Areache grade identification method and device based on ejection quantity of 3D massage machine core

Abstract

The invention discloses an aching pain grade identification method and device based on the ejection amount of a 3D massage movement, and the method comprises the steps: obtaining the capacitance change of a human body collected in a current movement period of the 3D massage movement, converting the capacitance change to obtain a voltage value at each moment, carrying out the fitting of the voltage value at each moment, and obtaining a fitting line of the voltage value changing with time; the ejection amount of the 3D massage machine core in the current movement period is obtained, and the slope of the ascending section of the fitting line before the moment of the wave crest is calculated in response to the determination that the fitting line has the wave crest and the ejection amount of the 3D massage machine core corresponding to the moment of the wave crest is the maximum value; determining the ache level in the current motion period based on the slope of the ascending section of the fitting line; and repeating the above steps for the same 3D massage machine core of the same massage part to obtain the ache levels in the plurality of motion periods, and performing statistics and filtering processing to obtain the final ache level. According to the invention, the soreness level of massage can be accurately detected, and the anti-interference capability is strong.

Description

Technical Field

[0001] This invention relates to the field of massage detection, specifically to a method and device for identifying the level of soreness based on the amount of pressure exerted by a 3D massage mechanism. Background Technology

[0002] Today, massage devices have increasingly sophisticated requirements for human body detection, needing to collect pain levels from various parts of the body for targeted massage and relaxation. Existing massage products have relatively poor accuracy in detecting pain levels in different body parts; the data varies from person to person, leading to mixed reviews in the market. There is an urgent need to find a unified solution to address the problem of inaccurate pain level detection. Inaccurate pain level detection may be caused by the following factors: 1. Differences due to variations in hand size and grip strength. Current methods may rely on grip strength to assess soreness, but individual hand sizes and grip strength differ, leading to significant errors in this method.

[0003] 2. Differences in body sweat volume due to different ages. Sweating caused by sympathetic nerve activation may be related to stress or body pain. If soreness causes the body to be in a state of stress, it may increase body sweat volume, thus making the method of detecting the degree of soreness by measuring body sweat volume inaccurate. Summary of the Invention

[0004] The purpose of this application is to propose a method and device for identifying the level of soreness based on the amount of 3D massage mechanism ejection, in response to the aforementioned technical problems.

[0005] In a first aspect, the present invention provides a method for identifying the level of soreness based on the amount of pressure exerted by a 3D massage mechanism, comprising the following steps: The capacitance changes of the human body collected during the current motion cycle of the 3D massage mechanism are obtained and converted into voltage values ​​at each moment. The voltage values ​​at each moment are fitted to obtain a fitted line of voltage value change over time. To obtain the ejection amount of the 3D massage mechanism within the current motion cycle, in response to the determination that the fitted line has a peak and the ejection amount of the 3D massage mechanism at the time of the peak is the maximum value, the slope of the rising segment of the fitted line before the time of the peak is calculated. The soreness level within the current exercise cycle is determined based on the slope of the rising segment of the fitted line. The above steps are repeated for the same 3D massage mechanism on the same massage area to obtain the soreness level in multiple exercise cycles. The results are then statistically analyzed and filtered to obtain the final soreness level.

[0006] Preferably, the soreness level within the current exercise cycle is determined based on the slope of the rising segment of the fitted line, specifically including: In response to the slope of the rising segment of the fitted line being less than or equal to a first threshold, the soreness level in the current exercise cycle is determined to be mild. In response to the fact that the slope of the rising segment of the fitted line is greater than the first threshold and less than or equal to the second threshold, the soreness level in the current exercise cycle is determined to be moderate. If the slope of the rising segment of the fitted line is greater than the second threshold, the soreness level in the current exercise cycle is determined to be severe.

[0007] As a preferred method, the statistics include taking the mode.

[0008] Preferably, the filtering process includes: If the current pain level differs from the previous pain level by 2 levels, the final pain level will be set to moderate. If the current pain level is less than 2 levels different from the previous pain level, then the current pain level will be set as the final pain level.

[0009] As a preferred option, it also includes: In response to the determination that the fitted line has a peak and the ejection amount of the 3D massage mechanism at the time of the peak is not at its maximum value, it is determined whether the maximum value of the ejection amount of the 3D massage mechanism is within the time threshold before and after the time of the peak. If so, the fitted line is offset and calibrated so that the ejection amount of the 3D massage mechanism at the time of the peak is at its maximum value, and then the slope of the rising segment of the fitted line before the time of the peak is calculated; otherwise, the slope of the rising segment of the fitted line before the time of the peak is not calculated.

