Control method and device of electric toothbrush, electric toothbrush and computer storage medium

Abstract

The invention provides a control method and device of an electric toothbrush, the electric toothbrush and a computer storage medium, and the method comprises the steps that under the condition that it is detected that a current sub-period starts, periodic tooth brushing data corresponding to the current sub-period are acquired, and the periodic tooth brushing data comprise tooth brushing behavior data collected in a preset reference period before the current sub-period; determining control parameter information of the current sub-period according to the periodic tooth brushing data; in the current sub-period, controlling the electric toothbrush to operate based on the control parameter information, and collecting tooth brushing behavior data in the current sub-period; and in response to the end of the current sub-cycle, updating the periodic tooth brushing data based on the tooth brushing behavior data collected in the current sub-cycle, generating updated periodic tooth brushing data, determining the start of the next sub-cycle, and determining the control parameter information of the next sub-cycle based on the updated periodic tooth brushing data. According to the embodiment provided by the scheme, the adaptive capacity of the electric toothbrush to individual differences can be enhanced.

Description

Technical Field

[0001] This application relates to the field of oral care technology, and in particular to a control method, device, electric toothbrush, and computer storage medium for an electric toothbrush. Background Technology

[0002] In related technologies, electric toothbrushes typically offer multiple preset cleaning modes, such as standard cleaning, sensitive care, and deep cleaning. Each mode corresponds to fixed operating parameters, which are usually set at the factory. Users can only switch between a few limited modes during use and cannot make in-depth personalized adjustments.

[0003] However, in practice, different users have significant differences in brushing habits, and using a fixed cleaning pattern is difficult to match the individualized cleaning needs. Summary of the Invention

[0004] This application provides a control method, device, electric toothbrush, and computer storage medium for an electric toothbrush, which can improve cleaning effect and user comfort, and enhance the adaptability of the electric toothbrush to individual differences. The above technical solution is as follows:

[0005] In a first aspect, embodiments of this application provide a control method for an electric toothbrush, the method comprising:

[0006] When the start of the current sub-cycle is detected, the periodic brushing data corresponding to the current sub-cycle is obtained. The periodic brushing data includes brushing behavior data collected within a preset reference cycle before the current sub-cycle.

[0007] The control parameter information for the current sub-cycle is determined based on the brushing data from the above cycle.

[0008] Within the aforementioned current sub-cycle, the electric toothbrush is controlled to operate based on the aforementioned control parameter information, and brushing behavior data within the aforementioned current sub-cycle is collected.

[0009] In response to the end of the current sub-cycle, the brushing data of the cycle is updated based on the brushing behavior data collected in the current sub-cycle, generating updated brushing data of the cycle, and the start of the next sub-cycle is determined. The control parameter information of the next sub-cycle is determined based on the updated brushing data of the cycle.

[0010] In one possible implementation, the control parameter information for the next sub-cycle is determined based on the updated periodic brushing data, including:

[0011] The next sub-cycle is taken as the new current sub-cycle, and the process returns to the steps of obtaining the cycle brushing data corresponding to the current sub-cycle when the start of the current sub-cycle is detected, and determining the control parameter information of the current sub-cycle based on the cycle brushing data.

[0012] In one possible implementation, after determining the control parameter information for the current sub-cycle based on the aforementioned periodic brushing data, the method further includes:

[0013] Determine whether the current update count of the brushing data in the above cycle has reached the preset update count threshold;

[0014] If the number of updates does not reach the preset update threshold, the steps of controlling the electric toothbrush to operate based on the control parameter information and collecting brushing behavior data within the current sub-cycle are determined to be executed.

[0015] In one possible implementation, the above method also includes:

[0016] When the number of updates reaches the preset update threshold, the first preset period is determined to begin, and the control parameter information is used as the initial control parameter for the first preset period.

[0017] Within the first preset period, the electric toothbrush is controlled to operate based on the initial control parameters, and brushing behavior data within the first preset period is collected.

[0018] In response to the end of the first preset cycle, a new current sub-cycle is started, and the process returns to the steps of obtaining the cycle brushing data corresponding to the current sub-cycle when the start of the current sub-cycle is detected.

[0019] In one possible implementation, the periodic brushing data is updated based on the brushing behavior data collected within the current sub-cycle to generate updated periodic brushing data, including:

[0020] The brushing behavior data collected in the current sub-cycle is added to the brushing data of the cycle to generate updated brushing data of the cycle.

[0021] In one possible implementation, updating the periodic brushing data based on the brushing behavior data collected within the current sub-cycle to generate updated periodic brushing data further includes:

[0022] If the amount of brushing data in the above-mentioned cycle exceeds the preset target amount, delete one or more brushing behavior data with the earliest corresponding time in the above-mentioned cycle brushing data, so that the amount of brushing data in the above-mentioned cycle is equal to the preset target amount.

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

[0024] If the electric toothbrush is detected to be in the initialization state, the preset initial control parameters are obtained;

[0025] Within the first preset period, the electric toothbrush is controlled to operate based on the initial control parameters mentioned above, and brushing behavior data within the first preset period is collected.

[0026] In response to the end of the first preset cycle, the current sub-cycle is started, and the brushing behavior data collected in the first preset cycle is used as the brushing behavior data collected in the preset reference cycle before the current sub-cycle. The steps of obtaining the cycle brushing data corresponding to the current sub-cycle are then executed.

[0027] In one possible implementation, obtaining the preset initial control parameters includes:

[0028] To obtain information about users' oral health issues and / or brushing habits;

[0029] The preset initial control parameters are determined based on the oral health information and / or brushing habits information mentioned above.

[0030] In one possible implementation, obtaining the user's oral health information and / or brushing habits information includes:

[0031] Obtain the oral health information and / or brushing behavior preference information identified by the user through the user terminal; and / or,

[0032] The above-mentioned electric toothbrush is used to perform oral examination on the above-mentioned user to identify oral health issues and / or brushing habits.

[0033] In one possible implementation, determining the control parameter information for the current sub-cycle based on the aforementioned periodic brushing data includes:

[0034] The control parameter information for the current sub-cycle is obtained by processing the brushing data of the aforementioned cycle using the first preset model locally on the electric toothbrush; or...

[0035] The aforementioned periodic brushing data is sent to the server, where a second preset model deployed on the server performs parameter generation processing on the periodic brushing data to obtain the control parameter information for the current sub-cycle, and receives the control parameter information returned by the server.

[0036] In one possible implementation, determining the control parameter information for the current sub-cycle based on the aforementioned periodic brushing data includes:

[0037] Feature extraction was performed on the above periodic brushing data to obtain brushing behavior feature values ​​corresponding to each tooth area;

[0038] By comparing and analyzing the above brushing behavior characteristics with preset health standard parameters, the risk level of each tooth area and the parameters to be adjusted are determined.

[0039] Based on the risk level and parameters to be adjusted for each of the aforementioned dental areas, determine the regional control parameters for each dental area.

[0040] The regional control parameters of each of the above-mentioned dental regions are used as the control parameter information for the current sub-cycle.

[0041] In one possible implementation, the above method also includes:

[0042] Based on the above periodic brushing data, the cleaning data for each dental area was determined;

[0043] The cleaning data of each of the above-mentioned dental areas were analyzed to obtain the corresponding analysis results for each of the above-mentioned dental areas.

[0044] Based on the analysis results corresponding to each of the above tooth regions, the first prompt information corresponding to the above tooth regions is generated;

[0045] The first prompt message mentioned above will be displayed.

[0046] In one possible implementation, the above-mentioned cleaning data of each tooth region is parsed to obtain the corresponding parsing results for each tooth region, including:

[0047] For each of the above-mentioned dental areas, the preset index data of the above-mentioned dental areas are obtained from the dental area cleaning data of the above-mentioned dental areas;

[0048] Determine whether the above preset indicator data meet the corresponding preset compliance conditions;

[0049] If the aforementioned preset indicator data does not meet the aforementioned preset criteria, an analytical result indicating the risk of tooth decay in the aforementioned dental area will be generated.

[0050] In one possible implementation, the aforementioned preset indicator data can be any of the following: number of missed brushes, cleaning coverage, and cleaning duration;

[0051] When the above-mentioned preset indicator data is the above-mentioned number of missed refreshes, the corresponding preset compliance condition is: the above-mentioned number of missed refreshes is less than the preset number threshold.

[0052] When the preset indicator data is the above-mentioned cleaning coverage rate, the corresponding preset compliance condition is: the above-mentioned cleaning coverage rate is greater than the preset coverage rate threshold.

[0053] When the preset indicator data is the above-mentioned cleaning time, the corresponding preset compliance condition is: the above-mentioned cleaning time is greater than the preset time threshold.

[0054] In one possible implementation, if the aforementioned preset indicator data does not meet the aforementioned preset compliance conditions, the method further includes:

[0055] For preset indicator data that do not meet the above preset criteria, generate the marking information for the above-mentioned dental areas;

[0056] The control parameter information for the current sub-cycle, determined based on the brushing data from the aforementioned cycle, includes:

[0057] Based on the preset parameter adjustment model, the brushing data of the above cycle and the marking information are processed to generate parameters to obtain the control parameter information of the current sub-cycle. The marking information is used as the input information of the parameter adjustment model to drive the parameter adjustment model to perform control parameter enhancement processing on the tooth area corresponding to the marking information.

[0058] In one possible implementation, displaying the aforementioned first prompt information includes:

[0059] The aforementioned first prompt message is displayed on the user terminal; and / or,

[0060] The aforementioned first prompt message is displayed on the screen of the electric toothbrush.

[0061] In one possible implementation, the above method also includes:

[0062] In response to the end of the current sub-cycle, determine whether the second preset cycle to which the current sub-cycle belongs has ended;

[0063] When the second preset cycle ends, the brushing data for the current cycle corresponding to the second preset cycle is generated.

[0064] Obtain the brushing data of the previous historical preset cycle corresponding to the second preset cycle mentioned above.

[0065] The brushing data of the current cycle and the brushing data of the historical cycles are compared to obtain the first comparison result;

[0066] A second prompt message is generated based on the first comparison result. The second prompt message is used to prompt the user about the changing trend of brushing behavior data within adjacent preset periods.

[0067] The second prompt message mentioned above will be displayed.

[0068] In one possible implementation, the aforementioned periodic brushing data includes at least one of the following: brushing frequency information, cleaning duration information, cleaning coverage information, missed brushing record information, brushing force information, and horizontal brushing record information within the aforementioned preset reference period.

[0069] In one possible implementation, the aforementioned control parameter information includes at least one of the following: brushing force parameter, cleaning duration parameter, vibration frequency parameter, and cleaning mode parameter.

[0070] In one possible implementation, the above method also includes:

[0071] If the completion of any brushing action within the current sub-cycle is detected, single brushing action data generated by the brushing action is generated.

[0072] A corresponding single brushing behavior assessment report is generated based on the above single brushing behavior data; and / or, a periodic brushing behavior assessment report is generated based on the above single brushing behavior data and the above periodic brushing data.

[0073] Show the above-mentioned single brushing behavior assessment report and / or the above-mentioned periodic brushing behavior assessment report.

[0074] In one possible implementation, the above method also includes:

[0075] Obtain the user's initial oral cavity model, as well as information on the user's oral health issues and / or brushing habits;

[0076] Based on the above information on oral health problems and / or the above information on brushing habits, the first potential health problem corresponding to each dental area is determined.

[0077] Based on the above periodic brushing data, the second potential health problem corresponding to each of the above dental areas was identified.

[0078] Based on the first and second potential health problems mentioned above, the initial oral cavity model is labeled to generate the target oral cavity model. Different types of potential health problems correspond to different labels.

[0079] The target oral cavity model described above is presented.

[0080] Secondly, embodiments of this application provide a control device for an electric toothbrush, the device comprising:

[0081] The first acquisition module is used to acquire the periodic brushing data corresponding to the current sub-cycle when the start of the current sub-cycle is detected. The periodic brushing data includes brushing behavior data collected within a preset reference cycle before the current sub-cycle.

[0082] The first determining module is used to determine the control parameter information of the current sub-cycle based on the brushing data of the above cycle.

[0083] The first control module is used to control the operation of the electric toothbrush based on the control parameter information during the current sub-cycle, and to collect brushing behavior data during the current sub-cycle.

[0084] The update module is used to update the brushing data of the current cycle based on the brushing behavior data collected in the current cycle in response to the end of the current sub-cycle, generate updated brushing data of the current cycle, determine the start of the next sub-cycle, and determine the control parameter information of the next sub-cycle based on the updated brushing data of the current cycle.

