Sub-gingival scaler power analysis method based on AI technology

Abstract

The invention relates to the technical field of supragingival cleaning, and discloses a supragingival cleaning device power analysis method based on an AI technology, and the method comprises the steps: obtaining the structure real-time data and position real-time data of dental calculus, employing a cleaning device power adjustment model, calculating a stress non-uniform coefficient, and calculating and adjusting the power of a cleaning device. According to the method, the real-time data of the structure and the position of the dental calculus are obtained in real time, and the power of the scaler is adjusted in combination with the scaler power adjustment model; by analyzing the stress structure change caused by the change of the real-time data of the dental calculus structure, the stress non-uniform coefficient is calculated, and then the power is adjusted; the power of the scaler is dynamically changed based on the actual condition of the dental calculus, when the area, shape or hardness of the dental calculus is changed and the dental calculus is close to the gingiva, the power is automatically and timely adjusted, damage to the gingiva due to improper power is avoided, and meanwhile the cleaning efficiency is improved. The problems that a traditional scaler is inaccurate in power control and cannot adapt to dental calculus changes in real time are effectively solved.

Description

Technical Field

[0001] The present application relates to the technical field of supragingival scaling, and specifically to a power analysis method of a supragingival scaler based on AI technology. Background Art

[0002] In the field of oral medicine, supragingival cleaning is an important means of preventing and treating periodontal diseases, and ultrasonic cleaners are widely used due to their high efficiency. However, the current supragingival cleaning technology has significant defects in power control, which are manifested in:

[0003] Most traditional dental scalers use fixed power output, or can only perform simple power level adjustment, and are unable to adjust the power in real time and accurately according to the actual situation of dental calculus. In the actual cleaning process, the area, hardness and other characteristics of dental calculus will continue to change with the cleaning process. For example, when dental calculus begins to fall off, its area and structure change, and the cleaning difficulty decreases accordingly. However, fixed-power scalers continue to work at a higher power, which can easily cause unnecessary impact and damage to the gums. When new dental calculus is detected and the cleaning difficulty increases, if the power cannot be increased in time, the cleaning efficiency will be low.

[0004] Although some advanced scalers try to use sensors to obtain tartar data, they fail to fully consider the impact of changes in the force structure caused by changes in the area structure on the difficulty of cleaning, and cannot achieve real-time dynamic adjustment of power. Chinese Patent No. CN202311041186.0 discloses a power control method, device, equipment, and readable storage medium, but the invention does not specifically involve power adjustment based on changes in the area structure of tartar, and does not involve the rapid response of the scaler in actual cleaning operations and related content on protecting the gums. The lag and inaccuracy of this power control not only affects the cleaning effect, but may also cause adverse reactions such as gingival bleeding and pain, reducing the patient's treatment experience.

[0005] In summary, there is an urgent need for a new supragingival scaler power analysis based on AI technology to realize real-time analysis of changes in tartar characteristics, accurately adjust the scaler power, and improve cleaning efficiency while protecting the gums. Summary of the invention

[0006] The purpose of this application is to provide a supragingival scaler power analysis method based on AI technology to solve the technical problems raised in the above background technology.

[0007] To achieve the above objectives, the present application discloses the following technical solutions: a supragingival scaler power analysis method based on AI technology, comprising:

[0008] Using sensors to obtain real-time structural data and real-time position data of dental calculus; wherein the real-time structural data is used to characterize the real-time inherent properties of dental calculus, which inherent properties at least include the area, shape and hardness of dental calculus, and the real-time position data is used to characterize the real-time position of dental calculus on the gums;

[0009] The force structure changes caused by the changes in the real-time data of the structure are analyzed by using a preset scaler power adjustment model, and the force unevenness coefficient is calculated in real time; wherein the scaler adjustment model is used to determine the real-time changes of the corresponding force structure based on the changes in the real-time data of the structure, and the unevenness coefficient is used to characterize the degree of easy cleaning of dental calculus, and the unevenness coefficient is proportional to the degree of easy cleaning of dental calculus;

[0010] Based on the changes in the real-time data of the structure, the force unevenness coefficient and the real-time data of the position of dental calculus, the power of the scaler is calculated and adjusted in real time.

