Operation habit classification method, device and equipment based on intelligent dental chair and medium

Abstract

The embodiment of the invention discloses an operation habit classification method and device based on an intelligent dental chair, equipment and a medium. The method is applied to the intelligent dental chair, the intelligent dental chair comprises a plurality of matched treatment tools, each treatment tool is provided with a position sensor and a pressure sensor, and the method comprises the following steps: after the intelligent dental chair is started, obtaining use information of the current intelligent dental chair; in the using process of the intelligent dental chair, using information corresponding to all the treatment tools is obtained through position sensors and pressure sensors on all the treatment tools, and the using information comprises using time, using tracks and using force; determining step feature information of each treatment step in the current treatment scheme according to the use time, the use trajectory and the use force corresponding to each treatment tool; and determining a target operation habit corresponding to the current doctor identifier according to the operation duration and the force control accuracy corresponding to each treatment step. Through the scheme, the operation habit classification precision of the dentist can be improved.

Description

Technical Field

[0001] The present application relates to the field of artificial intelligence technology, and in particular to a method, device, equipment and medium for classifying operating habits based on a smart dental chair. Background Art

[0002] The dental chair is an essential medical device in dental treatment, used to provide patients with comfortable support and working environment during dental treatment. It is the most important working platform in a dental clinic or dental office.

[0003] With the development of medical technology and industry competition, the requirements for doctors are getting higher and higher. Classifying doctors' operating habits can better evaluate doctors. Currently, the operating habits of dentists are generally classified through manual observation. However, since the doctor's operating strength cannot be well observed by the naked eye, and the operating position is located in the patient's mouth, which is not conducive to the observer's viewing, the classification accuracy of the operating habits of dentists is not high enough. Summary of the invention

[0004] The embodiments of the present application provide a method, device, equipment and medium for classifying operating habits based on a smart dental chair, which can improve the accuracy of classifying operating habits of dentists.

[0005] In a first aspect, an embodiment of the present application provides an operation habit classification method based on a smart dental chair, the method being applied to a smart dental chair, the smart dental chair comprising a plurality of matching treatment tools, each of the treatment tools being equipped with a position sensor and a pressure sensor, the method comprising: When the smart dental chair is started, current usage information of the smart dental chair is obtained, wherein the usage information includes a current doctor identification and a current treatment plan; During the use of the smart dental chair, the use information corresponding to each of the treatment tools is obtained through the position sensor and the pressure sensor on each of the treatment tools, and the use information includes the use time, the use track and the use force; Determine step characteristic information of each treatment step in the current treatment plan according to the use time, the use trajectory and the use force corresponding to each treatment tool, wherein the step characteristic information includes operation duration and force control accuracy; The target operation habit corresponding to the current doctor identification is determined according to the operation duration corresponding to each treatment step and the force control accuracy.

[0006] In a second aspect, the embodiment of the present application further provides an operation habit classification device, wherein the smart dental chair includes a plurality of matching treatment tools, each of which is equipped with a position sensor and a pressure sensor, and the operation habit classification device includes: a transceiver unit, configured to obtain current usage information of the smart dental chair after the smart dental chair is started, wherein the usage information includes a current doctor identification and a current treatment plan; and to obtain usage information corresponding to each of the treatment tools respectively through position sensors and pressure sensors on each of the treatment tools during the use of the smart dental chair, wherein the usage information includes a usage time, a usage trajectory, and a usage force; A processing unit is used to determine step characteristic information of each treatment step in the current treatment plan according to the usage time, the usage trajectory and the usage force corresponding to each treatment tool, wherein the step characteristic information includes operation duration and force control accuracy; and determine the target operation habit corresponding to the current doctor identification according to the operation duration and the force control accuracy corresponding to each treatment step.

[0007] In a third aspect, an embodiment of the present application further provides a computer device, which includes a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the above method when executing the computer program.

