A brushing monitoring and evaluation method, device, electric toothbrush, and readable storage medium.

Abstract

This application relates to the field of smart toothbrush technology, and discloses a brushing monitoring and evaluation method, device, electric toothbrush, and readable storage medium. The method includes: acquiring a user-set standard brushing time parameter, and dividing the standard brushing time parameter into target times corresponding to multiple brushing areas according to preset rules; collecting brushing force data at a preset sampling frequency during the user's brushing process; analyzing the brushing force data based on force judgment conditions to obtain the effective brushing time corresponding to each brushing area; generating area brushing status data corresponding to each brushing area based on the effective brushing time; and generating brushing scores and visual information for displaying brushing status using the area brushing status data. This toothbrush achieves a scientific, visual, and intelligent evaluation of the brushing process, effectively improving user brushing compliance and cleaning quality. It enhances the human-computer interaction experience and helps users develop good oral care habits.

Description

Technical Field

[0001] This application relates to the field of smart toothbrush technology, and in particular to a brushing monitoring and evaluation method, device, electric toothbrush, and readable storage medium. Background Technology

[0002] Currently, with the widespread adoption of smart health devices, electric toothbrushes with brushing behavior monitoring functions are gradually entering the consumer market. Existing products typically collect users' brushing movements and pressure information through built-in accelerometers or pressure sensors, and combine this with preset algorithms to analyze dimensions such as brushing time, coverage area, and force applied to evaluate brushing quality. Some high-end models are also equipped with displays or connect to mobile applications (APPs) that can display brushing progress, zone cleaning status, and overall score results in real time, thereby helping users improve their brushing habits. In addition, some systems are attempting to introduce reminder mechanisms based on time division or multi-zone guidance, prompting users to switch brushing areas during brushing through vibration or voice prompts, achieving proactive intervention in the brushing process and improving the comprehensiveness and effectiveness of oral cleaning.

[0003] However, existing brushing monitoring and evaluation methods still have significant shortcomings: although data such as brushing force are collected, most systems still use total brushing time as the main or even sole evaluation criterion, failing to accurately identify the effectiveness of brushing actions based on force ranges, and unable to distinguish between gentle, ineffective friction and effective brushing actions that achieve cleaning results; at the same time, without accurately identifying the effective cleaning degree of each area, existing scoring models mostly use simple threshold judgments or binary scoring methods to generate scores, resulting in a disconnect between the scoring results and the actual cleaning effect, and the feedback is rough and delayed; in terms of interaction design, due to the lack of refined judgment on the cleaning status of each area, the reminder of missed brushing near the end often only provides full voice broadcast for multiple uncleaned areas, causing information redundancy and auditory interference, affecting the user experience. Summary of the Invention

[0004] In view of this, the embodiments of this application provide a brushing monitoring and evaluation method, device, electric toothbrush and readable storage medium, which can effectively solve the technical problems in the prior art that lead to inaccurate scoring, imprecise feedback and strong interactive interference due to the lack of recognition of effective brushing behavior.

[0005] In a first aspect, embodiments of this application provide a brushing monitoring and evaluation method, applied to an electric toothbrush, comprising: Obtain the user-defined standard brushing time parameter, and divide the standard brushing time parameter into target times corresponding to multiple brushing areas according to preset rules; During the user's brushing process, brushing force data is collected at a preset sampling frequency; The brushing force data is analyzed based on preset force judgment conditions to obtain the effective brushing time corresponding to each brushing area. Based on the effective brushing time, generate brushing status data for each brushing area; The brushing status data of the aforementioned regions are used to generate brushing scores and visualizations to show the brushing status.

[0006] In some embodiments, the method further includes: When the current brushing time is detected to have reached the standard brushing time parameter, a brushing quality assessment report is generated based on the visualization information and the brushing score, and the brushing quality assessment report is read aloud via voice.

[0007] In some embodiments, obtaining the user-defined standard brushing time parameter and dividing the standard brushing time parameter into target times for multiple brushing areas according to preset rules includes: Receives standard brushing duration parameters input by the user; The brushing process is divided into six brushing areas, and the standard brushing time parameter is evenly distributed among the six brushing areas to obtain the target time corresponding to each brushing area.

