparation and initialization: At the beginning of brushing, initialize the brushing duration of each tooth region to zero. The system obtains the attitude angle of the toothbrush from the gyroscope (here, the yaw angle is taken as an example, which represents the left-right deflection angle of the toothbrush relative to the front). At the same time, define a time slice length Δt. Also set the boundary value and parameter: the boundary angle θ_boundary (0°, representing the middle); the steepness parameter α (a constant that controls the sensitivity of the allocation, for example, α = 0.1 per degree, used to determine the speed of the allocation change).

[0030] Calculate the weight for each time slice: for each time slice during brushing, the system first calculates the current attitude angle θ of the toothbrush; use a smooth mathematical function such as the sigmoid function to calculate the weight of each region. When the angle θ is far to the left, the left weight is close to 1, and all the allocation is to the left, and the right is close to 0; when the angle is exactly at the boundary, the weights of both sides are 0.5; when the angle is biased to the right, the left weight is close to 0, and the right weight is close to 1.

[0031] Allocate the duration to each region: for the current time slice, the system multiplies this time slice Δt by the corresponding weight, and then adds it to the duration of the corresponding region.

[0032] This accumulation process is repeated throughout the brushing process until the brushing is completed.

[0033] In one specific implementation, the toothbrush attitude is represented by the angle of the toothbrush handle axis relative to a predetermined reference coordinate system; in one specific implementation, the toothbrush attitude is represented by Euler angles or quaternions, and data is collected using a gyroscope module (typically a 6-axis or 9-axis IMU, including a gyroscope and an accelerometer). The attitude is specifically represented by the angle change of the toothbrush handle axis relative to the reference coordinate system. Among them, the trajectory is obtained by integrating the displacement vector of the gyroscope.

[0034] In one specific implementation, the reference coordinate system takes the user's head as the origin, establishing a three-dimensional coordinate system (X-Y-Z axis). The X-axis is along the left-right direction of the user (horizontal), the Y-axis is along the front-back direction (depth), and the Z-axis is along the up-down direction (vertical).

[0035] In one specific implementation, the angle definition includes: pitch angle (Pitch): the angle between the toothbrush handle axis and the horizontal plane (X-Y plane), used to distinguish the upper jaw (positive pitch) and the lower jaw (negative pitch), ranging from -90° to 90°.

[0036] Roll angle (Roll): the rotation of the toothbrush handle axis around its own axis, used to distinguish the inside (lingual side) and outside (labial side) of the teeth, ranging from 0° to 360°.

[0037] Yaw: the angle between the toothbrush handle axis and the forward direction (Y-axis), used to distinguish the left and right areas, ranging from -180° to 180°, with 0° as the forward direction.

[0038] These angles are the relative angles between the toothbrush handle axis and the axes of the reference coordinate system, calculated by integrating the angular velocity data of the gyroscope. Quaternions are used to avoid the gimbal lock problem of Euler angles, ensuring the continuity and accuracy of the attitude representation.

[0039] In combination with the motion sequence of the toothbrush posture and trajectory, the brushing time of each predetermined tooth area is obtained, including the following steps: Obtain the effective brushing cumulative time when the toothbrush posture meets the predetermined toothbrush posture condition during brushing; In one specific implementation, the predetermined toothbrush posture condition is: Pitch | < 60° to ensure that the toothbrush points to the teeth rather than the sky or the ground; Roll ∈ [45°, 135°] or [225°, 315°], corresponding to inside / outside brushing; Yaw | > 30° to distinguish left / right.

[0040] According to the trajectory, the effective brushing cumulative time is allocated to each tooth area to obtain the brushing time of each tooth area; In one specific implementation, the allocation rule for allocating the effective brushing cumulative time to each tooth area is: Maxillary left: Pitch > 0° and Yaw < -30°; Maxillary right: Pitch > 0° and Yaw > +30°; Mandibular left: Pitch < 0° and Yaw < -30°; Mandibular right: Pitch < 0° and Yaw > +30°.

[0041] For each time slice Δt = 1 / f, f is the sampling rate of the gyroscope, check the validity of the posture. If valid, add to the brushing time Ti of the corresponding area, i = 1~4, corresponding to the four tooth areas.

[0042] Integrate the posture weight W(θ), W(θ) = 1 if the posture is valid, otherwise 0. In one specific implementation, the trajectory speed v can also be introduced, if v < v min such as 5 cm / s, considered as invalid stay, to prevent static timing.

[0043] Total time Ti = Σ [W(θt) ×Δt] for all t in area i.

[0044] Assume action sequence length N, pose sequence {θ1, θ2,..., θN}. For each θk, calculate region label Lk= map(θk). It is known that Ti = (1 / f) x count({k | Lk = i and W(θk)=1}). This method ensures that the duration reflects valid brushing actions.

[0045] According to the brushing duration, the coverage degree of each tooth region during brushing is calculated; the coverage degree is the coverage degree of the toothbrush to each tooth region during brushing; In one specific implementation, the coverage degree is calculated by the following formula: , In the formula, the coverage degree is represented; T represents the brushing duration.