[0008] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, wherein the storage medium stores a computer program, wherein the computer program includes program instructions, and wherein the program instructions can implement the above method when executed by a processor.

[0009] The embodiment of the present application provides a method, device, equipment and medium for classifying operation habits based on a smart dental chair. The method is applied to a smart dental chair, which includes a variety of matching treatment tools, each of which is equipped with a position sensor and a pressure sensor, and the method includes: when the smart dental chair is started, obtaining the current use information of the smart dental chair, the use information includes the current doctor identification and the current treatment plan; during the use of the smart dental chair, using the position sensor and the pressure sensor on each treatment tool, respectively obtaining the use information corresponding to each treatment tool, the use information includes the use time, the use track and the use force; according to the use time, the use track and the use force corresponding to each treatment tool, determining the step feature information of each treatment step in the current treatment plan, the step feature information includes the operation time and the force control accuracy; according to the operation time and the force control accuracy corresponding to each treatment step, determining the target operation habit corresponding to the current doctor identification. The embodiment of the present application can obtain the usage time, usage trajectory and usage force of the treatment tools based on the position sensors and pressure sensors in the treatment tools, and classify the dentist's operating habits in combination with the usage time, usage trajectory and usage force of each treatment tool, thereby improving the classification accuracy of the dentist's operating habits. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0011] Figure 1 A schematic diagram of a process flow of an operation habit classification method based on a smart dental chair provided in an embodiment of the present application; Figure 2 A schematic diagram of a sub-process of the method for classifying operating habits based on a smart dental chair provided in an embodiment of the present application; Figure 3 A schematic block diagram of an operation habit classification device provided in an embodiment of the present application; Figure 4 A schematic block diagram of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0012] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are 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 this application.

[0013] It should be understood that when used in this specification and the appended claims, the terms "include" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0014] It should also be understood that the terms used in this application specification are only for the purpose of describing specific embodiments and are not intended to limit the application. As used in this application specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0015] It should be further understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0016] The embodiments of the present application provide a method, device, equipment and medium for classifying operation habits based on a smart dental chair.

[0017] The executor of the operation habit classification method based on the smart dental chair can be the operation habit classification device provided in the embodiment of the present application, or a computer device integrated with the operation habit classification device. Specifically, the computer device is a data processing device in the smart dental chair. The smart dental chair includes a variety of matching treatment tools, each of which is equipped with a position sensor and a pressure sensor. Specifically, the pressure sensor is installed at the position of the treatment tool that contacts the patient's mouth.

[0018] Figure 1 is a flow chart of the method for classifying operation habits based on a smart dental chair provided in an embodiment of the present application. Figure 1 As shown, the method includes the following steps S110-S140.

[0019] S110: After the smart dental chair is started, current usage information of the smart dental chair is obtained, where the usage information includes a current doctor identification and a current treatment plan.

[0020] In this embodiment, when the smart dental chair is started, the doctor or the doctor's assistant enters the current doctor identification (such as the doctor's name or work number, etc.) and the current treatment plan (such as orthodontics or root canal treatment, etc.). In some embodiments, the patient identification (such as the patient's name or consultation number, etc.) is also entered to record the treatment process of the corresponding patient.

[0021] S120. During the use of the smart dental chair, the use information corresponding to each of the treatment tools is obtained through the position sensors and pressure sensors on each of the treatment tools, and the use information includes the use time, the use trajectory and the use force.

[0022] In this embodiment, when the doctor uses a treatment tool, the treatment tool automatically turns on the position sensor and the pressure sensor, and records the usage time, usage trajectory and usage force in real time, wherein the usage trajectory and usage force are continuous information corresponding to the usage time. The usage time of different treatment tools is also used to determine the usage order of different treatment tools and the usage time of each treatment tool.

[0023] S130. Determine step characteristic information of each treatment step in the current treatment plan according to the usage time, the usage trajectory, and the usage force corresponding to each treatment tool, wherein the step characteristic information includes operation duration and force control accuracy.