[0008] In some embodiments, the step of collecting brushing force data at a preset sampling frequency during the user's brushing process includes: Upon receiving the brushing start signal, a real-time sampling task is initiated and the brushing time counter is initialized; Brushing force data is continuously collected according to the preset sampling frequency to obtain continuous brushing force data; Each collected brushing force data is associated with the brushing area identifier of the current brushing time, and the original brushing force data sequence corresponding to each brushing area is constructed in sequence.

[0009] In some embodiments, judging the brushing force data based on preset force judgment conditions to obtain the effective brushing time for each brushing area includes: Perform a moving average process on the original brushing force data sequence for each brushing area to obtain the corresponding smoothed force data; Based on a preset effective force range, the smooth force data is judged point by point to determine the data points in each brushing area that meet the force range. Based on the distribution of the data points on the time axis, the effective brushing time for each brushing area is calculated.

[0010] In some embodiments, generating corresponding area brushing status data based on the effective brushing time includes: Half of the target time for each brushing area is used as the state determination threshold. The effective brushing time for each brushing area is compared with the state determination threshold to obtain the corresponding brushing state. The brushing status is mapped to corresponding color status data to form regional brushing status data.

[0011] In some embodiments, generating brushing scores and visualizations for displaying brushing status using the regional brushing status data includes: The brushing status data for each brushing area is scored and calculated to obtain the corresponding single-area score value. The brushing score is generated by summing the scores of each individual area. Based on the brushing status data, the visualization information used to display the cleaning status of each brushing area is generated according to the preset graphic mapping rules.

[0012] Secondly, embodiments of this application provide a brushing monitoring and evaluation device, comprising: The duration division module is used to obtain the standard brushing time parameter set by the user and divide the standard brushing time parameter into target durations for multiple brushing areas according to preset rules; The sampling module is used to collect brushing force data at a preset sampling frequency during the user's brushing process; The judgment module is used to judge the brushing force data based on preset force judgment conditions in order to obtain the effective brushing time for each brushing area. The data generation module is used to generate corresponding area brushing status data based on the effective brushing time. The scoring module is used to generate a brushing score using the brushing status data of the area, and to generate visual information to display the brushing status.

[0013] Thirdly, embodiments of this application provide an electric toothbrush, which includes a processor and a memory. The memory stores a computer program, and the processor executes the computer program to implement the brushing monitoring and evaluation method of the first aspect described above.

[0014] Fourthly, embodiments of this application provide a computer-readable storage medium, wherein when the computer program is executed on a processor, it implements the brushing monitoring and evaluation method of the first aspect described above.

[0015] The embodiments of this application have the following beneficial effects: First, the standard brushing time parameter set by the user is obtained, and it is divided into target times corresponding to multiple brushing areas according to preset rules; during brushing, brushing force data is continuously collected at a preset sampling frequency; the collected data is analyzed based on preset force judgment conditions, and combined with the area division results on the time axis, the effective brushing time corresponding to each brushing area is calculated; brushing status data corresponding to each area is generated based on the effective brushing time; and brushing scores and visualization information for displaying brushing status are generated using this status data.

[0016] This application introduces an effective brushing time determination mechanism, which can accurately identify ineffective cleaning behaviors caused by insufficient or excessive brushing force, thus improving the scientific nature of the scoring. The logical area division based on time equalization does not rely on complex posture recognition hardware, reducing implementation costs. The dynamically generated area brushing status enhances the real-time interactivity. Combined with the refined scoring and visualization of the cleaning status, it helps users adjust their brushing behavior in a timely manner, significantly improving oral cleaning effect and user experience. Attached Figure Description

[0017] 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.

[0018] Figure 1 A flowchart of a brushing monitoring and evaluation method according to an embodiment of this application is shown; Figure 2 Another flowchart of the brushing monitoring and evaluation method according to an embodiment of this application is shown; Figure 3 This illustrates yet another flowchart of the brushing monitoring and evaluation method according to an embodiment of this application; Figure 4 This illustration shows a state-color mapping diagram in the brushing monitoring and evaluation method of this application. Figure 5 A schematic diagram of voice playback in the brushing monitoring and evaluation method of this application is shown; Figure 6 A schematic diagram of a structure in the brushing monitoring and evaluation method of this application is shown. Detailed Implementation

[0019] The technical solutions in 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.