[0011] Preferably, the method of using sensors to obtain real-time data on the structure and position of dental calculus is as follows:

[0012] The boundary contour of dental plaque is dynamically captured by using the pressure sensor, displacement sensor and image sensor preset on the scaler probe; based on the preset image recognition algorithm and geometric calculation algorithm, the structural data and the position data are updated in real time to obtain real-time structural data and real-time position data.

[0013] Preferably, the scaler power adjustment model is specifically:

[0014] Obtaining structural history data and location history data of dental calculus;

[0015] The power adjustment model of the dental scaler is trained by using AI technology to perform the calculation of the force unevenness coefficient by using the structural history data and the position history data, and the calculation process includes: dividing the obtained dental calculus image into several areas, recording the forces exerted on the dental calculus in different areas based on the time series and calculating the average force exerted on the dental calculus at the corresponding time, and calculating the force unevenness coefficient based on the forces exerted on the dental calculus in different areas and the average force exerted on the dental calculus at the corresponding time;

[0016] Based on the force unevenness coefficient and the position history data, the history record of adjusting the scaler power is obtained and feature extraction is performed to obtain a gum safety distance parameter, wherein the gum safety distance parameter is used to trigger the adjustment of the scaler power, and the adjustment includes increasing the power and decreasing the power;

[0017] Based on the change of the force unevenness coefficient and the historical data of the position of dental calculus, a proportional coefficient when fitting and calculating and adjusting the scaler power is used to calculate the scaler power adjustment value;

[0018] The change of the real-time data of the position of dental calculus is used to determine whether to trigger the adjustment of the power of the scaler. If yes, the power of the scaler is calculated and adjusted in real time based on the real-time data of the structure and the force unevenness coefficient. Otherwise, the change of the real-time data of the position of dental calculus is repeatedly used to determine whether to trigger the adjustment of the power of the scaler.

[0019] Preferably, the calculation of the stress unevenness coefficient is specifically as follows:

[0020] The force unevenness coefficient is calculated using a preset force unevenness coefficient calculation formula, wherein the force unevenness coefficient calculation formula is:

[0021]

[0022] Among them, F i,t is the force on the dental plaque at time t and area i, is the average force on the dental calculus at time t, n is the number of divided areas, U t is the calculated force unevenness coefficient.

[0023] Preferably, the use of the change in the real-time data of the position of dental calculus to determine whether to trigger the adjustment of the scaler power is to calculate and adjust the scaler power in real time based on the real-time data of the structure and the force unevenness coefficient, specifically:

[0024] When the distance between the real-time data of the position of the dental calculus and the gums is less than or equal to the gum safety distance parameter, it is determined that the adjustment of the scaler power is triggered, and the scaler power adjustment value is calculated using a preset scaler power adjustment formula; wherein the scaler power adjustment formula is:

[0025] ΔP t =c(k t )*U t *S t

[0026] Among them, S t is the area of ​​dental calculus at time t, c(k t ) is a preset proportional coefficient judgment function for adjusting the power of the scaler, and the proportional coefficient judgment function is used to output the proportional coefficient selected at time t, ΔP t is the calculated power adjustment value of the scaler.

[0027] Preferably, the proportional coefficient judgment function is specifically:

[0028] Calculate the change rate ΔU of the non-uniformity coefficient within the preset non-uniformity coefficient supervision period T before time t T , then the proportional coefficient of the output at time t is:

[0029]

[0030] Among them, k 1 k is the output reduction coefficient and 1 <0, k 2 k is the output increase ratio and 2 >0.