[0024] In this embodiment, the current treatment plan includes multiple treatment steps. The current treatment step can be determined by manual input or automatically analyzed and determined by the smart dental chair, wherein different treatment steps correspond to different execution orders and different treatment tools.

[0025] Specifically, in this embodiment, the operation time of each treatment step is determined by analyzing the usage time of each treatment tool, and the force control accuracy is determined by analyzing the usage trajectory and usage force of each treatment tool. Furthermore, a trained force control accuracy model is preset, and for each treatment step, the usage trajectory and usage force collected by the treatment tool under the treatment step are input into the force control accuracy model for force accuracy analysis to obtain the force control accuracy corresponding to the treatment step.

[0026] S140, determining the target operation habit corresponding to the current doctor identification according to the operation duration corresponding to each of the treatment steps and the force control accuracy.

[0027] In some embodiments, see Figure 2 , step S140 includes: S1401. For each of the treatment steps, according to the corresponding operation duration and the force control accuracy, a preset clustering algorithm is used to determine the step operation characteristics of the treatment step.

[0028] In this embodiment, for each treatment step, based on the operation duration corresponding to the treatment step and the force control accuracy, a clustering algorithm is used to determine which step operation feature of the preset multiple candidate step operation features the step operation feature of the treatment step belongs to.

[0029] The operation characteristics of this step include speed value, precision value and stability value.

[0030] S1402. Determine the target operation habit according to the step operation characteristics corresponding to each of the treatment steps.

[0031] In this embodiment, after determining the step operation characteristics corresponding to each treatment step, the step operation characteristics corresponding to each treatment step are further analyzed to obtain the doctor's target operation habits under the current treatment plan.

[0032] Specifically, different treatment steps correspond to different weight values. After the step operation characteristics of each treatment step are obtained, the target operation habit is determined according to the step operation characteristics and weight values ​​respectively corresponding to each treatment step.

[0033] For example, for each treatment step, the speed value, precision value and stability value corresponding to the treatment step are multiplied by the corresponding weight values ​​respectively to determine the speed weighted value, precision weighted value and stability weighted value of the treatment step, and then the speed weighted values ​​corresponding to each treatment step are added to obtain the total speed value, the precision weighted values ​​corresponding to each treatment step are added to obtain the total precision value, and the stability weighted values ​​corresponding to each treatment step are added to obtain the total stability value; finally, the target operation habit is determined by analyzing the total speed value, the total precision value and the total stability value, such as, when the total speed value is greater than the preset speed threshold and the total stability value is greater than the preset stability threshold, the target operation habit is fast and stable, when the total speed value is greater than the preset speed threshold and the total precision value is greater than the preset precision threshold, the target operation habit is fast and accurate, and so on.

[0034] In some embodiments, in order to provide the doctor's medical level, personalized skill improvement suggestions are also generated. At this time, after determining the step feature information of each treatment step in the current treatment plan according to the use time, the use trajectory and the use intensity corresponding to each treatment tool, the method further includes: Based on the step feature information corresponding to each of the treatment steps and the preset standard step feature information, skill improvement suggestions and a first treatment score corresponding to the current treatment plan are generated. The standard step feature information includes standard operation time and standard force control accuracy. The skill improvement suggestions include treatment tool usage tips and time management optimization suggestions.

[0035] Specifically, the standard step characteristic information of each treatment step includes a speed standard value, a precision standard value, and a stability standard value.

[0036] For example, when the speed value in the step characteristic information is less than the speed standard value, a suggestion is generated to increase the operation speed when executing the corresponding treatment step; when the precision value in the step characteristic information is less than the precision standard value, a suggestion is generated to improve the accuracy when executing the corresponding treatment step; when the stability value in the step characteristic information is less than the stability standard value, a suggestion is generated to improve the stability when executing the corresponding treatment step; and then based on the preset scoring rules, the first treatment score is determined according to the standard step characteristic information of each treatment step and the step operation characteristics of each step.