[0085] Thirdly, embodiments of this application provide an electric toothbrush, including: a processor and a memory;

[0086] The aforementioned memory stores a computer program adapted to be loaded by the aforementioned processor and execute the steps of the method provided by the first aspect of the embodiments of this application or any possible implementation thereof.

[0087] Fourthly, embodiments of this application provide a computer storage medium storing a plurality of instructions adapted for loading by a processor and executing the steps of the method provided by the first aspect of the embodiments of this application or any possible implementation thereof.

[0088] This application embodiment acquires the corresponding periodic brushing data for the current sub-cycle upon detecting the start of the current sub-cycle. This periodic brushing data includes brushing behavior data collected within a preset reference cycle preceding the current sub-cycle. Then, control parameters for the current sub-cycle are determined based on the periodic brushing data. Within the current sub-cycle, the electric toothbrush is controlled based on these control parameters, and brushing behavior data is collected again. Subsequently, in response to the end of the current sub-cycle, the periodic brushing data is updated based on the collected brushing behavior data, generating updated periodic brushing data. The start of the next sub-cycle is then determined, and control parameters for the next sub-cycle are determined based on the updated periodic brushing data. Thus, by determining control parameters based on historical periodic brushing behavior data at the start of each sub-cycle and updating the periodic data after the sub-cycle ends, dynamic adaptive adjustment of brushing control parameters is achieved. Furthermore, by constructing a feedback optimization system between brushing behavior data and control strategies, the operating mode can be optimized according to the user's actual brushing habits and oral condition, thereby improving cleaning effectiveness and user comfort, and enhancing the electric toothbrush's adaptability to individual differences. Attached Figure Description

[0089] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0090] Figure 1 A schematic diagram of the structure of a control system for an electric toothbrush provided as an exemplary embodiment of this application;

[0091] Figure 2 A flowchart illustrating a control method for an electric toothbrush provided as an exemplary embodiment of this application;

[0092] Figure 3 A schematic diagram illustrating a preset period setting method provided for an exemplary embodiment of this application;

[0093] Figure 4 A flowchart illustrating a method for determining control parameter information of the current sub-cycle, provided as an exemplary embodiment of this application;

[0094] Figure 5 A flowchart illustrating a control method for an electric toothbrush provided as an exemplary embodiment of this application;

[0095] Figure 6 A flowchart illustrating a method for generating a first prompt message provided in an exemplary embodiment of this application;

[0096] Figure 7 A flowchart illustrating a second prompt information generation method provided for an exemplary embodiment of this application;

[0097] Figure 8 A schematic diagram of a periodic brushing data display page provided for an exemplary embodiment of this application;

[0098] Figure 9 A schematic diagram of the structure of a control device for an electric toothbrush provided as an exemplary embodiment of this application;

[0099] Figure 10 This is a schematic diagram of the structure of an electric toothbrush provided as an exemplary embodiment of this application. Detailed Implementation

[0100] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings.

[0101] The terms "first," "second," "third," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0102] Please refer to the following. Figure 1 The example illustrates a schematic diagram of the structure of a control system for an electric toothbrush provided in an embodiment of this application. Figure 1 As shown, the control system of this electric toothbrush may include: an electric toothbrush 110 and / or a user terminal 120. Wherein:

[0103] Electric toothbrushes 110 may, but are not limited to, be equipped with one or more indicator lights, one or more buttons, a speaker, a motor, etc.

[0104] Optionally, a wireless connection device may be installed in the electric toothbrush 110 to connect to the user terminal 120 and transmit corresponding brushing behavior data to the user terminal 120, such as, but not limited to, brushing number information, cleaning duration information, cleaning coverage information, missed brushing record information, brushing force information, and horizontal brushing record information.

[0105] Optionally, the electric toothbrush 110 can determine the control parameter information for the next sub-cycle of the current sub-cycle according to the control method of the electric toothbrush provided in the embodiments of this application. The electric toothbrush 110 can then operate in the next sub-cycle according to the determined control parameter information.

[0106] User terminal 120 can be a fixed or mobile terminal. A wireless connection device can be installed in user terminal 120 for establishing a wireless communication connection with one or more electric toothbrushes 110. User terminal 120 can have a control parameter information generation function. After establishing a wireless communication connection with the electric toothbrush 110, upon detecting the start of the current sub-cycle, it can acquire the periodic brushing data corresponding to the current sub-cycle. The periodic brushing data includes brushing behavior data collected within a preset reference cycle prior to the current sub-cycle. Based on the periodic brushing data, it determines the control parameter information for the current sub-cycle. Within the current sub-cycle, it controls the electric toothbrush to operate based on the control parameter information and collects brushing behavior data within the current sub-cycle. In response to the end of the current sub-cycle, it updates the periodic brushing data based on the brushing behavior data collected within the current sub-cycle, generating updated periodic brushing data, and determines the start of the next sub-cycle. Based on the updated periodic brushing data, it determines the control parameter information for the next sub-cycle. Here, a sub-cycle can be a subdivided time period within a larger cycle, and the larger cycle can be a second preset cycle, meaning the sub-cycle is a time unit contained within the second preset cycle. For example, when the second preset period is 7 days, the sub-period can be any natural day in that 7-day period.

[0107] User terminal 120 may be, but is not limited to, devices such as mobile phones, tablets, and laptops with user software installed, or display devices such as central control units with wireless connection devices installed.

[0108] It is understood that the electric toothbrush control method provided in this application embodiment can be executed by one or more of the electric toothbrush 110 and user terminal 120, and this application embodiment does not limit this.

[0109] The network can be a medium that provides a communication link between the electric toothbrush 110 and the user terminal 120, or it can be the Internet, which includes network devices and transmission media, and is not limited thereto. The transmission medium can be a wireless link, such as, but not limited to, Bluetooth, Wi-Fi, and mobile device networks.

[0110] Understandably, Figure 1 The number of electric toothbrushes 110 and user terminals 120 in the control system of the electric toothbrush shown is only an example. In a specific implementation, the control system of the electric toothbrush can include any number of electric toothbrushes 110 and user terminals 120. This application embodiment does not specifically limit this. For example, but not limited to, the electric toothbrush 110 can be an electric toothbrush cluster composed of multiple electric toothbrushes, and the user terminal 120 can be a terminal cluster composed of multiple terminals.

[0111] Next, combine Figure 1Taking the control method for an electric toothbrush as an example, this application introduces an exemplary embodiment of a control method for an electric toothbrush. Please refer to [link / reference needed] for details. Figure 2 The example illustrates a flowchart of a control method for an electric toothbrush provided in an embodiment of this application. Figure 2 As shown, the control method of this electric toothbrush includes the following steps:

[0112] S201: When the start of the current sub-cycle is detected, the periodic brushing data corresponding to the current sub-cycle is obtained. The periodic brushing data includes brushing behavior data collected within a preset reference cycle before the current sub-cycle.

[0113] The sub-period can be a subdivided time period within a larger period, which can be a second preset period. In other words, the sub-period is a time unit contained within the second preset period. For example, when the second preset period is 7 days, the sub-period can be any natural day within that 7-day period.

[0114] Optionally, the start time of the current sub-cycle can be identified through the electric toothbrush's internal time management function or triggered events (such as the user activating the electric toothbrush or the system time reaching a preset time), thereby enabling the detection of the start of the sub-cycle.

[0115] In one embodiment, periodic brushing data can refer to a set of brushing behavior data collected and saved in units of a fixed window period (i.e., the aforementioned preset reference period). For example, the preset reference period can be 7 days, then the periodic brushing data corresponding to the current sub-cycle is a set of brushing behavior data collected and saved within the 7 days prior to the current sub-cycle.

[0116] In one embodiment, the periodic brushing data may include at least one of the following: brushing frequency information, cleaning duration information, cleaning coverage information, missed brushing record information, brushing force information, and horizontal brushing record information within the aforementioned preset reference period. Specifically, the brushing frequency information can be used to determine whether the user's brushing frequency meets the recommended frequency, and may include, but is not limited to, the total number of times the user brushes within the preset reference period, the number of times they brush each day within the first period, etc. The cleaning duration information may include the duration of each brushing session, as well as statistical indicators such as the average, maximum, and minimum cleaning duration within the period, used to analyze whether the user is over-brushing. The cleaning coverage information can be used to reflect the completeness of cleaning each dental area, indicating whether the user has covered all dental areas during brushing; specifically, the coverage of each dental area can be determined through the inertial sensor or position detection algorithm built into the electric toothbrush. The missed brushing record information can indicate the number of times certain dental areas were not cleaned within the period. The brushing force information can be used to indicate the brushing force applied by the user to the teeth (e.g., light, medium, heavy) to determine whether there is excessive or insufficient force; specifically, it can be collected by the pressure sensor or current detection module built into the electric toothbrush. The horizontal brushing record information can include the number of times and the duration of incorrect back-and-forth brushing. The horizontal brushing record information can be detected by an accelerometer / angular velocity sensor to determine whether there are any unrecommended horizontal brushing behaviors.

[0117] By comprehensively collecting and analyzing information from multiple dimensions, it is possible to accurately characterize users' brushing behavior, thereby determining key indicators such as brushing frequency, cleaning completeness, and appropriateness of force. It can also identify bad brushing habits such as missing brushing, excessive force, or horizontal brushing, effectively improving the comprehensiveness of periodic brushing data.

[0118] S202: Determine the control parameter information for the current sub-cycle based on the brushing data of the above cycle.

[0119] The control parameter information can be configuration items used to adjust the brushing mode of the electric toothbrush. The aforementioned control parameter information includes at least one of the following: brushing force parameter, cleaning duration parameter, vibration frequency parameter, and cleaning mode parameter.

[0120] Optionally, determining the control parameter information for the current sub-cycle based on the brushing data of the aforementioned cycle includes: adjusting the parameters based on the control parameter information corresponding to the preset reference cycle and combining the brushing behavior data to generate the control parameter information for the current sub-cycle.

[0121] For example, multiple preset indicator data and corresponding preset achievement conditions can be set. These preset indicator data may include the number of missed brushings, cleaning coverage, and cleaning time. Specifically, the preset achievement condition for the number of missed brushings is: the number of missed brushings is less than a preset threshold; the preset achievement condition for cleaning coverage is: the cleaning coverage is greater than a preset coverage threshold; and the preset achievement condition for cleaning time is: the cleaning time is greater than a preset time threshold. Then, when any of the preset indicator data fails to meet the corresponding preset achievement condition, the control parameters for the preset reference period are adjusted accordingly. For example, if the number of missed brushings does not meet the corresponding preset achievement condition, the cleaning time parameter in the current sub-cycle can be extended; if the cleaning coverage does not meet the corresponding preset achievement condition, the frequency of reminders for missed brushing areas can be increased, or the brushing path control strategy can be adjusted; if the cleaning time does not meet the corresponding preset achievement condition, the vibration intensity can be increased or the overall brushing time can be extended.

[0122] By dynamically generating control parameters for the current sub-cycle based on brushing data from previous cycles, the electric toothbrush's brushing mode can be intelligently adjusted. This supports personalized optimization of key parameters such as brushing intensity, cleaning duration, vibration frequency, and cleaning mode. As a result, not only is brushing quality and coverage improved, but users are also effectively guided to develop scientific brushing habits. This reduces the burden of manual settings and enhances the convenience and health management capabilities of the electric toothbrush, thus significantly improving its intelligence and adaptability.

[0123] S203: During the current sub-cycle, control the electric toothbrush to operate based on the control parameter information and collect brushing behavior data during the current sub-cycle.

[0124] The current sub-cycle can refer to the time period during which the user is using the electric toothbrush. For example, if the sub-cycle is a natural day, the electric toothbrush can be controlled based on the above control parameter information during brushing in the morning and evening of that day, and brushing behavior data within the current sub-cycle can be collected.

[0125] Optionally, the operating status of the electric toothbrush can be automatically configured based on control parameter information, such as controlling the motor speed and intensity, controlling the cleaning time of different tooth areas in stages, and switching different vibration frequencies, so as to control the electric toothbrush to operate in the current sub-cycle and collect new brushing behavior data generated during operation.

[0126] S204: In response to the end of the current sub-cycle, update the periodic brushing data based on the brushing behavior data collected during the current sub-cycle, generate updated periodic brushing data, determine the start of the next sub-cycle, and determine the control parameter information for the next sub-cycle based on the updated periodic brushing data.

[0127] Understandably, a continuous timeline can be divided into sub-cycles at fixed time intervals. In this way, the end of the current sub-cycle marks the beginning of the next new sub-cycle. Adjacent sub-cycles are sequentially connected in time, ensuring continuous cycle data and clear control logic. For example, by dividing by natural days, N natural days can be considered as a sub-cycle, where N is a positive integer.