[0046] In this embodiment, the brushing duration T of each region is mapped to a coverage degree of 0%-100%, and the coverage degree mapping algorithm uses a piecewise linear function f (T), which calculates the cleaning coverage percentage of each region based on the brushing duration T (unit: seconds). This algorithm extends the threshold values provided in the document, introduces intermediate interpolation to achieve smooth transition, and ensures that the coverage rate is related to the actual plaque removal, such as T>20s corresponding to >95% removal rate. The algorithm considers user habit learning and adjusts the threshold value through historical data, where the initial threshold value is based on clinical research, such as plaque reduction model of single brushing experiment.

[0047] The coverage degree is converted into an RBG gray value, and the coverage degree of each tooth region during brushing is displayed on a predetermined display interface through the gray value.

[0048] In one specific implementation, the predetermined display interface is displayed through a 12-face dental model and a 4-region state.

[0049] In one specific implementation, the RBG gray value is calculated by the following formula: , In the formula, is the gray value.

[0050] In one specific implementation, the gray value rendering color changes from black (0) to white (255).

[0051] When T<5s, it means that the coverage rate is insufficient, which is considered as 0%, and is displayed as black, encouraging to extend; When T=5-10s, the basic coverage rate is 25%, which is displayed as light gray.

[0052] When T=10-15s: linearly increases to 50%, which is displayed as medium gray.

[0053] When T = 15-20s: Linearly increase to 75%, shown as light gray.

[0054] When T≥20s: Full coverage 100%, shown as white.

[0055] In one specific implementation, different colors are displayed on the predetermined display interface according to the brushing intensity on each brushing area during the brushing process, including: Record the duration when the brushing intensity exceeds the predetermined intensity threshold, denoted as overpressure duration; When the overpressure duration is not higher than the predetermined first duration threshold, such as T=0s, it is displayed as the first color, such as white; When the overpressure duration is higher than the predetermined first duration threshold and lower than the predetermined second duration threshold, such as T=3s, it is displayed as the second color, such as light red; When the overpressure duration is not lower than the predetermined second duration threshold, it is displayed as the third color, such as deep red, and a flashing warning is added.

[0056] In one specific implementation, power consumption management is also performed according to the running state of the toothbrush, including: When the toothbrush is in the working state, the gyroscope module is run for monitoring, and data is transmitted through Bluetooth; When the toothbrush is in the sleep state, the radio frequency is cut off and the RTC clock is turned off; When the toothbrush is in the transportation mode, only the wake-up pin is retained.

[0057] In this embodiment, the power consumption management is based on the running state of the toothbrush, optimizing the battery life, with a target standby time of >1 year.

[0058] In one specific implementation, the working state represents active brushing of the toothbrush, and the running modules are gyroscope (monitoring posture), pressure sensor (intensity), and Bluetooth module (data transmission to APP), with a power consumption of ≈50mA; The sleep state is entered after the inaction duration is greater than 5min, the radio frequency (Bluetooth is turned off), and the RTC (real-time clock, saving clock power consumption) is turned off. The running module is only a low-power MCU standby, with a power consumption of <1μA; The transportation mode is set when the toothbrush is out of the factory / transported, used to prevent accidental wake-up. Only the wake-up pin (GPIO interrupt) is retained, and all sensors / RF are turned off. The transportation mode is entered by long-pressing the power >10s; the transportation mode is exited by triggering the first action posture threshold. The power consumption is <0.1μA, ensuring the safety of logistics.

[0059] In one specific implementation, the next brushing duration is also predicted based on the average brushing duration of the historical period, calculated by the following formula: , , ,

[0060]

[0061] , In the formula, This represents the average brushing time during the first n brushing sessions. This represents the duration of the k-th brushing session out of the previous n brushing sessions. Let T be the predicted brushing time for the (n+1)th brushing session, i.e., the next brushing session duration; A represents the set of sequences with a selected sample size n, and T is the set of sequences with a selected sample size n. A Let A be the set of brushing duration sequences corresponding to A; Cov is the covariance function; Var is the variance function; mean is the mean function; Indicates the slope; Indicates the intercept; If the duration of the next brushing session exceeds a predetermined brushing duration threshold, the brushing duration threshold will be increased by S seconds. For example, when n=3, T A When A = {20, 22, 24} and A = {1, 2, 3}, =(Cov≈1.33) / Var(2 / 3)≈2, =18, =26s. In one specific implementation, the brushing time threshold is 25s, at which point... If the brushing time threshold is greater than 25 seconds, the brushing time threshold will be increased by 5 seconds to encourage users to extend their brushing time to 30 seconds.

[0062] Example 2: Figure 2 This is a schematic diagram of the structure of a smart toothbrush according to an embodiment of the present invention, as shown below. Figure 2 As shown, the device includes a processor 201, a memory 202, a bus 203, and a computer program stored in the memory 202 and executable on the processor 201. The processor 201 includes one or more processing cores. The memory 202 is connected to the processor 201 via the bus 203. The memory 202 is used to store program instructions. When the processor executes the computer program, it implements the steps in the above-described method embodiment of Embodiment 1 of the present invention.