[0031] Preferably, the calculation of the stress non-uniformity coefficient further includes:

[0032] The optimized force uneven coefficient is calculated using a preset optimized force uneven coefficient calculation formula, and the optimized force uneven coefficient is used to optimize the force uneven coefficient based on changes in hardness and area; wherein the optimized force uneven coefficient calculation formula is:

[0033]

[0034] Where: f(H t ) is the hardness optimization value calculated by a preset hardness optimization function, wherein the hardness optimization function is used to optimize the force unevenness coefficient based on the change of hardness, α 1 It is the trigger index of the hardness optimization function. When the hardness change value does not meet the preset hardness change value threshold within the preset hardness supervision period, α 1 =1, otherwise α 1 =0; g(S t ) is the area optimization value calculated by a preset area optimization function, wherein the area optimization function is used to optimize the force unevenness coefficient based on the change of the area, α 2 is the area optimization function trigger index. When the area change rate does not meet the preset area change rate threshold within the preset area supervision period, α 2 =1, otherwise α 2 =0; U' t is the calculated optimized force uneven coefficient.

[0035] Preferably, the hardness optimization function is specifically:

[0036]

[0037] Among them, β is the hardness change correction coefficient obtained by regression analysis, which is used to normalize the hardness change value. t is the hardness at time t, is the period of the last hardness monitoring cycle ΔtH The hardness at the end, f(H t ) is the optimized hardness value calculated at time t.

[0038] Preferably, the area optimization function is specifically:

[0039]

[0040] in, is the area at time t in the previous area supervision cycle Δt S The absolute value of the area change rate at the end, g(S t ) is the area optimization value calculated at time t.

[0041] Preferably, when the optimized force unevenness coefficient exists, the power of the scaler is calculated and adjusted in real time using the optimized force unevenness coefficient and the real-time data of the structure.

[0042] Beneficial effects: The supragingival scaler power analysis method based on AI technology of the present application utilizes pressure sensors, displacement sensors and image sensors to obtain real-time data on the structure and position of tartar, and combines with a preset scaler power adjustment model to achieve accurate and real-time adjustment of the scaler power; by analyzing the changes in the force structure caused by changes in the real-time data of the tartar structure, the force unevenness coefficient is calculated, and then the power is adjusted according to the changes in the real-time data of the structure, force and position; the scaler power is dynamically changed based on the actual situation of the tartar, and the power is automatically and timely adjusted when the area, shape or hardness of the tartar changes, and when the tartar is close to the gums, to avoid damage to the gums due to improper power, while improving cleaning efficiency, effectively solving the problem of inaccurate power control of traditional scalers and the inability to adapt to real-time changes in tartar. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without paying any creative work.

[0044] Figure 1 A flowchart of a supragingival scaler power analysis method based on AI technology provided in an embodiment of the present application. DETAILED DESCRIPTION

[0045] The technical solutions in the embodiments of the present application are described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application.

[0046] In this article, the term "comprising" is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of more restrictions, the elements defined by the sentence "comprising..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0047] This embodiment discloses Figure 1 A supragingival scaler power analysis method based on AI technology is shown, comprising:

[0048] S1: using sensors to obtain real-time structural data and real-time position data of dental calculus; wherein the real-time structural data is used to characterize the real-time inherent properties of dental calculus, which at least include the area, shape and hardness of dental calculus, and the real-time position data is used to characterize the real-time position of dental calculus on the gums;

[0049] S2: Analyze the force structure changes caused by the changes in the real-time data of the structure using the preset scaler power adjustment model, and calculate the force unevenness coefficient in real time; wherein the scaler adjustment model is used to determine the real-time changes of the corresponding force structure based on the changes in the real-time data of the structure, and the unevenness coefficient is used to characterize the degree of easy cleaning of dental calculus, and the unevenness coefficient is proportional to the degree of easy cleaning of dental calculus;

[0050] S3: Based on the changes in the real-time data of the structure, the force unevenness coefficient and the real-time data of the position of dental plaque, the scaler power is calculated and adjusted in real time.

[0051] Based on the above, this embodiment uses pressure sensors, displacement sensors and image sensors to obtain real-time data on the structure and position of tartar, and combines with a preset scaler power adjustment model to achieve accurate and real-time adjustment of the scaler power; by analyzing the changes in the force structure caused by changes in the real-time data of the tartar structure, the force unevenness coefficient is calculated, and the power is adjusted according to the changes in the real-time data of the structure, force and position; the scaler power is dynamically changed based on the actual situation of the tartar, and the power is automatically and timely adjusted when the area, shape or hardness of the tartar changes, and when the tartar is close to the gums, to avoid damage to the gums due to improper power, while improving cleaning efficiency, effectively solving the problem of inaccurate power control of traditional scalers and the inability to adapt to real-time changes in tartar.