[0037] The scoring rule is as follows: for each treatment step, the speed score is determined according to the corresponding speed value and the speed standard value, wherein when the speed value is the same as the speed standard value, the speed score is the speed standard score, and when the speed value is lower than the speed standard value, the higher the deviation, the lower the corresponding speed score, and when the speed value is higher than the speed standard value, the higher the deviation, the higher the corresponding speed score; for each treatment step, the precision score is determined according to the corresponding precision value and the precision standard value, wherein when the precision value is the same as the precision standard value, the precision score is the precision standard score, and when the precision value is lower than the precision standard value, the higher the deviation, the lower the corresponding precision score. , when the precision value is higher than the precision standard value, the higher the deviation, the higher the corresponding precision score; for each treatment step, determine the stability score according to the corresponding stability value and stability standard value, wherein, when the stability value is the same as the stability standard value, the stability score is the stability standard score, when the stability value is lower than the stability standard value, the higher the deviation, the lower the corresponding stability score, when the stability value is higher than the stability standard value, the higher the deviation, the higher the corresponding stability score; then add the speed score, the precision standard value and the stability score to obtain the step score of the corresponding treatment step; finally, determine the first treatment score based on the step score of each step and the weight value corresponding to each step.

[0038] In some embodiments, the doctor's operating habits also affect the patient's emotions, and the patient's emotions affect the evaluation of the doctor. In order to improve the accuracy of the doctor's treatment score, this embodiment also obtains the patient's emotional value; at this time, the smart dental chair system also includes a camera installed above the smart dental chair, a heart rate sensor and a blood pressure sensor installed on the armrest of the smart dental chair. During the use of the smart dental chair, the method also includes: The facial change feature information of the patient is obtained through the camera; the heart rate information and the blood pressure information of the patient are obtained through the heart rate sensor and the blood pressure sensor respectively; based on a preset patient emotion recognition model, a first emotion value of the patient during the treatment process is determined according to the facial change feature information, the heart rate information and the blood pressure information; a second emotion value of the patient during the treatment process is obtained through a patient satisfaction feedback module; and a target emotion value is determined according to the first emotion value and the second emotion value.

[0039] In this embodiment, the patient emotion recognition model is a pre-trained deep learning model used to identify different emotion values ​​based on different facial change feature information, heart rate information, and blood pressure information. The higher the first emotion value, the better the patient's emotion during treatment. The first emotion value is an objective emotion value detected by the smart dental chair.

[0040] Furthermore, considering that the heart rate and blood pressure of different patients in a calm state are also different, at this time, it is necessary to obtain the patient's calm heart rate data and calm blood pressure data in a calm state. The heart rate information indicates the difference between the current heart rate data and the calm heart rate data, and the blood pressure information indicates the difference between the current blood pressure data and the calm blood pressure data.

[0041] The second emotion value is a subjective emotion value input by the patient after the treatment.

[0042] In some embodiments, obtaining the facial change feature information of the patient through the camera includes: The current facial video information of the patient is obtained through the camera; the current shape features of key facial parts are extracted from the current facial video information, and the key facial parts include nose, eyes, eyebrows, mouth, cheeks and forehead; the facial change feature information is obtained by analyzing the current shape features and static shape features, and the static shape features are the shape features of the key facial parts collected in advance when the patient is in a calm state.

[0043] Specifically, the static shape feature is the static shape feature captured by the camera when the patient is in a calm state before treatment when lying on the smart dental chair.

[0044] The facial change feature information includes nose change features, eye change features, eyebrow change features, mouth change features, cheek change features and forehead change features. The facial change feature information includes the change amplitude and change direction of each key part of the face. Specifically, the nose change feature includes the nose change amplitude and change direction, the eye change feature includes the eye change amplitude and change direction, the eyebrow change feature includes the eyebrow change amplitude and change direction, the mouth change feature includes the mouth change amplitude and change direction, the cheek change feature includes the cheek change amplitude and change direction, and the forehead change feature includes the forehead change amplitude and change direction.