[0020] The components of the embodiments of this application described and illustrated in the accompanying drawings can be arranged and designed in a variety of different configurations. Therefore, the following detailed description of the embodiments of this application provided in the drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0021] In the following text, the terms "comprising," "having," and their cognates, which may be used in various embodiments of this application, are intended only to indicate a particular feature, number, step, operation, element, component, or combination thereof, and should not be construed as primarily excluding the presence of one or more other features, numbers, steps, operations, elements, components, or combinations thereof, or adding the possibility of one or more combinations thereof. Furthermore, the terms "first," "second," "third," etc., are used only for distinguishing descriptions and should not be construed as indicating or implying relative importance.

[0022] Unless otherwise specified, all terms used herein (including technical and scientific terms) shall have the same meaning as commonly understood by one of ordinary skill in the art to which the various embodiments of this application pertain. Terms (such as those defined in commonly used dictionaries) shall be interpreted as having the same meaning as in their contextual meaning in the relevant technical field and shall not be construed as having an idealized or overly formal meaning, unless clearly defined in the various embodiments of this application.

[0023] The following detailed description of some embodiments of this application is provided in conjunction with the accompanying drawings. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0024] Considering the technical problems of inaccurate scoring, imprecise feedback, and strong interactive interference caused by the lack of recognition of effective brushing behavior in existing technologies, a brushing monitoring and evaluation method is proposed. By integrating time-partition management and effective brushing behavior recognition mechanism, the method can achieve accurate evaluation and dynamic feedback of the brushing process, thereby improving user brushing compliance and oral hygiene.

[0025] The following examples illustrate this brushing monitoring and evaluation method.

[0026] Figure 1 A flowchart of a brushing monitoring and evaluation method according to an embodiment of this application is shown. Exemplarily, the brushing monitoring and evaluation method includes the following steps: Step S100: Obtain the standard brushing time parameter set by the user, and divide the standard brushing time parameter into target times corresponding to multiple brushing areas according to preset rules.

[0027] The standard brushing time parameter refers to the duration of a complete brushing process set by the user before starting brushing by operating the physical button on the electric toothbrush; the brushing area is a time segment unit divided based on oral cleaning logic; and the target time refers to the recommended cleaning time that each brushing area should achieve. By receiving the total time input by the user and dividing it evenly according to the fixed number of zones, the system achieves structured management of the time dimension of the brushing process, which serves to provide a time benchmark for subsequent effectiveness evaluation and status feedback of each area.

[0028] In an optional embodiment, step S100 includes the following sub-steps: S101 receives the standard brushing time parameter input by the user.

[0029] The standard brushing time parameter ranges from 2 to 4 minutes, with a minimum adjustment unit of 30 seconds. Users can increment the value by clicking the power button, and the currently selected duration is recorded in real time as the total brushing time for this task. For example, when a user first presses the power button to turn on the screen, they are directly taken to the mode selection interface without any history. Each press of the power button sequentially changes the displayed preset duration to "2 minutes," "2 minutes 30 seconds," "3 minutes," and so on up to "4 minutes." Pressing it again confirms and starts the brushing process. At this point, the selected value (e.g., 180 seconds) is stored as the standard brushing time parameter in local memory for subsequent timing and zone calculations. For instance, if the user sets the brushing time to 180 seconds, all subsequent time-related judgment logic, including the zone-switching reminder trigger cycle and the cleaning achievement threshold setting, will be executed based on this.

[0030] S102, the brushing process is divided into six brushing areas, and the standard brushing time parameter is evenly distributed to the six brushing areas to obtain the target time corresponding to each brushing area.

[0031] The six brushing zones are abstract units that divide a brushing process into six stages in chronological order. These stages correspond to the time allotted for cleaning common areas in the mouth, such as the upper left, upper right, upper front teeth, lower left, lower right, and lower front teeth or the lingual side. The target duration is the total duration divided by six. For example, based on the user-set total duration of 180 seconds, the target duration for each brushing zone is calculated to be 30 seconds (180 ÷ 6), and six consecutive intervals are established on the timeline: [0, 30), [30, 60), [60, 90), [90, 120), [120, 150), [150, 180). Each interval corresponds to one brushing zone. Whenever the effective brushing time accumulates to the next interval, it is considered as entering a new brushing zone, triggering the corresponding state update mechanism.