[0128] For example, if the sub-cycle is one calendar day, the current sub-cycle is considered to have ended when the detected time reaches 24:00 on that day. It should be noted that the end of the current sub-cycle is unrelated to the end time of brushing behavior. Even if the user does not use an electric toothbrush that day, the current sub-cycle will be considered complete at the end of that day. If no brushing is performed that day, it can be recorded as missing data or 0 brushings. The brushing behavior data collected within the current sub-cycle can then be added to the aforementioned cycle brushing data to generate updated cycle brushing data. Furthermore, the control parameters for the next sub-cycle can be determined based on the updated cycle brushing data. For example, based on the control parameters corresponding to a preset reference cycle, the parameters can be adjusted by combining brushing behavior data from a second preset cycle to generate the control parameters for the next sub-cycle.

[0129] This application embodiment acquires periodic brushing data corresponding to the current sub-cycle upon detecting the start of the current sub-cycle. This periodic brushing data includes brushing behavior data collected within a preset reference cycle preceding the current sub-cycle. Then, control parameters for the current sub-cycle are determined based on the periodic brushing data. Within the current sub-cycle, the electric toothbrush is controlled based on these control parameters, and brushing behavior data is collected again. Subsequently, in response to the end of the current sub-cycle, the periodic brushing data is updated based on the collected brushing behavior data, generating updated periodic brushing data. The start of the next sub-cycle is then determined, and control parameters for the next sub-cycle are determined based on the updated periodic brushing data. Thus, by determining control parameters based on historical periodic brushing behavior data at the start of a sub-cycle and updating the periodic data after the sub-cycle ends, dynamic adaptive adjustment of brushing control parameters is achieved. Furthermore, by constructing a feedback optimization system between brushing behavior data and control strategies, the operating mode can be optimized according to the user's actual brushing habits and oral condition, thereby improving cleaning effectiveness and user comfort, and enhancing the electric toothbrush's adaptability to individual differences.

[0130] In one embodiment, for the activation of the current sub-cycle, the method further includes: when the electric toothbrush is detected to be in an initialization state, obtaining preset initial control parameters; controlling the electric toothbrush to operate based on the initial control parameters within a first preset cycle, and collecting brushing behavior data within the first preset cycle; in response to the end of the first preset cycle, activating the current sub-cycle, and using the brushing behavior data collected within the first preset cycle as the brushing behavior data collected within a preset reference cycle prior to the current sub-cycle, and performing the step of obtaining the cycle brushing data corresponding to the current sub-cycle.

[0131] The initialization state can refer to the electric toothbrush's state during first use, factory reset, first startup after clearing user data, or configuration by a new user. When the electric toothbrush is in the initialization state, it has not yet stored valid historical brushing behavior data, nor has it formed personalized control parameters for the user. At this time, default initial control parameters are required to initiate the first brushing process and start data collection. Initial control parameters can include default brushing intensity parameters, cleaning duration parameters, vibration frequency parameters, and cleaning mode parameters, providing a consistent and safe startup behavior for the electric toothbrush and preventing brushing failure due to invalid or empty parameters.

[0132] Optionally, this first preset period can serve as a fixed parameter control period, meaning that within this first preset period, the electric toothbrush operates based on initial control parameters without dynamic adjustments. Through this fixed control phase, comprehensive user brushing behavior data can be collected to construct periodic brushing data, providing a reliable data foundation for the subsequent dynamic control phase in the second preset period, enabling personalized optimization and iterative updates of the brushing strategy.

[0133] In one embodiment, the first preset period and the second preset period can be set indirectly. The first preset period, the second preset period, and the preset reference period can be equal or unequal time periods, and the specific settings can be flexibly determined according to actual needs or strategy configuration. For example, in some application scenarios, the first preset period, the second preset period, and the preset reference period can be set to the same time length, such as 7 consecutive days; in other scenarios, the first preset period and the preset reference period can be set to a shorter initial data acquisition window (such as 5 days), while the second preset period is set to a longer dynamic control period (such as 10 days) to enhance the stability of personalized adjustment. In addition, the time lengths of the first preset period, the second preset period, and the preset reference period can also be dynamically adapted or automatically set by the system according to user behavior, data fluctuation degree, or system control accuracy requirements, and this application does not limit this.

[0134] Optionally, if the current sub-cycle is the first sub-cycle within a second preset cycle, then the preset reference cycle preceding the current sub-cycle can be the first preset cycle. For example, when a user uses an electric toothbrush for the first time, they can use initial control parameters to brush their teeth in a fixed pattern for the first 7 days (the first preset cycle), while simultaneously collecting brushing behavior data. When the 8th day is the first sub-cycle within the second preset cycle, the preset reference cycle preceding this sub-cycle can be the first preset cycle, i.e., days 1 to 7. In other words, the brushing data corresponding to the 8th day is the brushing behavior data collected within the 7 days preceding the 8th day (days 1 to 7).

[0135] Optionally, if the current sub-cycle is not the first sub-cycle within the second preset cycle, the preset reference cycle may include the preceding sub-cycles within the second preset cycle. For example, suppose both the first and second preset cycles are 7 days, and each sub-cycle is 1 day. If the current sub-cycle is the 3rd day of this cycle, the preset reference cycle preceding the current sub-cycle may be the previous 7 consecutive days, including the first 2 sub-cycles of the current second preset cycle (i.e., days 1 to 2) and the last 5 days of the previous first / second preset cycle (i.e., days 3 to 7 of the previous preset cycle).

[0136] Figure 3 A schematic diagram illustrating a preset period setting method provided in an exemplary embodiment of this application, as shown below. Figure 3 As shown, assuming both the first and second preset cycles are one week long (7 days), the electric toothbrush can automatically learn brushing behavior during the first preset cycle (e.g., days 1 to 7). During this stage, the electric toothbrush operates based on default initial control parameters, continuously collecting user brushing behavior data to build cyclical brushing data for subsequent parameter optimization and adjustment. The second preset cycle (e.g., days 8 to 14) consists of multiple sub-cycles (e.g., one sub-cycle per day). During this second preset cycle, the data collected in the first preset cycle is mined and analyzed, and targeted optimizations are gradually implemented. By assessing the brushing performance of each tooth area and adjusting parameters, dynamic and personalized configuration of brushing control parameters is achieved. Then, after the second preset cycle ends, starting from day 15, the intelligent adaptation stage begins. Based on the accumulated cyclical brushing data and adjustment records, a more stable and consistent control strategy tailored to the user's oral health and brushing habits is formed. During this stage, the electric toothbrush can automatically update control parameters according to cyclical changes, achieving long-term intelligent operation and self-iteration.

[0137] This application embodiment sets a first preset cycle and uses fixed initial control parameters when the electric toothbrush is in the initialization state. This enables the collection of user brushing behavior data even without historical data, thus laying the foundation for subsequent dynamic personalized control strategies. Based on this, combined with a preset reference cycle mechanism, flexible selection and dynamic sliding analysis of brushing behavior data at different stages are achieved. Whether in the initial sub-cycle of the second preset cycle or any intermediate sub-cycle, more accurate and reliable personalized control parameters can be generated by combining data within the reference cycle, effectively improving the continuity and timeliness of the control strategy. Furthermore, the preset cycle setting method provided in this application embodiment helps to achieve a brushing control process from learning and data collection to dynamic optimization and intelligent adaptation, based on a thorough understanding of user brushing behavior, thereby improving overall user experience and oral care levels.

[0138] In one embodiment, obtaining the preset initial control parameters includes: obtaining the user's oral health information and / or brushing habits information; and determining the preset initial control parameters based on the oral health information and / or brushing habits information.

[0139] The user's oral health information and brushing habits information can be basic information related to the user's oral health collected during the initialization phase. Oral health information can be subjectively filled out by the user and may include, but is not limited to, tooth decay, tartar, bleeding gums, sensitive gums, orthodontic treatment, etc. Brushing habits information can be obtained through questionnaires, application settings, or historical data, and may include, but is not limited to: whether the user has a habit of brushing horizontally, brushing frequency, whether certain areas are frequently missed, preferred brushing pressure, or cleaning duration, etc.

[0140] Optionally, the preset initial control parameters can be determined based on preset control strategy matching rules, combined with the oral health information and / or brushing habit information. For example, the control strategy matching rules may include: if there is gum sensitivity in the oral health information, the vibration frequency parameter is set to a preset low level, and the set sensitivity mode is enabled first; if there is a horizontal brushing habit in the brushing habit information, the brushing posture monitoring function can be enabled, and correction prompts (such as vibration reminders or voice guidance) can be enabled during brushing; if the brushing habit information includes a short brushing time (such as less than 120 seconds), a longer time (such as more than 120 seconds) can be allocated to each tooth area, and the area-by-area reminder function can be enabled; if the user reports "orthodontic status", a gentle brushing program is enabled, and the cleaning time of specific tooth areas is extended to adapt to the cleaning difficulties of the bracket area.

[0141] Optionally, the corresponding initial control parameters can be determined based on a preset tag combination mapping table. Specifically, common oral problems and brushing habits are pre-labeled, such as generating tags like "sensitive gums," "wearing orthodontic appliances," "having a habit of brushing horizontally," and "preferring to brush quickly." Based on one or more tags possessed by the user, the matching control parameter configuration is searched in the tag combination mapping table. For example, with the tag "sensitive gums + habit of brushing horizontally," the initial control parameters could be matched as: sensitive mode, low-intensity vibration, and activation of horizontal brushing correction prompts.

[0142] In this embodiment, by combining the user's oral health information and brushing habits during the initialization phase, and based on preset control strategy matching rules or tag combination mapping tables, personalized initial control parameters are intelligently set, which can significantly improve the adaptability and user experience of the electric toothbrush.

[0143] In one embodiment, obtaining the user's oral health information and / or brushing habit information includes: obtaining the user's determined oral health information and / or brushing habit information through a user terminal; and / or, performing oral health checks on the user through the electric toothbrush to identify the user's oral health information and / or brushing habit information.

[0144] The user terminal can have an application that matches the electric toothbrush installed, allowing users to actively input or select personalized information, such as gum sensitivity, orthodontic treatment, preference for low vibration mode, or forgetting to brush the lower right teeth area.

[0145] Optionally, electric toothbrushes can also connect with their built-in sensors or external devices to automatically detect the user's brushing behavior, thereby automatically identifying the user's oral health issues and brushing habits. For example, pressure sensors can identify brushing force, accelerometers can detect horizontal brushing motions, or the coverage of tooth areas can identify missed areas.

[0146] This embodiment combines user subjective input with automatic detection by the electric toothbrush to more comprehensively acquire information on users' oral health issues and brushing habits, achieving dual-channel fusion of personalized data collection. On one hand, users can proactively provide personalized preferences and oral health information through a terminal application, satisfying their diverse needs; on the other hand, the electric toothbrush, relying on built-in sensors and intelligent algorithms, automatically identifies the user's behavioral characteristics during actual brushing, improving the objectivity and real-time nature of data acquisition.

[0147] In one embodiment, in S202 above, determining the control parameter information of the current sub-cycle based on the periodic brushing data includes: performing parameter generation processing on the periodic brushing data using a first preset model local to the electric toothbrush to obtain the control parameter information of the current sub-cycle; or, sending the periodic brushing data to a server, where a second preset model deployed on the server performs parameter generation processing on the periodic brushing data to obtain the control parameter information of the current sub-cycle, and receiving the control parameter information returned by the server.

[0148] Optionally, the first preset model can be an artificial intelligence (AI) model deployed locally on the electric toothbrush (e.g., deployed on an embedded chip or control module within the electric toothbrush body) to perform parameter generation. The first preset model can be a lightweight design to adapt to the computing power and power consumption limitations of the electric toothbrush.

[0149] Specifically, the periodic brushing data is input into a first preset model, which then outputs the control parameter information for the current sub-cycle. Since the first preset model is deployed locally on the electric toothbrush, real-time control parameter information can be generated without relying on a network connection, thereby improving the response speed and offline availability of the electric toothbrush's control parameter upgrades.

[0150] Optionally, the second preset model can be an AI model deployed on a server to perform parameter generation. This second preset model can be a high-precision model trained using stronger computing power and a larger amount of data.

[0151] The server refers to the network device that hosts and runs the aforementioned second preset model, specifically a remote cloud server or an edge computing node. This server can store user brushing behavior data, related model parameters, and user profiles, and can support continuous model updates, iterative training, and real-time inference prediction, as well as send control parameter information to devices such as electric toothbrushes and user terminals. Optionally, the deployment method of the second preset model can include, but is not limited to, private clouds, public clouds, or intelligent service platforms provided by electric toothbrush manufacturers.