[0045] It can be seen that this embodiment combines the patient's subjective emotion value and objective emotion value to perform emotion evaluation, and the emotion evaluation has high accuracy.

[0046] Furthermore, after the target emotion value is obtained, a second treatment score corresponding to the target emotion value is determined according to the corresponding relationship between the emotion value and the treatment score, and then the target treatment score is determined according to the first treatment score and the second treatment score.

[0047] Specifically, different weights may be assigned to the first treatment score and the second treatment score, and then the target treatment score is determined according to the first treatment score, the second treatment score, the weight corresponding to the first treatment score, and the weight corresponding to the second treatment score.

[0048] It can be seen that when scoring the current treatment, this embodiment not only considers the doctor's operation score (first score), but also scores in combination with the patient's emotions (second score), and the scoring accuracy is high.

[0049] Furthermore, the calculated target operation habit is the operation habit identified when the doctor performs the current treatment. Since the doctor has different operation habits when performing different treatments, the operation habit identified in one operation cannot well reflect the doctor's operation style type. In order to accurately identify the operation style type corresponding to the current doctor's identifier, at this time, after determining the target operation habit corresponding to the current doctor's identifier according to the operation duration corresponding to each treatment step and the force control accuracy, the method further includes: The target operation habit is stored in an operation style database corresponding to the current doctor identification, wherein the operation style database stores a plurality of operation habit data; and the operation style type corresponding to the current doctor identification is determined according to the operation habit data in the operation style database.

[0050] Specifically, the operating habit with the largest number in the operating habit data may be determined as the operating style type corresponding to the current doctor identification.

[0051] To summarize, the embodiments of the present application can obtain the usage time, usage trajectory, and usage force of the treatment tools based on the position sensors and pressure sensors in the treatment tools, and classify the dentist's operating habits based on the usage time, usage trajectory, and usage force of each treatment tool, thereby improving the classification accuracy of the dentist's operating habits.

[0052] Figure 3 is a schematic block diagram of an operation habit classification device 300 provided in an embodiment of the present application. Figure 3 As shown, corresponding to the above operation habit classification method based on the smart dental chair, the present application also provides an operation habit classification device 300. The operation habit classification device 300 includes a unit for executing the above operation habit classification method based on the smart dental chair. The operation habit classification device 300 is configured in the smart dental chair, and the smart dental chair includes a variety of matching treatment tools, each of which is equipped with a position sensor and a pressure sensor. For details, please refer to Figure 3 The operation habit classification device 300 includes a transceiver unit 301 and a processing unit 302, wherein: The transceiver unit 301 is used to obtain the current usage information of the smart dental chair after the smart dental chair is started, and the usage information includes the current doctor identification and the current treatment plan; during the use of the smart dental chair, the usage information corresponding to each treatment tool is obtained through the position sensor and the pressure sensor on each treatment tool, and the usage information includes the usage time, usage trajectory and usage force; The processing unit 302 is used to determine the step characteristic information of each treatment step in the current treatment plan according to the usage time, the usage trajectory and the usage force corresponding to each treatment tool, wherein the step characteristic information includes operation duration and force control accuracy; and determine the target operation habit corresponding to the current doctor identification according to the operation duration and the force control accuracy corresponding to each treatment step.

[0053] In some embodiments, when the processing unit 302 executes the step of determining the target operation habit corresponding to the current doctor identifier according to the operation duration and the force control accuracy corresponding to each of the treatment steps, it is specifically used to: For each of the treatment steps, a preset clustering algorithm is used to determine the step operation characteristics of the treatment step according to the corresponding operation duration and the force control accuracy; the target operation habit is determined according to the step operation characteristics corresponding to each of the treatment steps.