[0063] Further, as an executable solution, the intelligent toothbrush can be a computer unit, which can be a desktop computer, a notebook computer, a palm computer, a cloud server, and the like. The computer unit can include, but is not limited to, a processor and a memory. Those skilled in the art can understand that the above-mentioned constituent structure of the computer unit is only an example of the computer unit, and does not constitute a limitation on the computer unit, and can include more or fewer components than the above, or combine certain components, or different components. For example, the computer unit can also include an input / output device, a network access device, a bus, and the like, and the embodiments of the present application do not limit this.

[0064] Further, as an executable solution, the processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, and the like. The general-purpose processor can be a microprocessor or any conventional processor, and the like. The processor is the control center of the computer unit, and connects various parts of the computer unit through various interfaces and lines.

[0065] The memory can be used to store the computer program and / or modules, and the processor realizes various functions of the computer unit by running or executing the computer program and / or modules stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system and at least one application required by a function; the data storage area can store data created according to the use of the mobile phone, and the like. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, at least one disk storage device, a flash memory device, or other volatile solid-state memory devices.

[0066] Embodiment three: The present application also provides a computer program product comprising a computer program which, when executed by a processor, implements the steps of the tooth brushing monitoring method as described above.

[0067] While the application has been particularly shown and described with reference to preferred embodiments, it will be understood to those skilled in the art that various changes in form and details can be made therein without departing from the spirit and scope of the application as defined by the appended claims.

Claims

1. A tooth brushing monitoring method for monitoring a tooth brushing process using a smart toothbrush, characterized by, The smart toothbrush comprises a preset gyroscope module, and the tooth brushing monitoring method comprises the following steps: Real-time monitoring of the toothbrush posture and trajectory during tooth brushing by the gyroscope module to obtain a motion sequence of the toothbrush posture and trajectory; the toothbrush posture is characterized by the angle of the toothbrush handle axis relative to a predetermined reference coordinate system; In combination with the motion sequence of the toothbrush posture and trajectory, the tooth brushing time length of each predetermined tooth region is obtained, comprising the following steps: Obtaining the effective tooth brushing cumulative time length of the toothbrush posture reaching a predetermined toothbrush posture condition during tooth brushing; According to the trajectory, the effective tooth brushing cumulative time length is distributed to each tooth region to obtain the tooth brushing time length of each tooth region; According to the tooth brushing time length, the coverage degree of each tooth region during tooth brushing is calculated; The coverage degree is converted into an RBG gray value, and the coverage degree of each tooth region during tooth brushing is displayed on a predetermined display interface through the gray value.

2. The tooth brushing monitoring method of claim 1, wherein, The predetermined tooth region comprises the upper left region, the upper right region, the lower left region and the lower right region.

3. The tooth brushing monitoring method of claim 1, wherein, The coverage degree is calculated by the following formula: ， In the formula, represents the degree of coverage; T represents the brushing duration.

4. The tooth brushing monitoring method of claim 3, wherein, The RBG gray value is calculated by the following formula: ， In the formula, is a gray value.

5. The tooth brushing monitoring method of claim 1, wherein, When the gyroscope module monitors that the posture of the toothbrush exceeds a predetermined motion threshold from a static state, the toothbrush is automatically powered on to wake up.

6. The tooth brushing monitoring method of claim 1, wherein, According to the brushing force on each tooth brushing region during tooth brushing, different colors are displayed on the predetermined display interface, including: Recording the time length when the brushing force exceeds the predetermined force threshold, which is recorded as the overpressure time length; When the overpressure time length is not higher than a predetermined first time threshold, a first color is displayed; When the overpressure time length is higher than the predetermined first time threshold and lower than a predetermined second time threshold, a second color is displayed; When the overpressure time length is not lower than the predetermined second time threshold, a third color is displayed.

7. The tooth brushing monitoring method of claim 1, wherein, According to the running state of the toothbrush, power consumption management is also performed, including: When the toothbrush is in a working state, the gyroscope module is run for monitoring, and data is transmitted through Bluetooth; When the toothbrush is in a sleep state, the radio frequency is cut off and the RTC clock is turned off; When the toothbrush is in a transportation mode, only the wake-up pin is retained.

8. The brushing monitoring method of claim 1, wherein, Based on the average tooth brushing time length of the historical period, the next tooth brushing time length is predicted, which is calculated by the following formula: ， ， ， ， ， ， In the formula, denotes the average brushing time of the previous n times of brushing, is the brushing time of the kth time of brushing in the previous n times of brushing; is the predicted brushing time of the n+1th time of brushing, i.e., the next brushing time; A denotes a sequence set of the selected sample number n, T A is a sequence set of the brushing time corresponding to A; Cov is a covariance function; Var is a variance function; mean is a mean value function; denotes the slope; denotes the intercept; When the next tooth brushing time length is higher than a predetermined tooth brushing time threshold, the tooth brushing time threshold is increased by S seconds.

9. A smart toothbrush characterized in that, The computer program is executed by the processor to realize the steps of the tooth brushing monitoring method according to any one of claims 1 to 8.

10. A computer program product comprising a computer program, characterized in that, The computer program is executed by the processor to realize the steps of the tooth brushing monitoring method according to any one of claims 1 to 8.

Images