[0152] In one embodiment, the electric toothbrush may be equipped with a Wi-Fi module or a cellular communication module, enabling direct network communication.

[0153] Specifically, upon detecting the start of the current sub-cycle, the electric toothbrush acquires the corresponding brushing data for that sub-cycle and uploads it to the server via a wireless network, without relying on the user terminal as an intermediary. After receiving the brushing data, the server invokes a second preset model deployed in the cloud to process the data and generate parameters, then outputs the control parameters for the current sub-cycle and returns them to the electric toothbrush via wireless communication. The electric toothbrush loads these control parameters in real time and operates based on them within the current sub-cycle.

[0154] Optionally, both the first and second preset models can be trained using supervised learning. Training data includes brushing behavior data collected from users across multiple sub-cycles and preset cycles, along with corresponding parameter labels (such as control parameter information configurations that perform well in actual use). The first preset model can employ a lightweight neural network or decision model, and be streamlined through local training datasets or distilled from a large model via transfer learning to improve its operational efficiency and resource adaptability on the electric toothbrush embedded chip. The second preset model can be centrally trained on a server-side based on large-scale, multi-user, and multi-scenario brushing data, employing deep neural networks, time-series models, or multimodal fusion models. This allows for more complex feature representation and personalized strategy generation, and continuous iterative optimization to improve prediction accuracy and generalization ability. During the training phase, label feedback, user ratings, or oral health test results can be introduced as optimization targets to achieve data-driven adaptive optimization of control parameters.

[0155] In this embodiment, inference calculations can be performed locally on the electric toothbrush using a first preset model, enabling real-time local generation of control parameter information. This allows for personalized adjustments to the brushing mode without relying on a network connection, improving response speed and providing high privacy protection. It is particularly suitable for applications where users are in environments without network access or require low-latency control. Furthermore, by integrating a network communication module into the electric toothbrush and combining it with a high-performance AI model deployed in the cloud, automatic uploading and remote inference of periodic brushing data can be achieved. This leverages the stronger computing power and richer data resources of the cloud to enable the operation of more complex and precise AI models. Whether using the first or second preset model for parameter generation, the cumbersome operation of frequently updating parameters via the user's terminal application (APP) can be effectively avoided. Users do not need to actively open the APP or manually synchronize data; the electric toothbrush can automatically obtain personalized control parameter information in each sub-cycle, achieving dynamic upgrades and precise adjustments to the brushing mode. This effectively improves the ease of use and intelligence of the electric toothbrush, and enhances the model's continuous optimization and responsiveness.

[0156] In another embodiment, such as Figure 4 As shown, in S202 above, determining the control parameter information for the current sub-cycle based on the brushing data includes:

[0157] S401: Extract features from the above periodic brushing data to obtain brushing behavior feature values ​​corresponding to each tooth area.

[0158] Among them, brushing behavior feature values ​​can be structured data extracted for each tooth area, such as the average cleaning time, coverage, and average force of each tooth area.

[0159] Optionally, the periodic brushing data can first be divided according to dental regions, and the data related to each dental region in each sub-cycle within a preset reference period can be aggregated and statistically analyzed to output a set of feature values ​​for each dental region. Specifically, the oral cavity can be divided into multiple dental regions, such as: upper left, upper right, lower left, and lower right, each of which can be further subdivided into anterior teeth / molars. Then, multiple brushing behavior feature indicators are calculated for each dental region, including: cleaning time per unit time, cleaning coverage, average brushing force and the range of force fluctuation, detection frequency of horizontal brushing behavior, and the number of missed brushings in certain sub-cycles. Through the above feature extraction process, a set of structured brushing behavior feature values ​​can be constructed for each dental region.

[0160] S402: Compare and analyze the above brushing behavior characteristic values ​​with preset health standard parameters to determine the risk level of each tooth area and the parameters to be adjusted.

[0161] Optionally, the health standard parameters can refer to pre-set ideal cleaning reference parameters, such as cleaning time for each tooth area ≥30 seconds, cleaning coverage ≥90%, and brushing force at a medium level.

[0162] Optionally, the risk level of a dental area can represent the assessment level of the cleaning quality of the dental area, which can be divided into different levels such as good, average, poor, and high risk; the parameters to be adjusted can be the parameters that need to be adjusted according to the risk level of the dental area, such as brushing force, cleaning time, prompting method, etc.; the area control parameters can be personalized control parameters generated for each dental area to guide subsequent brushing behavior.

[0163] Specifically, brushing behavior characteristics can be used to determine whether each dental area meets the health standard parameters. If any indicator is not met, a corresponding risk marker is added to that dental area. Based on the number and degree of deviation of the unmet brushing behavior characteristics, the dental areas are divided into different risk levels, and corresponding parameters to be adjusted are determined. For example, one or more of the following parameters, such as cleaning time, coverage, and brushing force, are determined for dental areas with poor or high risk levels.

[0164] S403: Determine the regional control parameters for each of the above-mentioned dental areas based on the risk level of the dental area and the parameters to be adjusted.

[0165] Optionally, based on the risk level assessment results of each dental area, a corresponding parameter adjustment strategy template can be matched. Taking a dental area with a "poor" risk level as an example, if the corresponding parameters to be adjusted are cleaning time and brushing force, control parameters such as extending the cleaning time (e.g., by 20%), limiting the maximum brushing force, and setting a priority cleaning sequence can be set for that area. For dental areas with a "high risk" risk level, further settings such as strong vibration reminders and position correction prompts (e.g., horizontal brushing detection) can be added. By implementing differentiated control for different dental areas based on risk level and brushing behavior characteristics, a more personalized and intelligent brushing guidance strategy can be achieved, thereby effectively improving the performance of the electric toothbrush.

[0166] S404: Use the regional control parameters of each of the above-mentioned dental areas as the control parameter information for the current sub-cycle.

[0167] Specifically, the regional control parameters of each dental area can be integrated to obtain the control parameter information for the current sub-cycle.

[0168] This embodiment achieves refined adjustment and intelligent personalized customization of brushing control parameters by extracting regional features from periodic brushing data and comparing them with health standards. Based on this, corresponding control strategy templates are matched according to the risk level of each dental zone and the parameters to be adjusted, generating personalized regional control parameters. These parameters are then integrated into the control parameter information for the current sub-cycle, guiding the actual brushing process and effectively improving the personalization of control parameter information and the reliability of the brushing process.

[0169] In one embodiment, in S204 above, updating the periodic brushing data based on the brushing behavior data collected in the current sub-cycle to generate updated periodic brushing data includes: adding the brushing behavior data collected in the current sub-cycle to the periodic brushing data to generate updated periodic brushing data.

[0170] Adding the brushing behavior data collected in the current sub-cycle to the brushing data of the above cycle means appending the newly collected brushing record to the periodic data set, forming a sliding data window that is updated in time sequence.

[0171] In this embodiment, by appending the brushing behavior data collected in the current sub-cycle to the cycle brushing data without deleting the old brushing behavior data, long-term accumulation and full-cycle tracking of user brushing behavior can be achieved. This helps to carry out trend analysis, personality modeling, historical behavior backtracking and deep optimization of control strategies, thereby improving the intelligence and personalization of the brushing control process.

[0172] Furthermore, in S204 above, updating the periodic brushing data based on the brushing behavior data collected in the current sub-cycle to generate updated periodic brushing data further includes: if the amount of the periodic brushing data exceeds the preset target amount of data, deleting one or more brushing behavior data with the earliest corresponding time in the periodic brushing data, so that the amount of the periodic brushing data is equal to the preset target amount of data.

[0173] The preset target data volume represents the maximum number of data entries allowed to be retained in the periodic brushing data used by the electric toothbrush to control and judge brushing behavior; that is, the upper limit of the number of brushing behavior data records set in advance. Optionally, a data entry can refer to the brushing behavior data collected within a sub-cycle, and the value of the preset target data volume is equal to the value of the sub-cycles included in the reference preset cycle.

[0174] For example, if the number of sub-cycles in the preset cycle is 7, the preset target data volume can be set to 7, which means that the cycle brushing data will only retain brushing behavior data within the most recent 7 sub-cycles.

[0175] In this embodiment of the application, when the number of data entries in the periodic brushing data exceeds the preset target data volume, the earliest one or more data records will be automatically deleted, and only the most recent data records will be retained, so that the data volume of the periodic brushing data is kept equal to the preset target data volume. This can effectively improve the timeliness of brushing behavior data and provide more stable and up-to-date data support for the generation of control parameters.

[0176] This application also provides another method for controlling an electric toothbrush, such as Figure 5 As shown, the above method also includes:

[0177] S501: When the start of the current sub-cycle is detected, the periodic brushing data corresponding to the current sub-cycle is obtained. The periodic brushing data includes brushing behavior data collected within a preset reference cycle before the current sub-cycle.

[0178] Specifically, S501 is the same as S201 above, and will not be repeated here.

[0179] S502: Determine the control parameter information for the current sub-cycle based on the brushing data of the above cycle.

[0180] Specifically, S502 is the same as S202 mentioned above, and will not be repeated here.

[0181] S503: Determine whether the current update count of the brushing data in the above cycle has reached the preset update count threshold; if not, execute S504; if yes, execute S507.

[0182] Each update of the periodic brushing data signifies the completion of a sub-cycle, allowing us to calculate the current update count of the periodic brushing data.

[0183] Optionally, the preset update count can determine the number of sub-cycle data updates allowed within a complete second preset period, and can be flexibly set according to actual needs. For example, the second preset period can be 10 days, and the preset update count can be set to 10, meaning that 10 updates are allowed within one round of the second preset period.

[0184] S504: During the current sub-cycle, control the operation of the electric toothbrush based on the control parameter information, and collect brushing behavior data during the current sub-cycle.

[0185] Specifically, S504 is the same as S203 above, and will not be repeated here.

[0186] S505: In response to the end of the current sub-cycle, update the brushing data of the cycle based on the brushing behavior data collected in the current sub-cycle, generate updated brushing data of the cycle, and determine the start of the next sub-cycle.

[0187] Specifically, S505 is the same as S204 above, and will not be repeated here.

[0188] S506: Take the next sub-cycle as the new current sub-cycle and return to the execution of step S301 above.

[0189] For example, after the current sub-cycle (e.g., the day) ends, the control parameters for the next sub-cycle are determined based on the updated cycle brushing data. Subsequently, this next sub-cycle is used as the new current sub-cycle, and the brushing control process is re-executed. That is, the electric toothbrush is controlled to run based on the control parameters, and a new round of brushing behavior data is collected to achieve periodic cycling and continuous optimization of brushing control.

[0190] The embodiments of this application effectively improve the intelligence, continuity, and personalization of the brushing control process by continuously tracking the user's brushing behavior and automatically updating and personalizing the control strategy.

[0191] S507: When the number of updates reaches the preset update number threshold, the first preset period is determined to start, and the control parameter information is used as the initial control parameter for the first preset period.

[0192] Optionally, reaching the aforementioned preset update threshold can indicate the completion of a second preset cycle update, thereby initiating a new first preset cycle. The current control parameter information can be used as the initial control parameter for the new first preset cycle. This initial control parameter is fixed within the first preset cycle, meaning that the operation of the electric toothbrush is controlled based on this initial control parameter within the first preset cycle and is no longer dynamically adjusted according to daily brushing behavior.

[0193] In another embodiment, if it is determined that the current update count of the brushing data in the above cycle has reached a preset update count threshold, the electric toothbrush can be continuously controlled to run based on the current control parameter information in the subsequent process. Then, after running for a preset duration, the step of determining the start of the next first preset cycle in S507 and using the above control parameter information as the initial control parameter of the next first preset cycle is executed.

[0194] S508: During the first preset period, the electric toothbrush is controlled to operate based on the initial control parameters, and brushing behavior data during the first preset period is collected.

[0195] During the first preset period (e.g., the next 10 days), the control parameters will no longer be updated based on daily brushing behavior. Instead, the initial control parameters will be used to control the electric toothbrush throughout the entire first preset period. At the same time, user brushing behavior data will continue to be collected during the first preset period for subsequent strategy optimization.

[0196] S509: In response to the end of the first preset cycle, start a new current sub-cycle and return to the execution of step S501.

[0197] Optionally, when the first preset cycle ends (i.e., the fixed parameter control period expires), a new current sub-cycle will be started, and the execution of the data-driven control flow (i.e., S501) will be returned to restart the adaptive strategy loop process, thereby realizing the periodic update and optimization of the control strategy.