[0054] In some embodiments, after executing the step of determining the step characteristic information of each treatment step in the current treatment plan according to the use time, the use trajectory and the use force corresponding to each treatment tool, the processing unit 302 is further used to: Based on the step feature information corresponding to each of the treatment steps and the preset standard step feature information, skill improvement suggestions and a first treatment score corresponding to the current treatment plan are generated. The standard step feature information includes standard operation time and standard force control accuracy. The skill improvement suggestions include treatment tool usage tips and time management optimization suggestions.

[0055] In some embodiments, the smart dental chair system further includes a camera installed above the smart dental chair, a heart rate sensor and a blood pressure sensor installed on the armrest of the smart dental chair. During the use of the smart dental chair, the processing unit 302 is further used to: The facial change feature information of the patient is obtained through the camera; the heart rate information and the blood pressure information of the patient are obtained through the heart rate sensor and the blood pressure sensor respectively; based on a preset patient emotion recognition model, a first emotion value of the patient during the treatment process is determined according to the facial change feature information, the heart rate information and the blood pressure information; a second emotion value of the patient during the treatment process is obtained through a patient satisfaction feedback module; and a target emotion value is determined according to the first emotion value and the second emotion value.

[0056] In some embodiments, when executing the step of acquiring the facial change feature information of the patient through the camera, the processing unit 302 is specifically configured to: The transceiver unit 301 is used to obtain the current facial video information of the patient through the camera; the current shape features of key facial parts are extracted from the current facial video information, and the key facial parts include nose, eyes, eyebrows, mouth, cheeks and forehead; the facial change feature information is obtained by analyzing the current shape features and static shape features, and the static shape features are the shape features of the key facial parts that are pre-collected when the patient is in a calm state.

[0057] In some embodiments, after executing the step of determining the target emotion value according to the first emotion value and the second emotion value, the processing unit 302 is further configured to: A second treatment score is determined according to the target emotion value; and a target treatment score is determined according to the first treatment score and the second treatment score.

[0058] In some embodiments, after executing the step of determining the target operation habit corresponding to the current doctor identifier according to the operation duration and the force control accuracy respectively corresponding to each of the treatment steps, the processing unit 302 is further configured to: The target operation habit is stored in an operation style database corresponding to the current doctor identification, wherein the operation style database stores a plurality of operation habit data; and the operation style type corresponding to the current doctor identification is determined according to the operation habit data in the operation style database.

[0059] To sum up, the operation habit classification device 300 provided in the embodiment of the present application can obtain the usage time, usage trajectory and usage force of the treatment tools based on the position sensors and pressure sensors in the treatment tools, and classify the dentist's operation habits in combination with the usage time, usage trajectory and usage force of each treatment tool, thereby improving the classification accuracy of the dentist's operation habits.

[0060] It should be noted that technicians in the relevant field can clearly understand that the specific implementation process of the above-mentioned operation habit classification device and each unit can refer to the corresponding description in the aforementioned method embodiment, and for the convenience and brevity of description, it will not be repeated here.

[0061] The above-mentioned operation habit classification device can be implemented in the form of a computer program. The computer program can be used in Figure 4 Runs on the computer device shown.

[0062] See also Figure 4 , Figure 4 1 is a schematic block diagram of a computer device provided in an embodiment of the present application. The computer device is a data processing device in an intelligent dental chair, and the intelligent dental chair includes a variety of matching treatment tools, each of which is equipped with a position sensor and a pressure sensor.

[0063] See also Figure 4 The computer device 400 includes a processor 402 , a memory and a network interface 405 connected via a system bus 401 , wherein the memory may include a non-volatile storage medium 403 and an internal memory 404 .

[0064] The non-volatile storage medium 403 can store an operating system 4031 and a computer program 4032. The computer program 4032 includes program instructions, and when the program instructions are executed, the processor 402 can execute an operation habit classification method based on a smart dental chair.

[0065] The processor 402 is used to provide computing and control capabilities to support the operation of the entire computer device 400 .