[0052] Specifically, the sensor is used to obtain the real-time data of the structure and position of dental calculus, specifically:

[0053] The pressure sensor, displacement sensor and image sensor preset on the scaler probe are used to dynamically capture the boundary contour of dental calculus; based on the preset image recognition algorithm and geometric calculation algorithm, the structural data and position data are updated in real time to obtain real-time structural data and real-time position data.

[0054] Based on the above, this embodiment uses the existing pressure sensors, displacement sensors and image sensors preset on the scaler probe, in conjunction with the existing image recognition algorithm and geometric calculation algorithm, to achieve real-time update of tartar structure and position data. These sensors can dynamically capture the boundary contour of tartar, and convert the collected data into accurate real-time structural data and real-time position data through algorithm processing, thereby providing an accurate data basis for subsequent power adjustment, so that the scaler power adjustment can be closely based on the actual state changes of tartar, and compared with traditional technologies, it can more accurately reflect the real-time situation of tartar, laying a solid data foundation for achieving precise power control.

[0055] Specifically, the scaler power adjustment model is as follows:

[0056] Obtaining structural history data and location history data of dental calculus;

[0057] The power adjustment model of the dental scaler is trained by using AI technology to calculate the force unevenness coefficient using the structural history data and the position history data. The calculation process includes: dividing the obtained dental calculus image into several areas, recording the forces exerted on the dental calculus in different areas based on the time series and calculating the average force exerted on the dental calculus at the corresponding time, and calculating the force unevenness coefficient based on the forces exerted on the dental calculus in different areas and the average force exerted on the dental calculus at the corresponding time;

[0058] Based on the force unevenness coefficient and the historical position data, the historical records of adjusting the scaler power are obtained and features are extracted to obtain a gum safety distance parameter. The gum safety distance parameter is used to trigger the adjustment of the scaler power, which includes increasing the power and decreasing the power.

[0059] Based on the change of the force unevenness coefficient and the historical data of the position of dental calculus, a proportional coefficient is fitted to calculate and adjust the scaler power, and the proportional coefficient is used to calculate the scaler power adjustment value;

[0060] The change of real-time data of the position of dental calculus is used to determine whether to trigger the adjustment of the scaler power. If so, the scaler power is calculated and adjusted in real time based on the real-time data of the structure and the force unevenness coefficient. Otherwise, the change of real-time data of the position of dental calculus is repeatedly used to determine whether to trigger the adjustment of the scaler power.

[0061] Based on the above, this embodiment uses the structural historical data and position historical data of dental calculus and existing AI technologies, such as deep learning model technology, to train the scaler power adjustment model, and realizes the optimization of the power adjustment strategy based on multi-dimensional data. The model calculates the force unevenness coefficient, extracts the gum safety distance parameter, and fits the proportional coefficient to determine whether to adjust the power based on the real-time data changes of the dental calculus position. During actual cleaning, the force conditions of the dental calculus in different areas, the distance from the gums, and the power adjustment history are taken into account, making the scaler power adjustment more intelligent and accurate, effectively improving the safety and efficiency of the cleaning process.

[0062] Specifically, the force unevenness coefficient is calculated as follows:

[0063] The force unevenness coefficient is calculated using the preset force unevenness coefficient calculation formula, where the force unevenness coefficient calculation formula is:

[0064]

[0065] Among them, F i,t is the force on the dental plaque at time t and area i, is the average force on the dental calculus at time t, n is the number of divided areas, U t is the calculated force unevenness coefficient.

[0066] Based on the above, this embodiment utilizes the calculation formula of the force unevenness coefficient to realize the quantitative evaluation of the uneven force degree of dental calculus. It divides the dental calculus image into several areas, records the force and the average force of different areas, and calculates the force unevenness coefficient, so as to intuitively reflect the uniformity of the force on the dental calculus, and then reflect its ease of cleaning, which provides a clear basis for the subsequent power adjustment, so that the power of the scaler can be adjusted based on the force characteristics of the dental calculus. Compared with the traditional method of relying on experience or simple judgment, the scientificity and accuracy of the power adjustment are greatly improved.