[0198] This application embodiment constructs a periodic and adaptive intelligent control method for electric toothbrushes by combining a switching mechanism between a fixed control phase and a dynamic control phase, effectively improving the intelligence and personalization of brushing behavior management. Specifically, by setting a first preset period and a second preset period, brushing control is divided into a stable period and an adjustment period: during the first preset period, fixed initial control parameters are used to ensure stable system startup and collection of complete behavioral data; during the second preset period, control parameters are dynamically optimized based on continuously updated periodic brushing data, gradually forming a personalized cleaning strategy that meets the individual needs of the user. This effectively improves the continuous adaptability and long-term health guidance capability of the user's brushing behavior, as well as enhances the self-management and self-optimization capabilities of the electric toothbrush.

[0199] In some embodiments, brushing behavior data from past cycles can also be parsed to generate and display prompts, such as... Figure 6 The above methods also include:

[0200] S601: Based on the above periodic brushing data, determine the cleaning data for each dental area.

[0201] Optionally, the periodic brushing data can be divided into oral cavity regions (dental areas), and basic statistical information related to the cleaning effect can be extracted to form dental area cleaning data.

[0202] Specifically, the dental cleaning data can be consistent with the brushing behavior characteristics mentioned above.

[0203] S602: Analyze the cleaning data of each of the above-mentioned dental areas to obtain the corresponding analysis results for each of the above-mentioned dental areas.

[0204] Optionally, the cleaning data of the dental area can be compared with the preset health standard parameters to obtain the analysis results corresponding to each dental area.

[0205] Specifically, the analysis results for each dental region can be used to indicate potential health problems (such as tooth decay) in that region.

[0206] In one embodiment, in S602, the cleaning data of each dental area is parsed to obtain the corresponding parsing results for each dental area, including: for each dental area, obtaining preset index data of the dental area from the cleaning data of the dental area; determining whether the preset index data meets the corresponding preset compliance conditions; and generating a parsing result indicating that there is a risk of tooth decay in the dental area if the preset index data does not meet the preset compliance conditions.

[0207] The aforementioned preset indicator data can be any one of the following: number of missed brushes, cleaning coverage rate, or cleaning duration. When the preset indicator data is the number of missed brushes, the corresponding preset compliance condition is: the number of missed brushes is less than a preset number threshold. When the preset indicator data is the cleaning coverage rate, the corresponding preset compliance condition is: the cleaning coverage rate is greater than a preset coverage rate threshold. When the preset indicator data is the cleaning duration, the corresponding preset compliance condition is: the cleaning duration is greater than a preset duration threshold.

[0208] Optionally, if any of the preset criteria are not met, an analysis result indicating the risk of tooth decay in the indicator tooth area can be generated.

[0209] In this embodiment, by setting multiple preset index data closely related to brushing effectiveness and comparing them with corresponding achievement conditions, a quantitative assessment of the cleaning status of each dental area is achieved. When any index fails to meet the standard, an analytical result indicating the risk of tooth decay in the indicated dental area is generated, thereby enabling early identification of potential oral health problems. This method has high sensitivity and good generalization ability, effectively reducing the risk of tooth decay caused by missed brushing or insufficient cleaning. It also provides a more reliable basis for subsequent personalized prompts and parameter adjustments, improving the practicality and intelligence of smart electric toothbrushes in preventive oral care.

[0210] In one embodiment, dynamic scoring can also be performed based on the compliance status of each dental area. Specifically, each dental area can correspond to a dynamic score value, which can be used to reflect the cleaning performance trend of the corresponding dental area within a preset reference period. This score value can be updated as brushing behavior changes within sub-cycles, thereby achieving continuous quantitative evaluation of the cleaning performance of each dental area.

[0211] For example, at the end of each sub-cycle, preset indicator data for each dental region are evaluated. If the preset indicator data meets the corresponding preset achievement conditions, a score is added to the dynamic score of that dental region (e.g., the score increases by 1 for each preset achievement condition met); if the indicator data does not meet the corresponding preset achievement conditions, a score is deducted from the dynamic score of that dental region (e.g., the score decreases by 1 for each preset indicator data that does not meet a preset achievement condition). The specific addition and subtraction values ​​can be flexibly configured according to actual needs. For example, the addition or subtraction range for each operation can be set to 0.5, 1, or other values ​​to adapt to different users or the importance of different dental regions.

[0212] It should be noted that the aforementioned dynamic scoring values ​​can be not only a comprehensive score based on multiple preset indicator data for each dental area, but also refined into individual scores corresponding to each preset indicator data. That is, the scoring value for each preset indicator is recorded independently and dynamically updated to reflect the changing trend of dental cleaning performance under the corresponding dimension.

[0213] For example, if a tooth area fails to meet the preset brushing time criteria for several consecutive sub-cycles, the corresponding cleaning time score will gradually decrease, while the cleaning coverage score will increase if the cleaning coverage consistently meets the preset criteria. Thus, through this multi-dimensional scoring system, a refined assessment of the cleaning status of tooth areas can be achieved, providing users with more targeted problem identification and improvement suggestions, further enhancing the personalized brushing experience of electric toothbrushes.

[0214] Furthermore, dynamic ratings can be visualized on the user terminal or the display screen on the electric toothbrush, allowing users to intuitively understand the long-term performance trend of cleaning effects in each dental area.

[0215] In this embodiment of the application, by setting a dynamic scoring mechanism for each tooth area, the cleaning performance of the tooth area can be continuously and quantitatively evaluated across multiple sub-cycle dimensions. This allows users to not only understand whether brushing in a certain sub-cycle meets the standards, but also to grasp the overall improvement or regression of the cleaning of the tooth area within a preset reference cycle. This helps users discover long-standing cleaning blind spots or behavioral problems, effectively improving the user experience and intelligence level of the electric toothbrush.

[0216] In one embodiment, if the preset index data does not meet the preset compliance conditions, the method further includes: generating marking information for the tooth region for the preset index data that does not meet the preset compliance conditions.

[0217] The labeling information is a structured identifier generated for a tooth region when a non-compliance is identified during the analysis of tooth region cleaning data. This identifier is used as input information for the parameter adjustment model to drive the model to perform control parameter enhancement processing on the tooth region corresponding to the labeling information.

[0218] Furthermore, the process of determining the control parameter information for the current sub-cycle based on the aforementioned periodic brushing data includes: performing parameter generation processing on the aforementioned periodic brushing data and the aforementioned marking information based on a preset parameter adjustment model to obtain the control parameter information for the current sub-cycle.

[0219] Optionally, the parameter tuning model can be a rule engine or model component used to automatically generate personalized control parameter information based on periodic brushing data and labeling information. Specifically, it can be a preset rule model, a weighted linear model, or a prediction module based on machine learning (such as a lightweight decision tree / neural network). The parameter tuning model can receive periodic brushing data and labeling information as input and then output the corresponding control parameter information.

[0220] Specifically, based on a preset parameter adjustment model, the aforementioned periodic brushing data and the aforementioned labeling information are input into the parameter adjustment model to perform parameter generation processing. The aforementioned labeling information is used to drive the model to enhance control strategies for the corresponding tooth areas, such as by extending cleaning time, increasing cleaning intensity, and increasing reminder frequency, to generate more targeted control parameters, thereby achieving refined intervention in the user's brushing behavior and personalized management of high-risk tooth areas.

[0221] S603: Based on the analysis results of each of the above-mentioned dental regions, generate the first prompt information corresponding to each of the above-mentioned dental regions.

[0222] The first notification message can be used to alert a user to a potential health problem in a certain dental area.

[0223] For example, if the analysis results for a tooth area indicate that the number of missed brushing attempts is not less than a preset threshold, the cleaning coverage is not greater than a preset coverage threshold, or the cleaning time is not greater than a preset time threshold, it can be inferred that there is a risk of inadequate cleaning in that tooth area. This could lead to plaque buildup or tartar residue, which in turn could induce dental caries and other health problems. In this case, the first prompt message can include information to alert the tooth area to the risk of dental caries, such as "Insufficient cleaning of the lower right posterior teeth poses a risk of dental caries; please strengthen cleaning."

[0224] S604: Display the first prompt message mentioned above.

[0225] Optionally, the first prompt message can be displayed in ways such as graphical highlighting, text reminder, voice broadcast, etc., to guide the user to strengthen the cleaning of the corresponding tooth area or adjust the brushing method during the subsequent brushing process, so as to prevent and intervene in potential health problems.

[0226] In some embodiments, in S604, the display of the first prompt message includes: displaying the first prompt message through the user terminal; and / or, displaying the first prompt message through the display screen of the electric toothbrush.

[0227] By structurally analyzing the periodic brushing data, combining health standard parameters and parameter adjustment models, the embodiments of the present application achieve the evaluation of the cleaning quality of tooth areas, risk identification, and personalized prompt feedback, effectively improving the intelligent control and user interaction capabilities of electric toothbrushes. This method not only supports quantitatively judging the cleaning situation of the user in each tooth area from key indicators such as the number of missed brushing times, cleaning coverage rate, and cleaning duration, but also drives the parameter adjustment model to formulate differentiated control strategies for tooth areas with problems by generating analysis results and marking information, thereby enhancing the brushing intervention intensity for potential problem tooth areas.

[0228] In addition, by generating targeted first prompt messages and providing visual or auditory prompt feedback, it can effectively guide the user to actively improve their behavior during the subsequent brushing process, reduce the oral health risks caused by insufficient brushing, and contribute to personalized caries prevention and early intervention.

[0229] In some embodiments, it is also possible to compare and analyze the periodic brushing data corresponding to two consecutive preset cycles, such as Figure 7 , the method further includes:

[0230] S701: In response to the end of the current sub-cycle, determine whether the second preset cycle to which the current sub-cycle belongs has ended.

[0231] Optionally, after each sub-cycle ends, it can be determined whether the second preset cycle to which the current belongs has reached the set cycle boundary conditions according to time information (such as the current date, the cumulative number of sub-cycles, etc.), such as the cycle days are full, the cumulative number of sub-cycles reaches the upper limit, etc. When it is determined that the current sub-cycle is the last sub-cycle of the second preset cycle, it is determined that the second preset cycle to which the current sub-cycle belongs has ended; when it is determined that the current sub-cycle is not the last sub-cycle of the second preset cycle, it is determined that the second preset cycle to which the current sub-cycle belongs has not ended.

[0232] S702: In the case where the second preset cycle ends, generate the current periodic brushing data corresponding to the second preset cycle.

[0233] The brushing data for the current cycle corresponding to the second preset cycle can be the brushing behavior data collected in each sub-cycle within the second preset cycle.

[0234] In one embodiment, if the second preset period has not ended, the next sub-cycle within the current second preset period can continue to begin.

[0235] S703: Obtain the brushing data of the previous historical preset cycle corresponding to the second preset cycle.

[0236] Optionally, the preceding historical preset period can be either the previous second preset period or the first preset period preceding the second preset period. The specific preceding historical preset period depends on the specific stage of the second preset period.

[0237] For example, taking a first preset period and a second preset period both of 7 days as an example, in one embodiment, the second preset period can be the current third preset period (i.e., day 15 to day 21), and the previous historical preset period is the second second preset period (i.e., day 8 to day 14). In another embodiment, the second preset period can be the current second preset period (i.e., day 8 to day 14), and the previous historical preset period is the first preset period, i.e., the first preset period (i.e., day 1 to day 7).

[0238] S704: Compare the brushing data of the current cycle with the brushing data of the historical cycles to obtain the first comparison result.

[0239] Optionally, brushing data from the current cycle can be compared with brushing data from historical cycles, segmented by tooth area, to identify differences or trends in brushing behavior within two adjacent preset cycles, thereby obtaining comparison results. Comparison methods may include, but are not limited to: numerical comparison (e.g., average cleaning time increased by 15 seconds, average coverage decreased by 5%), state difference judgment (e.g., no missed brushing occurred in the historical preset cycle, but missed brushing occurs in the current second preset cycle), statistical trend analysis (e.g., reduced intensity fluctuations, more stable cleaning), and risk level change analysis (e.g., a tooth area was assessed as medium risk in the historical preset cycle, but is assessed as good in the current second preset cycle).

[0240] S705: Generate a second prompt message based on the first comparison result. The second prompt message is used to prompt the user about the changing trend of brushing behavior data within adjacent preset periods.

[0241] Optionally, the second prompt message can be used to provide feedback on changes in the user's brushing habits, praise improved behavior, or indicate regression or risk of a rebound. For example, the second prompt message could be: "Brushing was more even this cycle than last cycle, with an average cleaning coverage increase of 5%, keep it up!" or "A decrease in average cleaning time was detected this cycle, and the lower left molars were not cleaned properly, please extend the brushing time appropriately."