[0032] For example, every 30 seconds, the toothbrush will simultaneously trigger a vibration (about 0.1 seconds) and play a voice prompt "Please switch to the next area" to guide the user to actively change the brushing position. Even if no actual action occurs, the internal state machine will still advance according to this time node.

[0033] In other implementations, the number of zones can be adjusted according to the needs of different groups. For example, the children's mode uses four logical zones to simplify the guidance process, but in the default implementation, it is fixed at six zones to accommodate the standard care requirements of adults.

[0034] Step S200: During the user's brushing process, brushing force data is collected at a preset sampling frequency.

[0035] Among them, brushing force data refers to the force applied by the user between the brush head and the tooth contact surface, which is detected in real time by the pressure sensor built into the electric toothbrush; the sampling frequency is used to control the periodicity and continuity of data acquisition to ensure high-precision capture of brushing behavior; this step forms a time-seriesd raw data stream by continuously acquiring force signals, which serves as a basis for subsequent judgment on whether it constitutes an effective brushing action.

[0036] In one alternative embodiment, such as Figure 2 As shown, step S200 includes the following sub-steps: S201: Upon receiving a brushing start signal, start a real-time sampling task and initialize the brushing time counter.

[0037] Among them, the brushing start signal refers to the operation command triggered by the user pressing the power button again in the mode selection interface, marking the official start of the brushing process; the real-time sampling task is a timed interrupt task scheduled by the main control MCU, which is responsible for periodically reading sensor data; the brushing time counter is used to record the running time since the start, in milliseconds or seconds.

[0038] As an example, when the user presses the power button after completing the duration setting on the mode interface, the system immediately sets the "brushing teeth" status flag, initializes the time to 0, and starts a timer interrupt service routine that triggers once every 50ms to enter the continuous monitoring phase; from then on, the system begins to perform subsequent sampling actions at a frequency of 20Hz.

[0039] For example, if the current total duration is set to 120 seconds, the system will start accumulating time from t=0s and compare it with the time interval of each area to determine which brushing area each collected data belongs to.

[0040] S202 continuously collects brushing force data according to a preset sampling frequency to obtain continuous brushing force data.

[0041] The preset sampling frequency is 20Hz, meaning that the raw force value is acquired from the pressure sensor every 50ms. The brushing force data is a time series set composed of multiple discrete sampling points, reflecting the dynamic process of force changes during brushing. Exemplarily, within each sampling period, the analog voltage output by the sensor is converted into a digital force value (e.g., 180g) via the ADC module, and this value is temporarily stored in a buffer; subsequently, it enters the data processing flow.

[0042] For example, at a sampling time t=1.05s, the system reads the original force value as 420g. After subsequent filtering, it is determined that the force value exceeds the effective range, so it is not included in the effective brushing time, but it is still retained in the original data sequence for integrity traceability.

[0043] S203, associate and bind the brushing force data collected each time with the brushing area identifier to which the current brushing time belongs, and construct the original brushing force data sequence corresponding to each brushing area in sequence.

[0044] Among them, the brushing area identifier is a logical label assigned based on which time interval the current brushing time falls within (such as Region_1 to Region_6); the original brushing force data sequence refers to an ordered array composed of all unprocessed sampling points belonging to the same region.

[0045] As an example, the corresponding region mapping table is looked up based on the current time counter value, and it is determined that t=1.05s is in the first region [0,30). Therefore, the 420g data collected this time is tagged with "Region_1" and appended to the cache queue corresponding to Region_1. As the brushing progresses, each region gradually accumulates its own sampling sequence.

[0046] Step S300: Analyze the brushing force data based on preset force judgment conditions to obtain the effective brushing time corresponding to each brushing area.

[0047] The preset force judgment criteria refer to the standards used to identify whether a single brushing action has achieved a cleaning effect, mainly based on whether the applied force falls within a reasonable range. Effective brushing time refers to the cumulative time that the user applies force consistently to meet cleaning requirements within a specific brushing area, rather than simply the total time. This step transforms the physical perception signal into a quantifiable cleaning effectiveness indicator by filtering, thresholding, and time aggregation of the raw data. Its purpose is to eliminate interference from ineffective operations such as brushing too lightly or too heavily, achieving an accurate assessment of actual cleaning behavior.