[0067] Specifically, the change of the real-time data of the position of the dental calculus is used to determine whether to trigger the adjustment of the scaler power. If so, the scaler power is calculated and adjusted in real time based on the real-time data of the structure and the force unevenness coefficient, specifically:

[0068] When the distance between the real-time data of the position of the dental calculus and the gums is less than or equal to the gum safety distance parameter, it is determined that the adjustment of the scaler power is triggered, and the scaler power adjustment value is calculated using a preset scaler power adjustment formula; wherein the scaler power adjustment formula is:

[0069] ΔP t =c(k t )*U t *S t

[0070] Among them, S t is the area of ​​dental calculus at time t, c(k t ) is a preset proportional coefficient judgment function for adjusting the power of the scaler, and the proportional coefficient judgment function is used to output the proportional coefficient selected at time t, ΔP t is the calculated power adjustment value of the scaler.

[0071] Based on the above, this embodiment utilizes the comparison between the real-time data of tartar position and the gum safety distance parameter, as well as the scaler power adjustment formula, to realize automatic adjustment of the scaler power based on the relative position of tartar and gums. In actual application, when the tartar is close to the gums and reaches the safety distance threshold, the power adjustment is triggered, and the adjustment value is calculated by the power adjustment formula, thereby effectively avoiding damage to the gums due to excessive power when the scaler is close to the gums. At the same time, it ensures that the scaler can work at appropriate power in the normal cleaning area, taking into account both cleaning efficiency and gum safety, and solving the problem of easy damage to the gums during traditional cleaning.

[0072] Specifically, the proportional coefficient judgment function is:

[0073] Calculate the change rate ΔU of the non-uniformity coefficient within the preset non-uniformity coefficient supervision period T before time t T , then the proportional coefficient of the output at time t is:

[0074]

[0075] Among them, k 1 k is the output reduction coefficient and 1 <0, k 2 k is the output increase ratio and 2 >0.

[0076] It should be noted that, in this embodiment, the response rate of the power adjustment is controlled based on the size of the non-uniform coefficient supervision period T, so as to improve the real-time performance of the power adjustment. It can be understood that, in ΔU T When ≥0, it means that the unevenness coefficient is increasing, which means the degree of easy cleaning is decreasing. At this time, the proportional coefficient is controlled to reduce the power, thereby ensuring the safety of the cleaning process. On the contrary, when ΔU T When it is less than 0, it indicates that the unevenness coefficient is decreasing, which means the degree of ease of cleaning is increasing. At this time, the proportional coefficient is controlled to increase the power, thereby ensuring the efficiency of the cleaning process.

[0077] Based on the above, this embodiment utilizes the calculation of the change rate of the unevenness coefficient and determines the proportional coefficient according to the change situation, thereby realizing the dynamic optimization of the proportional coefficient of the scaler power adjustment. By analyzing its changing trend within the unevenness coefficient supervision period and outputting different proportional coefficients when the change rate is different, the scaler power adjustment can be more finely controlled according to the dynamic changes in the difficulty of tartar cleaning. In a specific example, when the cleaning difficulty changes greatly, a larger proportional coefficient is used to quickly adjust the power, and when the change is small, a smaller proportional coefficient is used to smoothly adjust it, thereby improving the adaptability and flexibility of the power adjustment and further optimizing the scaling process.

[0078] Specifically, the calculation of the force unevenness coefficient also includes:

[0079] The optimized force uneven coefficient is calculated using a preset calculation formula for the optimized force uneven coefficient, and the optimized force uneven coefficient is used to optimize the force uneven coefficient based on changes in hardness and area; wherein the calculation formula for the optimized force uneven coefficient is:

[0080]

[0081] Where: f(H t ) is the hardness optimization value calculated by the preset hardness optimization function. The hardness optimization function is used to optimize the force unevenness coefficient based on the change of hardness. 1 It is the trigger index of the hardness optimization function. When the hardness change value does not meet the preset hardness change value threshold within the preset hardness supervision period, α 1 =1, otherwise α 1 =0; g(St ) is the area optimization value calculated by the preset area optimization function. The area optimization function is used to optimize the force unevenness coefficient based on the change of area. 2 is the area optimization function trigger index. When the area change rate does not meet the preset area change rate threshold within the preset area supervision period, α 2 =1, otherwise α 2 =0; U' t is the calculated optimized force uneven coefficient.