[0242] It is understandable that adjacent preset cycles can be one adjacent first preset cycle and one adjacent second preset cycle, or two adjacent second preset cycles.

[0243] S706: Display the second prompt message mentioned above.

[0244] Optionally, the second prompt information may be displayed in the following ways, including but not limited to: text pop-ups (such as dialog boxes appearing in the APP); graphic annotations (such as highlighting the changed area in the dental area diagram); voice broadcast; calendar / trend charts (showing the change trajectory of several consecutive preset periods), etc.

[0245] In this embodiment, by automatically triggering cross-cycle behavioral data comparison and trend analysis at the end of each second preset cycle, a second prompt message is generated for changes in the user's brushing habits, thereby realizing a cycle-level intelligent feedback mechanism. This mechanism not only supports longitudinal trend evaluation of multi-dimensional features such as cleaning time, coverage, and brushing force, but also identifies specific dental areas where behavior has improved or regressed, and provides personalized feedback through diverse prompting methods. This helps enhance the user's self-awareness of brushing behavior and their willingness to actively adjust, significantly improving the intelligence and continuity of the electric toothbrush in the process of user behavior intervention and health management.

[0246] In some embodiments, when the first preset period or the second preset period has ended, a prediction can also be made for the next second preset period. The above method further includes:

[0247] When the first or second preset period is detected to have ended, a preset number of brushing behavior data points within a preset historical time period are obtained, and a prediction result is generated based on the preset number of brushing behavior data points.

[0248] One brushing behavior data point can refer to brushing behavior data collected within a sub-cycle. The aforementioned preset historical time period can be a continuous range of several days prior to the current time, such as the past 7, 14, or 21 days, which can be dynamically set according to actual needs. The preset number can be an integer greater than 0, and the preset number of brushing behavior data points can be brushing behavior data collected within the preset number of sub-cycles corresponding to the preset historical time period. These can be brushing behavior data collected in consecutive sub-cycles in chronological order, or non-consecutive sub-cycle data filtered according to set rules.

[0249] Optionally, the prediction results can be used to characterize the brushing behavior trends, potential risk areas, or control parameter change trends that users may exhibit in the next second preset period.

[0250] Specifically, the above prediction results may include at least one of the following: the expected cleaning coverage trend (e.g., the coverage of a certain dental area may continue to decline), the expected cleaning time trend (e.g., the user's overall brushing time may decrease), the expected changes in brushing force (e.g., the area of ​​excessive pressure continues to expand), or the expected changes in the risk level of certain dental areas (e.g., there is a continuous trend of missed brushing in a certain dental area, and the risk level may rise from medium risk to high risk).

[0251] For example, when the end of the second preset period is detected, seven brushing behavior data points from seven consecutive sub-cycles within a preset historical time period (such as the past seven days) are obtained. Based on these seven brushing behavior data points, a prediction result is generated. This prediction result can reflect the brushing behavior trend, potential risk areas, or control parameter change trends that the user may exhibit in the next second preset period.

[0252] In one embodiment, preset rules can be used to analyze a preset number of brushing behavior data points and generate prediction results. For example, if the cleaning coverage of a certain dental area is less than 80% in the past seven consecutive sub-cycles, it is predicted that the dental area is at risk of continuous missed brushing in the next second preset cycle. Rule-based judgment triggers corresponding risk warnings and parameter adjustment strategies to achieve rapid and interpretable prediction.

[0253] In another embodiment, a brushing behavior prediction model can be constructed, such as one based on decision trees, random forests, or lightweight neural network models, to learn from brushing data samples from multiple sub-cycles in the user's history. The model input includes features such as cleaning time, coverage, and brushing force for each tooth area, and the output prediction results are the coverage rate or risk level prediction values ​​for each tooth area in the next preset cycle. Based on the model's prediction results, potential risk areas can be identified in advance, and personalized control suggestions can be generated.

[0254] Furthermore, based on the above prediction results, corresponding third prompt information can be generated. The third prompt information is used to show users in advance the possible brushing behavior trends, potential risk areas, or control parameter change directions in the next second preset cycle, so that users can know in advance and optimize their brushing habits.

[0255] Optionally, the third prompt can be displayed in the form of text reminders, graphic highlights, or APP voice broadcasts to enhance users' sense of active participation and awareness of behavior improvement.

[0256] In this embodiment, by introducing comparative analysis and trend prediction of brushing behavior, a more intelligent and personalized brushing strategy control scheme can be achieved, which effectively improves the cleaning efficiency of electric toothbrushes and the level of oral health management.

[0257] Furthermore, based on this prediction result, suggested control parameters suitable for the next second preset cycle are generated in advance and used as reference information at the start of the next second preset cycle. These parameters are then combined with the brushing data from the current cycle to generate control parameters for sub-cycles within the next second preset cycle. This not only improves the responsiveness of sub-cycle control parameters but also dynamically optimizes the control parameters based on the user's brushing behavior trends, achieving a more intelligent and personalized brushing control effect.

[0258] In some embodiments, comparative analysis can also be performed on brushing data corresponding to two consecutive sub-cycles. After obtaining the brushing data corresponding to the current sub-cycle, the method further includes: obtaining historical brushing data corresponding to the previous sub-cycle of the current sub-cycle. The brushing data corresponding to the current sub-cycle and the historical brushing data are compared to obtain a second comparison result. A fourth prompt message is generated based on the second comparison result. The fourth prompt message is used to prompt the user about the changing trend of brushing behavior data in two adjacent sub-cycles. The fourth prompt message is then displayed.

[0259] The previous sub-cycle can be the most recent sub-cycle before the start of the current sub-cycle (such as yesterday). Historical brushing data includes brushing behavior data collected within the preset reference cycle corresponding to the previous sub-cycle.

[0260] Optionally, historical brushing data can come from one or more sources, such as the electric toothbrush's local cache, cloud synchronization records, or brushing logs from the app.

[0261] Optionally, the brushing data of the current sub-cycle can be compared item by item with the historical brushing data of the previous sub-cycle, segmented by tooth area, to identify differences or trend changes in brushing behavior and obtain comparison results. The comparison methods may include, but are not limited to: numerical comparison (e.g., cleaning time increased by 15 seconds, coverage decreased by 5%), judgment of state differences (e.g., no missed brushing yesterday, missed brushing today), statistical trend analysis (e.g., reduced fluctuation in brushing force, more stable cleaning), and risk level change analysis (e.g., medium risk in the previous cycle, good risk in this cycle).

[0262] Optionally, the fourth prompt message can be used to provide feedback on changes in the user's brushing habits, praise improved behavior, and indicate regression or risk of rebound. For example, the fourth prompt message could be: "This brushing was more even than last time, with a 5% improvement in cleaning coverage. Keep it up!", "A reduction in cycle cleaning time was detected, and the lower left molars were not cleaned thoroughly. Please extend the brushing time appropriately," or "Compared to yesterday, the cleaning quality of the right anterior teeth has decreased, and there is a risk of missing any teeth."

[0263] Optionally, the display methods for the fourth prompt information may include, but are not limited to: text pop-ups (such as dialog boxes appearing in the APP); graphic annotations (such as highlighting the changed areas in the dental area diagram); voice broadcasts; calendars / trend charts (showing the change trajectory over several consecutive days), etc.

[0264] This application's embodiments introduce a comparative analysis mechanism for brushing data between the current and previous sub-cycles, enabling trend tracking and real-time feedback on changes in user brushing behavior. This further enhances the interactive intelligence and behavioral guidance capabilities of the electric toothbrush. By comparing current cycle brushing data with historical cycle data item by item, it can precisely identify specific changes in cleaning duration, coverage, cleaning intensity, and missed brushing areas, forming trend-based and differentiated comparison results and generating corresponding prompts. This allows for timely alerts to signs of regression or potential health risks, thus constructing a dynamic feedback and self-correction mechanism. This helps enhance users' perception of their brushing quality and their willingness to manage it autonomously, effectively improving the reliability and comprehensiveness of electric toothbrush use.

[0265] In some embodiments, the method further includes: generating single brushing behavior data generated by the brushing behavior when the completion of any brushing behavior within the current sub-cycle is detected; generating a corresponding single brushing behavior evaluation report based on the single brushing behavior data; and / or generating a periodic brushing behavior evaluation report based on the single brushing behavior data and the periodic brushing data; and displaying the single brushing behavior evaluation report and / or the periodic brushing behavior evaluation report.

[0266] Optionally, each time a user completes a brushing session (from power-on to power-off), sensor data related to that brushing session can be collected, such as brushing duration, brushing pressure, coverage area, whether there were any missed areas, and whether horizontal brushing occurred. This data is then integrated into a structured record as single-session brushing behavior data. Subsequently, this single-session brushing behavior data can be analyzed to generate a single-session brushing behavior evaluation report. This report reflects whether the brushing behavior met the preset cleaning standards and whether there were any issues such as excessive brushing force or improper brushing posture. Additionally, a periodic brushing behavior evaluation report can be generated by combining the single-session brushing behavior data with the periodic brushing data corresponding to the current sub-cycle (such as periodic brushing data from the past 7 days). Furthermore, the single-session brushing behavior evaluation report and / or the aforementioned periodic brushing behavior evaluation report can be displayed on the electric toothbrush screen and / or the user terminal.

[0267] Specifically, the single brushing behavior assessment report and the aforementioned periodic brushing behavior assessment report can be displayed sequentially in an automatic page carousel, so that users can quickly obtain immediate feedback on their brushing behavior after a brushing session, and understand their overall brushing performance within the period, which helps to improve their perception of brushing effectiveness and awareness of behavior improvement.

[0268] In some embodiments, the method further includes: acquiring an initial oral cavity model, and acquiring the user's oral health problem information and / or brushing habit information; determining a first potential health problem corresponding to each dental area based on the oral health problem information and / or the brushing habit information; determining a second potential health problem corresponding to each dental area based on the periodic brushing data; labeling the initial oral cavity model based on the first and second potential health problems to generate a target oral cavity model, wherein different types of potential health problems correspond to different labels; and displaying the target oral cavity model.

[0269] The initial oral cavity model can be a 3D oral cavity structure diagram provided during the user's initial setup, or a dental region division diagram generated based on a scan / preset template, used as the basis for subsequent labeling operations. This initial oral cavity model includes the spatial structure and numbering information of multiple dental regions.

[0270] Optionally, the first potential health issue can be identified by analyzing the oral health information and / or brushing habits provided by the user, revealing potential risks or areas of focus for each tooth region. For example, if the user has a habit of brushing horizontally on the upper right posterior teeth, there may be a risk of enamel wear in that area. The second potential health issue can be objectively identified by using brushing behavior data collected from an electric toothbrush, such as insufficient cleaning, missed brushing times, or abnormal brushing pressure.

[0271] Furthermore, combining the first and second potential health issues, the potential problems corresponding to each dental area are marked on the initial oral model. Different types of problems are distinguished using different colors, icons, or textures to enhance recognizability. The final target oral model is presented to the user in a graphical interface, allowing the user to intuitively understand the distribution of their own oral health potential risks, which helps guide them to improve their brushing habits and focus on key dental areas.

[0272] Optionally, the aforementioned target oral model can be displayed on a user terminal in the form of 3D interactive diagrams, zonal diagrams, heat maps, etc., and users can rotate to view the status of each tooth area, click to obtain corresponding risk descriptions and improvement suggestions, thereby enhancing the user's feedback experience in brushing behavior and awareness of oral health management.

[0273] This embodiment combines user-defined oral health information, brushing habits, and periodic brushing data to identify the first and second potential health problems in each dental area. These are then visually marked on an initial oral model, generating a target oral model which is displayed to the user. This provides personalized prompts and an intuitive presentation of oral risk areas. Consequently, it effectively improves users' awareness of their own oral health and enhances the accuracy of brushing guidance provided by electric toothbrushes.

[0274] In one embodiment, after obtaining the periodic brushing data corresponding to the current sub-cycle, the method further includes: displaying the periodic brushing data through a terminal device.