[0048] In one alternative embodiment, such as Figure 3 As shown, step S300 includes the following sub-steps: S301, Perform a moving average processing on the original brushing force data sequence of each brushing area to obtain the corresponding smooth force data.

[0049] The moving average processing is a digital signal denoising algorithm that suppresses instantaneous sensor jitter or noise fluctuations by calculating the arithmetic mean of several consecutive sampling points. The smoothed force data is a more stable and representative force value sequence after filtering, used to improve the accuracy of subsequent judgments. For example, a moving average filter with a length of 5 points is applied to the original data sequence maintained independently for each brushing area (e.g., Region_1 contains 600 sampling points from t=0 to 30s) for mean filtering. That is, for each smoothed value output, the average of the current point and its four preceding adjacent points is taken as the result, thus generating a new smoothed force data sequence. For example, if a segment of original data is [45g, 38g, 420g, 48g, 52g], after moving average, the smoothed value at the midpoint is approximately 121.4g, effectively weakening the influence of abnormal peaks and making subsequent judgments closer to the true force trend.

[0050] S302, based on the preset effective force range, performs point-by-point judgment on the smooth force data to determine the data points in each brushing area that meet the force range.

[0051] The preset effective force range is defined as [50g, 400g], meaning that only force applied within this range can be considered an effective brushing action with cleaning ability. Force below the lower limit is considered insufficient friction, and force above the upper limit may damage the gums; neither is included in the effective time. For example, the system iterates through each data point in the smoothed force data sequence for each region, determining whether each point satisfies the condition 50 ≤ force ≤ 400. If true, the sampling time is marked as an "effective time." For instance, within a certain time period in Region_2, the system detects a set of smoothed force values ​​of 48g, 55g, 390g, and 410g. Only 55g and 390g fall within the effective range; therefore, only these two time points are considered effective, while the rest are considered invalid or risky actions.

[0052] S303 calculates the effective brushing time for each brushing area based on the distribution of data points on the time axis.

[0053] The distribution of data points on the time axis reflects the frequency and continuity of effective brushing actions. Each data point that meets the conditions corresponds to a sampling period (e.g., 50ms). For example, the sampling period lengths corresponding to all data points marked as "effective" are summed to obtain the cumulative effective brushing time for that region. For instance, in the 30-second target time of Region_3, a total of 600 data points are collected, of which 200 points meet the effective force condition; therefore, the effective brushing time is 200 × 0.05s = 10 seconds.

[0054] For example, if the effective brushing time for a certain area is 10 seconds, while the target time for that area is 30 seconds and the cleaning threshold is 15 seconds (i.e., half), then the area is considered not cleaned, which will affect the final score and status display.

[0055] In other implementations, the effective intensity range can be dynamically adjusted according to different user groups, for example, providing a gentle mode of [60g, 350g] for users with sensitive teeth.

[0056] Step S400: Based on the effective brushing time, generate brushing status data for each brushing area.

[0057] Effective brushing time refers to the cumulative time spent within a preset effective range of brushing pressure in a specific brushing area. Area brushing status data is structured information characterizing the degree of cleaning completion in that area, including semantic content such as whether the standard is met and the cleaning level. This step compares the quantified time indicators with preset judgment criteria, transforming raw perceived data into an interpretable state. Its purpose is to provide a unified status basis for subsequent steps of scoring calculation and visual feedback.

[0058] In an optional embodiment, step S400 includes the following sub-steps: S401, use half of the target time for each brushing area as the state determination threshold.

[0059] The status judgment threshold is a time benchmark for determining whether a brushing area has achieved basic cleaning requirements. It is set at 50% of the corresponding target time, reflecting the user experience design principle of "half-effective cleaning is considered complete." For example, after completing the time partitioning, the target time for each area is calculated, and half of that time is taken as the cleaning standard for that area. For instance, when the total brushing time is 180 seconds, the target time for each area is 30 seconds, then the status judgment threshold is 15 seconds. If the effective brushing time for an area reaches or exceeds 15 seconds, then that area is considered to have achieved basic cleaning. This threshold setting avoids the pressure of having to "brush the entire area for the full time" while preventing perfunctory behavior caused by judging completion in too short a time, thus balancing scientific accuracy and usability.