[0082] Based on the above, this embodiment uses the optimization formula for calculating the force unevenness coefficient, combined with the hardness optimization function and the area optimization function, to achieve the optimization of the force unevenness coefficient. By considering the changes in hardness and area, when the hardness or area changes to a certain extent, the force unevenness coefficient is adjusted so that the force unevenness coefficient more accurately reflects the actual cleaning difficulty of dental calculus, providing a more accurate basis for adjusting the power of the cleaning device. Compared with the traditional method that only considers the basic force conditions, it can more comprehensively consider the impact of changes in dental calculus characteristics on the cleaning difficulty, thereby improving the accuracy of power adjustment.

[0083] Specifically, the hardness optimization function is:

[0084]

[0085] Among them, β is the hardness change correction coefficient obtained by regression analysis, which is used to normalize the hardness change value. t is the hardness at time t, is the period of the last hardness monitoring cycle Δt H The hardness at the end, f(H t ) is the optimized hardness value calculated at time t.

[0086] Based on the above, this embodiment uses the hardness optimization function to process the hardness change value, realizes the optimization of the force unevenness coefficient based on the hardness change, obtains the hardness change value correction coefficient through the existing regression analysis technology, and calculates the hardness optimization value after normalizing the hardness change value. The optimization value is used to adjust the force unevenness coefficient so that the force unevenness coefficient can more accurately reflect the change in cleaning difficulty caused by the hardness change of dental calculus. When the hardness of dental calculus changes, the power of the scaler can be adjusted more reasonably accordingly, which improves the adaptability of the scaling process to the change of dental calculus hardness and ensures the cleaning effect and safety.

[0087] Specifically, the area optimization function is:

[0088]

[0089] in, is the area at time t in the previous area supervision cycle Δt S The absolute value of the area change rate at the end, g(S t ) is the area optimization value calculated at time t.

[0090] Based on the above, this embodiment uses the area optimization function to analyze the area change, realizes the optimization of the force unevenness coefficient based on the area change, and calculates the absolute value of the area change rate and uses it to calculate the area optimization value of the area optimization function. The optimization value can reflect the impact of the area change on the difficulty of cleaning dental calculus, thereby optimizing the force unevenness coefficient. When the area of ​​dental calculus changes, such as the increase in area, which may increase the difficulty of cleaning, the area optimization function can make the force unevenness coefficient change accordingly, thereby prompting the scaler power to make reasonable adjustments, and enhancing the ability of the scaler to cope with changes in the area of ​​dental calculus.

[0091] Specifically, when there is an optimized force unevenness coefficient, the optimized force unevenness coefficient and real-time structural data are used to calculate and adjust the scaler power in real time.

[0092] Based on the above, when there is an optimized force uneven coefficient, this embodiment uses the coefficient and the real-time data of the structure to calculate and adjust the power of the scaler in real time, thereby achieving more precise power control. The optimized force uneven coefficient comprehensively considers the influence of multiple factors such as hardness and area on the difficulty of tartar cleaning. It is more accurate than the original force uneven coefficient. Combining the power adjustment with the real-time data of the structure can allow the scaler to adjust the power more accurately according to the comprehensive information of the real-time status of the tartar. While ensuring the cleaning effect, it protects the gums to the greatest extent, significantly improving the overall effect and safety of supragingival cleaning.