[0066] The internal memory 404 provides an environment for the operation of the computer program 4032 in the non-volatile storage medium 403. When the computer program 4032 is executed by the processor 402, the processor 402 can execute a method for classifying operation habits based on the smart dental chair.

[0067] The network interface 405 is used to communicate with other devices over the network. Figure 4 The structure shown in the figure is merely a block diagram of a portion of the structure related to the solution of the present application, and does not constitute a limitation on the computer device 400 to which the solution of the present application is applied. The specific computer device 400 may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0068] The processor 402 is used to run the computer program 4032 stored in the memory to implement the following steps: When the smart dental chair is started, current usage information of the smart dental chair is obtained, wherein the usage information includes a current doctor identification and a current treatment plan; During the use of the smart dental chair, the use information corresponding to each of the treatment tools is obtained through the position sensor and the pressure sensor on each of the treatment tools, and the use information includes the use time, the use track and the use force; Determine step characteristic information of each treatment step in the current treatment plan according to the use time, the use trajectory and the use force corresponding to each treatment tool, wherein the step characteristic information includes operation duration and force control accuracy; The target operation habit corresponding to the current doctor identification is determined according to the operation duration corresponding to each treatment step and the force control accuracy.

[0069] It should be understood that in the embodiment of the present application, the processor 402 may be a central processing unit (CPU), and the processor 402 may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0070] It can be understood by those skilled in the art that all or part of the processes in the method for implementing the above embodiment can be completed by instructing the relevant hardware through a computer program. The computer program includes program instructions, and the computer program can be stored in a storage medium, which is a computer-readable storage medium. The program instructions are executed by at least one processor in the computer system to implement the process steps of the embodiment of the above method.

[0071] Therefore, the present application also provides a storage medium. The storage medium may be a computer-readable storage medium. The storage medium stores a computer program, wherein the computer program includes program instructions. When the program instructions are executed by a processor, the processor executes the following steps: When the smart dental chair is started, current usage information of the smart dental chair is obtained, wherein the usage information includes a current doctor identification and a current treatment plan; During the use of the smart dental chair, the use information corresponding to each of the treatment tools is obtained through the position sensor and the pressure sensor on each of the treatment tools, and the use information includes the use time, the use track and the use force; Determine step characteristic information of each treatment step in the current treatment plan according to the use time, the use trajectory and the use force corresponding to each treatment tool, wherein the step characteristic information includes operation duration and force control accuracy; The target operation habit corresponding to the current doctor identification is determined according to the operation duration corresponding to each treatment step and the force control accuracy.

[0072] The storage medium may be a USB flash drive, a mobile hard disk, a read-only memory (ROM), a magnetic disk, or an optical disk, etc., which are computer-readable storage media that can store program codes.

[0073] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0074] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of each unit is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0075] The steps in the method of the embodiment of the present application can be adjusted in order, combined and deleted according to actual needs. The units in the device of the embodiment of the present application can be combined, divided and deleted according to actual needs. In addition, the functional units in the various embodiments of the present application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0076] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, terminal, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application.

[0077] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present application, and these modifications or replacements should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A method for classifying operating habits based on a smart dental chair, characterized in that: The method is applied to an intelligent dental chair, which includes a plurality of matching treatment tools, each of which is equipped with a position sensor and a pressure sensor, and the method includes: When the smart dental chair is started, current usage information of the smart dental chair is obtained, wherein the usage information includes a current doctor identification and a current treatment plan; During the use of the smart dental chair, the use information corresponding to each of the treatment tools is obtained through the position sensor and the pressure sensor on each of the treatment tools, and the use information includes the use time, the use track and the use force; Determine step characteristic information of each treatment step in the current treatment plan according to the use time, the use trajectory and the use force corresponding to each treatment tool, wherein the step characteristic information includes operation duration and force control accuracy; The target operation habit corresponding to the current doctor identification is determined according to the operation duration corresponding to each treatment step and the force control accuracy.