[0060] S402, compare the effective brushing time of each brushing area with the state determination threshold to obtain the corresponding brushing state.

[0061] The brushing status is represented by a binary or multi-level label, such as "cleaned" or "not cleaned," indicating the completion status of the current area. For example, the system iterates through the six brushing areas, comparing the cumulative effective brushing time of each area with the corresponding status threshold. If the former is greater than or equal to the latter, a "cleaned" status label is generated; otherwise, a "not cleaned" status label is generated. For instance, Region_4 has an effective brushing time of 12 seconds, which is less than its 15-second threshold, so the system marks it as "not cleaned"; while Region_1 has 18 seconds, which is greater than 15 seconds, so it is marked as "cleaned." This result directly affects subsequent scoring and interface display logic.

[0062] S403 maps the brushing status to corresponding color status data to form area brushing status data.

[0063] Color status data is color-coded information used to drive the UI display; for example, red indicates uncleaned and white indicates cleaned, providing intuitive visual feedback. As an example, a status-color mapping table is established, mapping "cleaned" to white and "uncleaned" to red, and this color value is written to the corresponding display buffer. The display screen updates the color of the corresponding area in the dental model image with a millisecond-level response time, achieving near real-time feedback. Figure 4 As shown.

[0064] For example, when a user brushes their teeth effectively in the third area for 16 seconds (>15 seconds threshold), an animation effect that changes color from red to white is immediately triggered to provide positive reinforcement.

[0065] In other implementations, intermediate colors (such as light red) can be introduced to represent a cleanliness level that is close to but not yet up to standard, or custom theme color schemes can be supported. However, in the current embodiment, only a two-color mechanism is used to ensure rendering efficiency and clear recognition under low-power devices.

[0066] Step S500: Use the regional brushing status data to generate brushing scores and visualization information to display the brushing status.

[0067] The brushing status data represents the cleaning completion status of each brushing area, including criteria such as whether the standard was met and the duration of brushing. The brushing score is a comprehensive evaluation of the brushing quality in numerical form, with a maximum score of 100. Visual information refers to the brushing status feedback presented through a graphical interface, such as changes in the color of the dental model and progress indicators. This step transforms discrete status data into highly readable quantitative scores and intuitive image output, realizing the conversion from low-level data analysis to user-perceptible results. Its role is to enhance the objectivity of feedback and interactive experience, helping users quickly understand the brushing effect and improve subsequent brushing habits.

[0068] In an optional embodiment, step S500 includes the following sub-steps: S501 calculates a score for the brushing status data of each brushing area to obtain the corresponding single-area score value.

[0069] The single-zone score is an independent score assigned to each of the six brushing zones. Its value is positively correlated with the effective brushing time in that zone, reflecting a gradual improvement in cleanliness rather than a simple binary judgment. For example, a total score of 100 points is set, and the score is evenly distributed across the six zones, with each zone having a maximum score of approximately 16.6 points. The actual score is calculated proportionally: Single-zone score = (16.6 / State judgment threshold) × Actual effective brushing time. For instance, if the target brushing time for a zone is 30 seconds, and the state judgment threshold is 15 seconds, and the actual effective brushing time for that zone is 12 seconds, the score is (16.6 / 15) × 12 ≈ 13.28, rounded to one decimal place as 13.3 points. If the effective brushing time is 15 seconds or more, the full score of 16.6 points is directly assigned. This mechanism ensures that the scoring accurately reflects the differences in the user's actual brushing performance, avoiding a coarse-grained "all or nothing" scoring.

[0070] S502 sums the scores of each individual area to generate a brushing score.

[0071] The brushing score is the arithmetic sum of the scores from six brushing zones, forming the final overall quality indicator presented to the user. For example, the individual zone scores for all zones are iterated and summed; for instance, if the scores for the six zones are 13.3, 16.6, 14.8, 16.6, 12.1, and 16.6, the total score is 90.0. This total score is displayed in real-time on the results page after brushing and can also be provided to the user via voice prompts.

[0072] In other implementations, weights can be set according to the importance of different regions (e.g., the anterior teeth region has a higher weight), but the current embodiment adopts an equal-weighted summation strategy to maintain the simplicity and fairness of the algorithm, which is suitable for general adult care scenarios.