[0275] Please see Figure 8 , Figure 8 This is a schematic diagram of a periodic brushing data display page provided as an exemplary embodiment of this application. Figure 8The periodic brushing data display page 800 shown can be a display interface in an application that matches the aforementioned electric toothbrush, or it can be a corresponding functional component page within that application. It is used to display statistical information on brushing behavior within a certain period, trends in various indicators, and the cleaning status of corresponding dental areas. Specifically, the periodic brushing data display page 800 can include multiple information display areas. For example, display area 801 presents the total number of brushings (e.g., a total of 12 times) within the second preset period (e.g., one week) to which the current sub-period belongs, and displays the brushing frequency by sub-period to help users understand the regularity and coverage frequency of brushing. Display area 802 displays the average cleaning time (e.g., an average of 2 minutes and 30 seconds) within the second preset period (e.g., one week) to which the current sub-period belongs, and uses a daily cleaning time bar chart to indicate whether the user's brushing time is insufficient. Display area 803 statistically displays the average tooth cleaning coverage rate (e.g., an average of 87%) within the second preset period (e.g., one week) to which the current sub-period belongs, and displays a related bar chart. In display area 804, an oral cavity diagram shows the number of missed brushing sessions in each tooth area within the second preset cycle (e.g., one week) of the current sub-cycle. This helps users identify weak points in cleaning specific tooth areas. Alternatively, the diagram can display dynamic score values ​​for each tooth area to quantify cleaning performance trends, further enhancing users' awareness of brushing effectiveness and motivation to improve. Display area 805 shows the cumulative over-pressure time caused by excessive brushing force in the current cycle (e.g., 24 seconds of cumulative over-pressure this week) to remind users to avoid gum damage caused by excessive brushing. Display area 806 displays the cumulative duration of horizontal brushing behavior within the second preset cycle (e.g., one week) of the current sub-cycle (e.g., an average of 12 seconds of horizontal brushing this week) to alert users to any improper horizontal brushing behavior. Display area 807 displays the plaque residue on the tooth surface within the second preset cycle (e.g., one week) of the current sub-cycle. This data can come from the electric toothbrush's integrated visual detection function or third-party testing equipment.

[0276] In this embodiment, the periodic brushing data display page 800 allows users to intuitively understand the overall picture of their brushing habits, behavioral changes, and cleaning quality within a second preset period. This facilitates the timely detection of potential oral health problems and enables self-management or optimization of brushing plans, thereby achieving personalized, data-driven intelligent brushing guidance.

[0277] Please refer to the following. Figure 9 This is a schematic diagram of the structure of a control device for an electric toothbrush provided in an exemplary embodiment of this application. Figure 9 As shown, the control device 900 for the electric toothbrush includes:

[0278] The first acquisition module 901 is used to acquire the periodic brushing data corresponding to the current sub-cycle when the start of the current sub-cycle is detected. The periodic brushing data includes brushing behavior data collected within a preset reference cycle before the current sub-cycle.

[0279] The first determining module 902 is used to determine the control parameter information of the current sub-cycle based on the brushing data of the above cycle.

[0280] The first control module 903 is used to control the operation of the electric toothbrush based on the control parameter information during the current sub-cycle, and to collect brushing behavior data during the current sub-cycle.

[0281] The update module 904 is used to update the brushing data of the cycle based on the brushing behavior data collected in the current sub-cycle in response to the end of the current sub-cycle, generate updated brushing data of the cycle, determine the start of the next sub-cycle, and determine the control parameter information of the next sub-cycle based on the updated brushing data of the cycle.

[0282] In one possible implementation, the update module 904 mentioned above includes:

[0283] The loop unit is used to take the next sub-cycle as the new current sub-cycle and return to execute the steps of obtaining the cycle brushing data corresponding to the current sub-cycle when the start of the current sub-cycle is detected, and determining the control parameter information of the current sub-cycle based on the cycle brushing data.

[0284] In one possible implementation, after determining the control parameter information for the current sub-cycle based on the aforementioned periodic brushing data, the control device 900 further includes:

[0285] The first judgment module is used to determine whether the current update count of the brushing data in the above periodic period has reached the preset update count threshold.

[0286] The first execution module is used to determine, when the number of updates has not reached the preset update number threshold, to execute the steps of controlling the electric toothbrush to operate based on the control parameter information and collecting brushing behavior data within the current sub-cycle.

[0287] In one possible implementation, the control device 900 further includes:

[0288] The second determining module is used to determine the start of the first preset period when the number of updates reaches the preset number of updates threshold, and to use the control parameter information as the initial control parameter of the first preset period.

[0289] The second control module is used to control the operation of the electric toothbrush based on the initial control parameters within the first preset period, and to collect brushing behavior data within the first preset period.

[0290] The loop module is used to respond to the end of the first preset cycle, start a new current sub-cycle, and return to execute the steps of obtaining the cycle brushing data corresponding to the current sub-cycle when the start of the current sub-cycle is detected.

[0291] In one possible implementation, the update module 904 mentioned above includes:

[0292] The addition unit is used to add the brushing behavior data collected in the current sub-cycle to the brushing data of the cycle, and generate updated brushing data of the cycle.

[0293] In one possible implementation, the update module 904 mentioned above includes:

[0294] The deletion unit is used to delete one or more brushing behavior data with the earliest corresponding time in the above-mentioned periodic brushing data when the data volume of the above-mentioned periodic brushing data exceeds the preset target data volume, so that the data volume of the above-mentioned periodic brushing data is equal to the preset target data volume.

[0295] In one possible implementation, the control device 900 further includes:

[0296] The second acquisition module is used to acquire preset initial control parameters when the electric toothbrush is detected to be in the initialization state.

[0297] The third control module is used to control the operation of the electric toothbrush based on the initial control parameters within the first preset period, and to collect brushing behavior data within the first preset period.

[0298] The second execution module is used to respond to the end of the first preset cycle, start the current sub-cycle, and use the brushing behavior data collected in the first preset cycle as the brushing behavior data collected in the preset reference cycle before the current sub-cycle, and execute the above steps of obtaining the cycle brushing data corresponding to the current sub-cycle.

[0299] In one possible implementation, the second acquisition module described above includes:

[0300] The first acquisition unit is used to acquire information about the user's oral health problems and / or brushing habits.

[0301] The first determining unit is used to determine the preset initial control parameters based on the oral health information and / or brushing habits information.

[0302] In one possible implementation, the first acquisition unit includes:

[0303] The acquisition subunit acquires the oral health problem information and / or brushing behavior preference information determined by the user through the user terminal; and / or,

[0304] The identification unit is used to perform oral cavity detection on the user using the electric toothbrush, and to identify the user's oral cavity problem information and / or brushing habit information.

[0305] In one possible implementation, the first determining module 902 includes:

[0306] The first generation unit is used to perform parameter generation processing on the aforementioned periodic brushing data using the first preset model local to the electric toothbrush, to obtain the control parameter information for the current sub-cycle; or...

[0307] The aforementioned periodic brushing data is sent to the server, where a second preset model deployed on the server performs parameter generation processing on the periodic brushing data to obtain the control parameter information for the current sub-cycle, and receives the control parameter information returned by the server.

[0308] In one possible implementation, the first determining module 902 includes:

[0309] The extraction unit is used to extract features from the above periodic brushing data to obtain brushing behavior feature values ​​corresponding to each tooth area.

[0310] The analysis unit is used to compare and analyze the above brushing behavior characteristic values ​​with preset health standard parameters to determine the risk level of each tooth area and the parameters to be adjusted.

[0311] The second determining unit is used to determine the regional control parameters of each of the above-mentioned dental areas based on the risk level of each dental area and the parameters to be adjusted.

[0312] The third determining unit is used to use the regional control parameters of each of the above-mentioned dental areas as the control parameter information of the current sub-cycle.

[0313] In one possible implementation, the control device 900 further includes:

[0314] The third determination module is used to determine the cleaning data of each dental area based on the above-mentioned periodic brushing data;

[0315] The parsing module is used to parse the cleaning data of each of the above-mentioned dental areas and obtain the corresponding parsing results for each of the above-mentioned dental areas;

[0316] The first generation module is used to generate the first prompt information corresponding to the above-mentioned tooth regions based on the analysis results of each tooth region.

[0317] The first display module is used to display the aforementioned first prompt information.

[0318] In one possible implementation, the above-mentioned parsing module includes:

[0319] The second acquisition unit is used to acquire preset index data of the tooth area from the tooth area cleaning data of the tooth area.

[0320] The judgment unit is used to determine whether the above preset indicator data meets the corresponding preset compliance conditions.

[0321] The second generation unit is used to generate an analysis result indicating the risk of tooth decay in the aforementioned dental area when the aforementioned preset index data does not meet the aforementioned preset compliance conditions.

[0322] In one possible implementation, the aforementioned preset indicator data can be any of the following: number of missed brushes, cleaning coverage, and cleaning duration;

[0323] When the above-mentioned preset indicator data is the above-mentioned number of missed refreshes, the corresponding preset compliance condition is: the above-mentioned number of missed refreshes is less than the preset number threshold.

[0324] When the preset indicator data is the above-mentioned cleaning coverage rate, the corresponding preset compliance condition is: the above-mentioned cleaning coverage rate is greater than the preset coverage rate threshold.

[0325] When the preset indicator data is the above-mentioned cleaning time, the corresponding preset compliance condition is: the above-mentioned cleaning time is greater than the preset time threshold.

[0326] In one possible implementation, if the preset indicator data does not meet the preset compliance conditions, the control device 900 further includes:

[0327] The second generation module is used to generate the marking information of the above-mentioned dental area for preset index data that do not meet the above-mentioned preset compliance conditions;

[0328] The aforementioned first determining module 902 includes:

[0329] The fourth determining unit is used to perform parameter generation processing on the above-mentioned periodic brushing data and the above-mentioned marking information based on a preset parameter adjustment model, so as to obtain the control parameter information of the current sub-cycle. The above-mentioned marking information is used as input information of the above-mentioned parameter adjustment model to drive the above-mentioned parameter adjustment model to perform control parameter enhancement processing on the tooth area corresponding to the above-mentioned marking information.

[0330] In one possible implementation, the first display module mentioned above includes:

[0331] The first display unit is used to display the aforementioned first prompt information via a user terminal; and / or,

[0332] The second display unit is used to display the first prompt information on the display screen of the electric toothbrush.

[0333] In one possible implementation, the control device 900 further includes:

[0334] The second judgment module is used to determine whether the second preset period to which the current sub-period belongs has ended in response to the end of the current sub-period.

[0335] The third generation module is used to generate brushing data for the current cycle corresponding to the second preset cycle when the second preset cycle ends.

[0336] The third acquisition module is used to acquire the brushing data of the previous historical preset cycle corresponding to the second preset cycle mentioned above.

[0337] The comparison module is used to compare the current cycle brushing data and the historical cycle brushing data to obtain the first comparison result;

[0338] The fourth generation module is used to generate a second prompt message based on the first comparison result. The second prompt message is used to prompt the user about the changing trend of brushing behavior data within adjacent preset periods.

[0339] The second display module is used to display the aforementioned second prompt information.

[0340] In one possible implementation, the aforementioned periodic brushing data includes at least one of the following: brushing frequency information, cleaning duration information, cleaning coverage information, missed brushing record information, brushing force information, and horizontal brushing record information within the aforementioned preset reference period.

[0341] In one possible implementation, the aforementioned control parameter information includes at least one of the following: brushing force parameter, cleaning duration parameter, vibration frequency parameter, and cleaning mode parameter.

[0342] In one possible implementation, the control device 900 further includes:

[0343] The fifth generation module is used to generate single brushing behavior data generated by the brushing behavior when the completion of any brushing behavior within the current sub-cycle is detected.

[0344] The sixth generation module is used to generate a corresponding single brushing behavior assessment report based on the above single brushing behavior data; and / or, to generate a periodic brushing behavior assessment report based on the above single brushing behavior data and the above periodic brushing data.

[0345] The third display module is used to display the above-mentioned single brushing behavior assessment report and / or the above-mentioned periodic brushing behavior assessment report.

[0346] In one possible implementation, the control device 900 further includes:

[0347] The fourth acquisition module is used to acquire the initial oral cavity model, as well as information on the user's oral health issues and / or brushing habits.

[0348] The fourth determination module is used to determine the first potential health problem corresponding to each dental area based on the above-mentioned oral health problem information and / or the above-mentioned brushing behavior habit information;

[0349] The fifth determination module is used to determine the second potential health problem corresponding to each of the above-mentioned dental areas based on the above-mentioned periodic brushing data;

[0350] The seventh generation module is used to label the initial oral cavity model based on the first potential health problem and the second potential health problem to generate a target oral cavity model, wherein different types of potential health problems correspond to different labels;

[0351] The fourth display module is used to display the target oral cavity model mentioned above.

[0352] The division of modules in the control device 900 for the electric toothbrush described above is for illustrative purposes only. In other embodiments, the control device for the electric toothbrush can be divided into different modules as needed to complete all or part of the functions of the control device. The implementation of each module in the control device for the electric toothbrush provided in the embodiments of this specification can be in the form of a computer program. This computer program can run on a terminal or server. The program modules constituted by this computer program can be stored in the memory of the terminal or server. When the computer program is executed by a processor, it implements all or part of the steps of the control method for the electric toothbrush described in the embodiments of this specification.