2. The method according to claim 1, characterized in that The determining of the target operation habit corresponding to the current doctor identifier according to the operation duration and the force control accuracy respectively corresponding to each treatment step includes: For each of the treatment steps, according to the corresponding operation duration and the force control accuracy, a preset clustering algorithm is used to determine the step operation characteristics of the treatment step; The target operation habit is determined according to the step operation characteristics corresponding to each of the treatment steps.

3. The method according to claim 1, characterized in that After determining the step characteristic information of each treatment step in the current treatment plan according to the use time, the use trajectory and the use strength corresponding to each treatment tool, the method further includes: Based on the step feature information corresponding to each of the treatment steps and the preset standard step feature information, skill improvement suggestions and a first treatment score corresponding to the current treatment plan are generated. The standard step feature information includes standard operation time and standard force control accuracy. The skill improvement suggestions include treatment tool usage tips and time management optimization suggestions.

4. The method according to claim 3, characterized in that: The smart dental chair system further includes a camera installed above the smart dental chair, a heart rate sensor and a blood pressure sensor installed on the armrests of the smart dental chair. During the use of the smart dental chair, the method further includes: Acquiring the patient's facial change feature information through the camera; Acquiring the patient's heart rate information and blood pressure information through the heart rate sensor and the blood pressure sensor respectively; Based on a preset patient emotion recognition model, determining a first emotion value of the patient during treatment according to the facial change feature information, the heart rate information, and the blood pressure information; Acquiring a second emotion value of the patient during the treatment process through a patient satisfaction feedback module; A target emotion value is determined according to the first emotion value and the second emotion value.

5. The method according to claim 4, characterized in that The step of obtaining the facial change feature information of the patient through the camera includes: Acquiring the current facial video information of the patient through the camera; Extracting current shape features of key parts of the face from the current face video information, wherein the key parts of the face include nose, eyes, eyebrows, mouth, cheeks and forehead; The facial change feature information is obtained by analyzing the current shape feature and the static shape feature, wherein the static shape feature is the shape feature of the key part of the face collected in advance when the patient is in a calm state.

6. The method according to claim 4, characterized in that After determining the target emotion value according to the first emotion value and the second emotion value, the method further includes: determining a second treatment score according to the target emotion value; A target treatment score is determined according to the first treatment score and the second treatment score.

7. The method according to any one of claims 1 to 6, characterized in that After determining the target operation habit corresponding to the current doctor identifier according to the operation duration and the force control accuracy corresponding to each treatment step, the method further includes: Storing the target operation habit in an operation style database corresponding to the current doctor identification, wherein the operation style database stores a plurality of operation habit data; The operation style type corresponding to the current doctor identification is determined according to the operation habit data in the operation style database.

8. An operation habit classification device, configured in an intelligent dental chair, characterized in that: The smart dental chair includes a variety of matching treatment tools, each of which is equipped with a position sensor and a pressure sensor, and the operation habit classification device includes: a transceiver unit, configured to obtain current usage information of the smart dental chair after the smart dental chair is started, wherein the usage information includes a current doctor identification and a current treatment plan; and to obtain usage information corresponding to each of the treatment tools respectively through position sensors and pressure sensors on each of the treatment tools during the use of the smart dental chair, wherein the usage information includes a usage time, a usage trajectory, and a usage force; A processing unit is used to determine step characteristic information of each treatment step in the current treatment plan according to the usage time, the usage trajectory and the usage force corresponding to each treatment tool, wherein the step characteristic information includes operation duration and force control accuracy; and determine the target operation habit corresponding to the current doctor identification according to the operation duration and the force control accuracy corresponding to each treatment step.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the operation habit classification method based on the smart dental chair according to any one of claims 1 to 7 is implemented.

10. A storage medium, characterized in that: The storage medium stores a computer program, which includes program instructions. When the program instructions are executed by a processor, the processor executes the operation habit classification method based on a smart dental chair as described in any one of claims 1 to 7.

Images