[0073] S503 generates visual information to display the cleaning status of each brushing area based on brushing status data and according to preset graphic mapping rules.

[0074] The graphic mapping rules define the correspondence between brushing status and UI elements, such as position, color, and animation effects. The visualization information is specifically represented by dynamic dental model images on the electric toothbrush display, simulating the cleaning progress of six areas in a real oral cavity. Exemplarily, the color of the corresponding tooth block is updated based on the brushing status of each area ("cleaned" or "not cleaned"): initially red, turning white after reaching the target, with the color change response latency controlled within milliseconds, achieving near-instantaneous feedback. For example, when the effective brushing time for Region_2 reaches the target, the screen immediately refreshes the corresponding tooth model to white, regardless of whether the user actually changes position; the system renders based on the time and effective action judgment results.

[0075] In an optional embodiment, the brushing monitoring and evaluation method further includes the following steps: When the system detects that the current brushing time has reached the standard brushing time parameter, it generates a brushing quality assessment report based on visual information and brushing score, and then reads the report aloud via voice.

[0076] The brushing quality assessment report is a summary feedback automatically generated after the brushing process, including an overall score, an overview of the cleaning status of each area, and encouraging or suggestive statements to help users understand their brushing performance. Voice-based feedback uses the electric toothbrush's built-in audio module to output pre-programmed or combined voice snippets, providing instant feedback without visual intervention. For example, when the preset total time (e.g., 180 seconds) is reached, the scoring summary module is immediately invoked to obtain the final brushing score (e.g., 90.0 points). Simultaneously, the color status data of the six areas (e.g., 4 white, 2 red) is read, and a structured broadcast message is generated based on a preset script template, such as: "This brushing score is 90 points; four areas are clean, and two areas need improvement." Subsequently, the voice chip is controlled to play this synthesized voice, completing the auditory feedback, such as... Figure 5 As shown.

[0077] For example: if all areas meet the standards, play encouraging messages such as "Congratulations on completing the full cleaning!"; if there are uncleaned areas, add reminders such as "Please pay attention to the cleaning time for the upper left and lower right areas".

[0078] In other implementations, the broadcast language, volume level, or mute mode can be set according to user preferences, and the report can also be pushed synchronously to a connected mobile application for long-term trend analysis.

[0079] Figure 6 A schematic diagram of a brushing monitoring and evaluation device according to an embodiment of this application is shown. Exemplarily, the device 100 includes: The duration division module 110 is used to obtain the standard brushing duration parameter set by the user and divide the standard brushing duration parameter into target durations for multiple brushing areas according to preset rules. The sampling module 120 is used to collect brushing force data at a preset sampling frequency during the user's brushing process; The judgment module 130 is used to judge the brushing force data based on preset force judgment conditions in order to obtain the effective brushing time of each brushing area. The data generation module 140 is used to generate corresponding area brushing status data based on the effective brushing time. The scoring module 150 is used to generate a brushing score using the brushing status data of the area, and to generate visual information to display the brushing status.

[0080] It is understood that the apparatus of this embodiment corresponds to the method of the above embodiments, and the options in the above embodiments are also applicable to this embodiment, so they will not be described again here.

[0081] This application also provides an electric toothbrush, exemplary of which includes a processor and a memory, wherein the memory stores a computer program, and the processor, by running the computer program, causes the electric toothbrush to perform the functions of the various modules in the above-described method or apparatus.

[0082] The processor can be an integrated circuit chip with signal processing capabilities. The processor can be a general-purpose processor, including at least one of a Central Processing Unit (CPU), Graphics Processing Unit (GPU), Network Processor (NP), Digital Signal Processor (DSP), Application-Specific Integrated Circuit (ASIC), Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. The general-purpose processor can be a microprocessor or any conventional processor, capable of implementing or executing the methods, steps, and logic block diagrams disclosed in the embodiments of this application.

[0083] The memory can be, but is not limited to, Random Access Memory (RAM), Read Only Memory (ROM), Programmable Read-Only Memory (PROM), Erasable Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), etc. The memory is used to store computer programs, and the processor can execute the computer programs accordingly after receiving execution instructions.