[0093] In summary, the supragingival scaler power analysis method based on AI technology in this embodiment uses pressure sensors, displacement sensors and image sensors to obtain real-time data on the structure and position of tartar, and combines with a preset scaler power adjustment model to achieve accurate and real-time adjustment of the scaler power; by analyzing the changes in the force structure caused by changes in the real-time data of the tartar structure, the force unevenness coefficient is calculated, and then the power is adjusted according to the changes in the real-time data of the structure, force and position; the scaler power is dynamically changed based on the actual situation of the tartar, and the power is automatically and timely adjusted when the area, shape or hardness of the tartar changes, and when the tartar is close to the gums, to avoid damage to the gums due to improper power, while improving cleaning efficiency, effectively solving the problem of inaccurate power control of traditional scalers and the inability to adapt to real-time changes in tartar.

[0094] In the embodiments provided in the present application, it should be understood that the embodiments described herein can be implemented in hardware, software, firmware, middleware, code or any appropriate combination thereof. For hardware implementation, the processor can be implemented in one or more of the following units: application specific integrated circuit (ASIC), digital signal processor (DSP), digital signal processing device (DSPD), programmable logic device (PLD), field programmable gate array (FPGA), processor, controller, microcontroller, microprocessor, other electronic units designed to implement the functions described herein or their combination. For software implementation, part or all of the flow of the embodiment can be completed by instructing the relevant hardware through a computer program. When implemented, the above program can be stored in a computer-readable storage medium or transmitted as one or more instructions or codes on a computer-readable storage medium. Computer-readable storage media include computer storage media and communication media, wherein the communication medium includes any medium that is convenient for transmitting a computer program from one place to another. The storage medium can be any available medium that a computer can access. The computer-readable storage medium can include but is not limited to RAM, ROM, EEPROM, CD-ROM or other optical disk storage, disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of an instruction or data structure and can be accessed by a computer.

[0095] Finally, it should be noted that the above is only a preferred embodiment of the present application and is not intended to limit the present application. Although the present application has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A supragingival scaler power analysis method based on AI technology, characterized in that: include: Using sensors to obtain real-time structural data and real-time position data of dental calculus; wherein the real-time structural data is used to characterize the real-time inherent properties of dental calculus, which inherent properties at least include the area, shape and hardness of dental calculus, and the real-time position data is used to characterize the real-time position of dental calculus on the gums; The force structure changes caused by the changes in the real-time data of the structure are analyzed by using a preset scaler power adjustment model, and the force unevenness coefficient is calculated in real time; wherein the scaler adjustment model is used to determine the real-time changes of the corresponding force structure based on the changes in the real-time data of the structure, and the unevenness coefficient is used to characterize the degree of easy cleaning of dental calculus, and the unevenness coefficient is proportional to the degree of easy cleaning of dental calculus; Based on the changes in the real-time data of the structure, the force unevenness coefficient and the real-time data of the position of dental calculus, the power of the scaler is calculated and adjusted in real time.

2. The AI-based supragingival scaler power analysis method according to claim 1 is characterized in that: The method of using sensors to obtain real-time data on the structure and position of dental calculus is specifically as follows: The boundary contour of dental plaque is dynamically captured by using the pressure sensor, displacement sensor and image sensor preset on the scaler probe; based on the preset image recognition algorithm and geometric calculation algorithm, the structural data and the position data are updated in real time to obtain real-time structural data and real-time position data.

3. The AI-based supragingival scaler power analysis method according to claim 1, characterized in that: The scaler power adjustment model is specifically: Obtaining structural history data and location history data of dental calculus; The power adjustment model of the dental scaler is trained by using AI technology to perform the calculation of the force unevenness coefficient by using the structural history data and the position history data, and the calculation process includes: dividing the obtained dental calculus image into several areas, recording the forces exerted on the dental calculus in different areas based on the time series and calculating the average force exerted on the dental calculus at the corresponding time, and calculating the force unevenness coefficient based on the forces exerted on the dental calculus in different areas and the average force exerted on the dental calculus at the corresponding time; Based on the force unevenness coefficient and the position history data, the history record of adjusting the scaler power is obtained and feature extraction is performed to obtain a gum safety distance parameter, wherein the gum safety distance parameter is used to trigger the adjustment of the scaler power, and the adjustment includes increasing the power and decreasing the power; Based on the change of the force unevenness coefficient and the historical data of the position of dental calculus, a proportional coefficient when fitting and calculating and adjusting the scaler power is used to calculate the scaler power adjustment value; The change of the real-time data of the position of dental calculus is used to determine whether to trigger the adjustment of the power of the scaler. If yes, the power of the scaler is calculated and adjusted in real time based on the real-time data of the structure and the force unevenness coefficient. Otherwise, the change of the real-time data of the position of dental calculus is repeatedly used to determine whether to trigger the adjustment of the power of the scaler.