[0353] Please refer to the following. Figure 10 This is a schematic diagram of the structure of an electric toothbrush provided in an exemplary embodiment of this application. Figure 10 As shown, the electric toothbrush 1000 may include a processor 1010 and a memory 1020, and may also include a user interface 1030, a network interface 1040 and a communication bus 1050.

[0354] The processor 1010 may include one or more processing cores. The processor 1010 connects to various parts within the electric toothbrush 1000 using various interfaces and lines. It executes various functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in the memory 1020, and by calling data stored in the memory 1020. Optionally, the processor 1010 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 1010 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system and applications; the GPU is responsible for rendering and drawing the content to be displayed on the screen; and the modem handles wireless communication. It is understood that the modem may also be implemented as a separate chip without being integrated into the processor 1010.

[0355] The memory 1020 may include random access memory (RAM) or read-only memory. Optionally, the memory 1020 may include a non-transitory computer-readable storage medium. The memory 1020 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 1020 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as receiving functions, control functions, etc.), instructions for implementing the various method embodiments described above, etc.; the data storage area may store data involved in the various method embodiments described above, etc. Optionally, the memory 1020 may also be at least one storage device located remotely from the aforementioned processor 1010. Figure 10 As shown, the memory 1020, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and program instructions.

[0356] Optionally, the communication bus 1050 is used to realize the connection and communication between these components. The user interface 1030 may include a display screen, a camera, and may also include standard wired interfaces and wireless interfaces. The network interface 1040 may optionally include standard wired interfaces and wireless interfaces (such as Wi-Fi interfaces).

[0357] exist Figure 10 In the electric toothbrush 1000 shown, the processor 1010 can be used to call program instructions stored in the memory 1020 and specifically execute the steps of any of the electric toothbrush control methods provided in the embodiments of this application.

[0358] This application also provides a computer-readable storage medium storing instructions that, when executed on a computer or processor, cause the computer or processor to perform one or more steps in the above embodiments. If the constituent modules of the control device for the electric toothbrush described above are implemented as software functional units and sold or used as independent products, they can be stored in the aforementioned computer-readable storage medium.

[0359] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions. When these computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in or transmitted through a computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium accessible to a computer or a data storage device such as a server or data center that integrates one or more available media. The aforementioned available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., digital versatile discs (DVDs)), or semiconductor media (e.g., solid-state drives (SSDs)).

[0360] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. The aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks. Unless otherwise specified, the technical features of this embodiment and its implementation can be combined arbitrarily.

[0361] The above-described embodiments are merely preferred embodiments of this application and are not intended to limit the scope of this application. Any modifications and improvements made by those skilled in the art to the technical solutions of this application without departing from the spirit of this application should fall within the protection scope defined by the claims of this application.

Claims

1. A control method for an electric toothbrush, characterized in that, The method includes: When the start of the current sub-cycle is detected, the periodic brushing data corresponding to the current sub-cycle is obtained. The periodic brushing data includes brushing behavior data collected within a preset reference cycle before the current sub-cycle. The control parameter information for the current sub-cycle is determined based on the brushing data of the cycle. Within the current sub-cycle, the electric toothbrush is controlled to operate based on the control parameter information, and brushing behavior data within the current sub-cycle is collected; In response to the end of the current sub-cycle, the periodic brushing data is updated based on the brushing behavior data collected during the current sub-cycle, generating updated periodic brushing data, and the start of the next sub-cycle is determined. The control parameter information for the next sub-cycle is then determined based on the updated periodic brushing data.

2. The method as described in claim 1, characterized in that, The process of determining the control parameter information for the next sub-cycle based on the updated periodic brushing data includes: The next sub-cycle is taken as the new current sub-cycle, and the process returns to the steps of obtaining the cycle brushing data corresponding to the current sub-cycle when the start of the current sub-cycle is detected, and determining the control parameter information of the current sub-cycle based on the cycle brushing data.

3. The method as described in claim 2, characterized in that, After determining the control parameter information of the current sub-cycle based on the periodic brushing data, the method further includes: Determine whether the current update count of the periodic brushing data has reached a preset update count threshold; If the number of updates does not reach the preset update threshold, the step of controlling the electric toothbrush to operate based on the control parameter information and collecting brushing behavior data within the current sub-cycle is determined to be executed.

4. The method as described in claim 3, characterized in that, The method further includes: When the number of updates reaches the preset update number threshold, the first preset period is determined to begin, and the control parameter information is used as the initial control parameter for the first preset period. Within the first preset period, the electric toothbrush is controlled to operate based on the initial control parameters, and brushing behavior data within the first preset period is collected; In response to the end of the first preset cycle, a new current sub-cycle is started, and the process returns to the step of obtaining the cycle brushing data corresponding to the current sub-cycle when the start of the current sub-cycle is detected.

5. The method as described in claim 1, characterized in that, The step of updating the periodic brushing data based on the brushing behavior data collected within the current sub-cycle to generate updated periodic brushing data includes: The brushing behavior data collected in the current sub-cycle is added to the cycle brushing data to generate updated cycle brushing data.

6. The method as described in claim 5, characterized in that, The step of updating the periodic brushing data based on the brushing behavior data collected within the current sub-cycle to generate updated periodic brushing data further includes: If the amount of data in the periodic brushing data exceeds the preset target amount of data, delete one or more brushing behavior data with the earliest corresponding time in the periodic brushing data, so that the amount of data in the periodic brushing data is equal to the preset target amount of data.

7. The method as described in claim 1, characterized in that, The method further includes: If the electric toothbrush is detected to be in an initialization state, the preset initial control parameters are obtained; Within a first preset period, the electric toothbrush is controlled to operate based on the initial control parameters, and brushing behavior data within the first preset period is collected. In response to the end of the first preset cycle, the current sub-cycle is started, and the brushing behavior data collected in the first preset cycle is used as the brushing behavior data collected in the preset reference cycle before the current sub-cycle. The step of obtaining the cycle brushing data corresponding to the current sub-cycle is then executed.

8. The method as described in claim 7, characterized in that, The process of obtaining the preset initial control parameters includes: To obtain information about users' oral health issues and / or brushing habits; The preset initial control parameters are determined based on the oral health information and / or brushing habits information.

9. The method as described in claim 8, characterized in that, The acquisition of users' oral health information and / or brushing habits includes: Information on oral health problems and / or brushing behavior preferences identified by the user is obtained through the user terminal; and / or, The electric toothbrush is used to perform oral cavity detection on the user, identifying the user's oral health issues and / or brushing habits.

10. The method as described in claim 1, characterized in that, The step of determining the control parameter information for the current sub-cycle based on the periodic brushing data includes: The electric toothbrush uses a local first preset model to process the periodic brushing data to generate parameters, thereby obtaining the control parameter information for the current sub-cycle; or... The periodic brushing data is sent to the server, where a second preset model deployed on the server performs parameter generation processing on the periodic brushing data to obtain the control parameter information for the current sub-cycle, and the control parameter information returned by the server is received.

11. The method as described in claim 1, characterized in that, The step of determining the control parameter information for the current sub-cycle based on the periodic brushing data includes: Feature extraction is performed on the periodic brushing data to obtain brushing behavior feature values ​​corresponding to each tooth area; The brushing behavior feature values ​​are compared and analyzed with preset health standard parameters to determine the risk level of each dental area and the parameters to be adjusted. The regional control parameters for each dental region are determined based on the risk level of that region and the parameters to be adjusted. The regional control parameters of each dental region are used as the control parameter information for the current sub-cycle.

12. The method as described in claim 1, characterized in that, The method further includes: Based on the aforementioned periodic brushing data, the cleaning data for each dental area is determined; The cleaning data of each dental region is analyzed to obtain the corresponding analysis results for each dental region. Based on the analysis results corresponding to each tooth region, the first prompt information corresponding to the tooth region is generated; Display the first prompt message.

13. The method as described in claim 12, characterized in that, The step of parsing the cleaning data of each tooth region to obtain the corresponding parsing results for each tooth region includes: For each dental region, preset index data for that dental region is obtained from the dental region cleaning data. Determine whether the preset indicator data meets the corresponding preset compliance conditions; If the preset indicator data does not meet the preset compliance conditions, an analytical result indicating the risk of tooth decay in the tooth area is generated.

14. The method as described in claim 13, characterized in that, The preset indicator data can be any of the following: number of missed brushes, cleaning coverage rate, and cleaning time; When the preset indicator data is the number of missed refreshes, the corresponding preset compliance condition is: the number of missed refreshes is less than a preset number threshold. When the preset indicator data is the cleaning coverage rate, the corresponding preset compliance condition is: the cleaning coverage rate is greater than the preset coverage rate threshold; When the preset indicator data is the cleaning time, the corresponding preset compliance condition is: the cleaning time is greater than the preset time threshold.

15. The method as described in claim 13, characterized in that, If the preset indicator data does not meet the preset compliance conditions, the method further includes: For preset index data that do not meet the preset compliance conditions, mark information for the tooth region is generated; The step of determining the control parameter information for the current sub-cycle based on the periodic brushing data includes: Based on a preset parameter adjustment model, the periodic brushing data and the marking information are processed to generate parameters to obtain the control parameter information of the current sub-cycle. The marking information is used as input information of the parameter adjustment model to drive the parameter adjustment model to perform control parameter enhancement processing on the tooth area corresponding to the marking information.

16. The method as described in claim 12, characterized in that, The display of the first prompt information includes: The first prompt message is displayed via the user terminal; and / or, The first prompt message is displayed on the screen of the electric toothbrush.

17. The method as described in claim 1, characterized in that, The method further includes: In response to the end of the current sub-cycle, determine whether the second preset cycle to which the current sub-cycle belongs has ended; When the second preset cycle ends, the brushing data for the current cycle corresponding to the second preset cycle is generated; Obtain the brushing data of the previous historical preset cycle corresponding to the second preset cycle; The current cycle brushing data and the historical cycle brushing data are compared to obtain a first comparison result; A second prompt message is generated based on the first comparison result. The second prompt message is used to prompt the user about the changing trend of brushing behavior data within adjacent preset periods. The second prompt message is displayed.

18. The method as described in claim 1, characterized in that, The periodic brushing data includes at least one of the following: brushing frequency information, cleaning duration information, cleaning coverage information, missed brushing record information, brushing force information, and horizontal brushing record information within the preset reference period.

19. The method as described in claim 1, characterized in that, The control parameter information includes at least one of the following: brushing force parameter, cleaning duration parameter, vibration frequency parameter, and cleaning mode parameter.

20. The method as described in claim 1, characterized in that, The method further includes: If the completion of any brushing action within the current sub-cycle is detected, single brushing action data generated by the brushing action is generated; A corresponding single brushing behavior assessment report is generated based on the single brushing behavior data; and / or, a periodic brushing behavior assessment report is generated based on the single brushing behavior data and the periodic brushing data. Display the single brushing behavior assessment report and / or the periodic brushing behavior assessment report.

21. The method as described in claim 1, characterized in that, The method further includes: Obtain an initial oral cavity model, as well as information on the user's oral health issues and / or brushing habits; Based on the oral health problem information and / or the brushing behavior habit information, the first potential health problem corresponding to each dental area is determined; Based on the periodic brushing data, a second potential health problem corresponding to each dental area is determined; The initial oral cavity model is labeled based on the first potential health problem and the second potential health problem to generate a target oral cavity model, wherein different types of potential health problems correspond to different labels; The target oral cavity model is shown.

22. A control device for an electric toothbrush, characterized in that, include The first acquisition module is used to acquire the periodic brushing data corresponding to the current sub-cycle when the start of the current sub-cycle is detected. The periodic brushing data includes brushing behavior data collected within a preset reference cycle before the current sub-cycle. The first determining module is used to determine the control parameter information of the current sub-cycle based on the periodic brushing data; The first control module is used to control the operation of the electric toothbrush based on the control parameter information during the current sub-cycle, and to collect brushing behavior data during the current sub-cycle. The update module is used to update the periodic brushing data based on the brushing behavior data collected during the current sub-cycle in response to the end of the current sub-cycle, generate updated periodic brushing data, determine the start of the next sub-cycle, and determine the control parameter information of the next sub-cycle based on the updated periodic brushing data.

23. An electric toothbrush, characterized in that, Including processor and memory; The memory stores a computer program adapted to be loaded by the processor and executed as described in any one of claims 1 to 21.

24. A computer storage medium, characterized in that, The computer storage medium stores a plurality of instructions adapted for loading by a processor and executing the method as described in any one of claims 1 to 21.

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