[0084] This application also provides a computer-readable storage medium for storing the computer program used in the electric toothbrush described above. For example, the computer-readable storage medium may include, but is not limited to, various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0085] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can also be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings show the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that, in alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and combinations of blocks in the block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0086] In addition, the functional modules or units in the various embodiments of this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0087] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a 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 part 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 smartphone, 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.

[0088] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A tooth brushing monitoring assessment method, characterized in that, The method applied to an electric toothbrush comprises: obtaining a standard brushing time parameter set by a user, and dividing the standard brushing time parameter into target time lengths corresponding to multiple brushing areas according to a preset rule; acquiring brushing force data at a preset sampling frequency during the user's brushing process; analyzing the brushing force data based on a preset force judgment condition to obtain effective brushing time lengths corresponding to the brushing areas; generating area brushing state data corresponding to the brushing areas according to the effective brushing time lengths; generating a brushing score and visual information for displaying brushing states by using the area brushing state data.

2. The brushing monitoring assessment method of claim 1, wherein, The method further comprises: when it is detected that the current brushing time reaches the standard brushing time parameter, generating a brushing quality evaluation report based on the visual information and the brushing score, and playing the brushing quality evaluation report through voice.

3. The brushing monitoring assessment method of claim 1, wherein, The method of obtaining a standard brushing time parameter set by a user, and dividing the standard brushing time parameter into target time lengths corresponding to multiple brushing areas according to a preset rule comprises: receiving a standard brushing time parameter input by a user; dividing a brushing process into six brushing areas, and equally distributing the standard brushing time parameter to the six brushing areas to obtain target time lengths corresponding to each brushing area.

4. The brushing monitoring assessment method of claim 1, wherein, The method of acquiring brushing force data at a preset sampling frequency during the user's brushing process comprises: starting a real-time sampling task and initializing a brushing time counter when a brushing start signal is received; continuously acquiring brushing force data at a preset sampling frequency to obtain continuous brushing force data; binding each acquired brushing force data to a brushing area identifier to which the current brushing time belongs, and sequentially constructing original brushing force data sequences corresponding to the brushing areas.

5. The brushing monitoring assessment method of claim 1, wherein, The method of judging the brushing force data based on a preset force judgment condition to obtain effective brushing time lengths of the brushing areas comprises: performing a moving average processing on the original brushing force data sequences of the brushing areas to obtain corresponding smooth force data; judging the smooth force data point by point based on a preset effective force interval to determine data points in the brushing areas that meet the force interval; statistically obtaining effective brushing time lengths of the brushing areas based on the distribution of the data points on a time axis.

6. The brushing monitoring assessment method of claim 1, wherein, The method of generating corresponding area brushing state data according to the effective brushing time lengths comprises: taking half of the target time length of each brushing area as a state judgment threshold; comparing the effective brushing time lengths of the brushing areas with the state judgment threshold to obtain corresponding brushing states; mapping the brushing states into corresponding color state data to form area brushing state data.

7. The brushing monitoring assessment method of claim 1, wherein, The method of generating a brushing score and visual information for displaying brushing states by using the area brushing state data comprises: performing score calculation on the brushing state data of each brushing area to obtain corresponding single-area score values; summing the single-area score values to generate the brushing score; generating the visual information for displaying cleaning states of the brushing areas based on the brushing state data and according to a preset graphic mapping rule.

8. A tooth brushing monitoring assessment device, characterized in that, Comprise: A time length division module, configured to obtain a standard brushing time length parameter set by a user, and divide the standard brushing time length parameter into target time lengths of a plurality of brushing areas according to a preset rule; A sampling module, configured to collect brushing force data at a preset sampling frequency during brushing of the user; A judgment module, configured to judge the brushing force data based on a preset force judgment condition, to obtain effective brushing time lengths of the brushing areas; A data generation module, configured to generate corresponding regional brushing state data according to the effective brushing time lengths; A scoring module, configured to generate a brushing score by using the regional brushing state data, and generate visual information for displaying a brushing state.

9. An electric toothbrush characterized by comprising: The electric toothbrush comprises a processor and a memory, the memory stores a computer program, and the processor is used to execute the computer program to implement the brushing monitoring and evaluation method in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The memory stores a computer program, and the computer program is executed on the processor to implement the brushing monitoring and evaluation method in any one of claims 1-7.

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