4. The AI-based supragingival scaler power analysis method according to claim 3 is characterized in that: The calculation of the non-uniform stress coefficient is specifically: The force unevenness coefficient is calculated using a preset force unevenness coefficient calculation formula, wherein the force unevenness coefficient calculation formula is: Among them, F i,t is the force on the dental plaque at time t and area i, is the average force on the dental calculus at time t, n is the number of divided areas, U t is the calculated force unevenness coefficient.

5. The AI-based supragingival scaler power analysis method according to claim 4, characterized in that: The use of the change in the real-time data of the position of dental calculus to determine whether to trigger the adjustment of the scaler power is to calculate and adjust the scaler power in real time based on the real-time data of the structure and the force unevenness coefficient, specifically: When the distance between the real-time data of the position of the dental calculus and the gums is less than or equal to the gum safety distance parameter, it is determined that the adjustment of the scaler power is triggered, and the scaler power adjustment value is calculated using a preset scaler power adjustment formula; wherein the scaler power adjustment formula is: ΔP t =c(k t )*U t *S t Among them, S t is the area of ​​dental calculus at time t, c(k t ) is a preset proportional coefficient judgment function for adjusting the power of the scaler, and the proportional coefficient judgment function is used to output the proportional coefficient selected at time t, ΔP t is the calculated power adjustment value of the scaler.

6. The AI-based supragingival scaler power analysis method according to claim 5, characterized in that: The proportional coefficient judgment function is specifically: Calculate the change rate ΔU of the non-uniformity coefficient within the preset non-uniformity coefficient supervision period T before time t T , then the proportional coefficient of the output at time t is: Wherein, k1 is the output reduction proportional coefficient and k1<0, k2 is the output increase proportional coefficient and k2>0.

7. The AI-based supragingival scaler power analysis method according to claim 4, characterized in that: The calculation of the stress non-uniformity coefficient also includes: The optimized force uneven coefficient is calculated using a preset optimized force uneven coefficient calculation formula, and the optimized force uneven coefficient is used to optimize the force uneven coefficient based on changes in hardness and area; wherein the optimized force uneven coefficient calculation formula is: Where: f(H t ) is the hardness optimization value calculated by the preset hardness optimization function, the hardness optimization function is used to optimize the force unevenness coefficient based on the change of hardness, α1 is the trigger index of the hardness optimization function, when the hardness change value does not meet the preset hardness change value threshold within the preset hardness supervision period, α1=1, otherwise α1=0; g(S t ) is the area optimization value calculated by the preset area optimization function, the area optimization function is used to optimize the force unevenness coefficient based on the change of the area, α2 is the area optimization function trigger index, when the area change rate does not meet the preset area change rate threshold within the preset area supervision period, α2 = 1, otherwise α2 = 0; U' t is the calculated optimized force uneven coefficient.

8. The AI-based supragingival scaler power analysis method according to claim 7, characterized in that: The hardness optimization function is specifically: Among them, β is the hardness change correction coefficient obtained by regression analysis, which is used to normalize the hardness change value. t is the hardness at time t, is the period of the last hardness monitoring cycle Δt H The hardness at the end, f(H t ) is the optimized hardness value calculated at time t.

9. The AI-based supragingival scaler power analysis method according to claim 7, characterized in that: The area optimization function is specifically: in, is the area at time t in the previous area supervision cycle Δt S The absolute value of the area change rate at the end, g(S t ) is the area optimization value calculated at time t.

10. The AI-based supragingival scaler power analysis method according to claim 7, characterized in that: When the optimized force unevenness coefficient exists, the optimized force unevenness coefficient and the real-time structural data are used to calculate and adjust the scaler power in real time.

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