[0010] Preferably, the sampling frequency of the voltage value is the same as that of the ejection amount of the 3D massage mechanism. The voltage value is obtained by a charge-discharge integral CV conversion circuit and filtered after data processing. The formula for calculating the ejection amount of the 3D massage mechanism is as follows: ; in, This represents the ejection volume at time T within the current motion cycle. A coordinate axis is constructed with the starting point of the 3D massage mechanism as the origin, and the direction parallel to the ground is used as... x The axis, with the direction perpendicular to the ground as... y axis, x and y These represent the 3D massage mechanism at time T within the current motion cycle. x shaft and y The coordinates of the axis.

[0011] Secondly, the present invention provides a pain level recognition device based on the amount of pressure exerted by a 3D massage mechanism, comprising: The data processing module is configured to acquire the capacitance changes of the human body collected during the current motion cycle of the 3D massage mechanism and convert them into voltage values ​​at each moment, and to fit the voltage values ​​at each moment to obtain a fitting line of voltage value change over time. The data calculation module is configured to obtain the ejection amount of the 3D massage mechanism within the current motion cycle. In response to determining that there is a peak in the fitted line and that the ejection amount of the 3D massage mechanism at the time of the peak is the maximum value, the module calculates the slope of the rising segment of the fitted line before the time of the peak. The judgment module is configured to determine the level of soreness in the current exercise cycle based on the slope of the rising segment of the fitted line. The pain level determination module is configured to repeat the above steps for the same 3D massage mechanism on the same massage area to obtain the pain level within multiple motion cycles, and perform statistical and filtering processing to obtain the final pain level.

[0012] Thirdly, the present invention provides an electronic device including one or more processors; and a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any implementation of the first aspect.

[0013] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method as described in any of the implementations of the first aspect.

[0014] Fifthly, the present invention provides a computer program product, including a computer program that, when executed by a processor, implements the method as described in any of the implementations in the first aspect.

[0015] Compared with the prior art, the present invention has the following beneficial effects: (1) The pain level identification method based on the ejection amount of the 3D massage mechanism proposed in this invention collects the capacitance change of the human body during the current exercise cycle and converts it into voltage value, and fits the fitting line that changes with time. Then, it combines the ejection amount of the 3D massage mechanism to determine the pain level, which can avoid data abnormalities caused by sweating and other physiological interferences.

[0016] (2) The pain level identification method based on the 3D massage core ejection amount proposed in this invention can simultaneously obtain the pressure value of different pain levels of each part, dynamically analyze the pain intensity, eliminate the data difference caused by the difference in pain tolerance of different people, and has strong adaptability and anti-interference ability.

[0017] (3) The pain level identification method based on the ejection amount of the 3D massage mechanism proposed in this invention uses a statistical method to comprehensively judge the pain level obtained multiple times, and uses filtering processing combined with the pain level obtained in the previous statistical analysis to verify the final pain level. Therefore, the accuracy is very high. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart illustrating a pain level identification method based on the ejection amount of a 3D massage mechanism, according to an embodiment of this application. Figure 2 This is a schematic diagram of the fitting line of the voltage value collected during the massage process versus time in the pain level recognition method based on the ejection amount of the 3D massage mechanism in an embodiment of this application. Figure 3 This is a schematic diagram of the fitting line of the voltage value changing over time when the sensor is not in contact, in the pain level recognition method based on the ejection amount of a 3D massage mechanism according to an embodiment of this application. Figure 4 This is a schematic diagram of a pain level recognition device based on the amount of 3D massage mechanism ejection, according to an embodiment of this application. Figure 5 This is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this invention, and not all of them. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0021] Figure 1 An embodiment of this application illustrates a method for identifying pain levels based on the ejection amount of a 3D massage mechanism, comprising the following steps: S1: Acquire the capacitance changes of the human body collected during the current motion cycle of the 3D massage mechanism and convert them into voltage values ​​at each moment. Fit the voltage values ​​at each moment to obtain a fitting line of voltage value change over time.

[0022] In a specific embodiment, the voltage value is sampled at the same frequency as the ejection amount of the 3D massage mechanism. The voltage value is obtained by a charge-discharge integral CV conversion circuit and is filtered after data processing.

[0023] Specifically, the voltage value in the embodiments of this application can be acquired using a circuit structure such as a charge-discharge integrating CV converter circuit. It reflects the capacitance change generated after the human body comes into contact with the sensor during one motion cycle. The sensor can be an electrode plate in the charge-discharge integrating CV converter circuit. Converting the capacitance change of the human body into an output voltage value requires the use of capacitive sensing technology. The equivalent capacitance of the human body to ground is typically between 50 and 200 picofarads (pF), depending on the environment (such as humidity and contact area) and posture. When the human body approaches or touches the sensor (e.g., with a finger), the capacitance value changes due to the change in electric field distribution. Therefore, an integrator composed of an operational amplifier can be used to convert the capacitance change into a voltage value. The voltage value is sampled at a fixed frequency, so the sampling time is also fixed, such as 50 ms, with one motion cycle being 9 s. In one example, the part of the human body in contact with the sensor can be the hand. In other embodiments, other suitable parts can be selected, and no limitation is made here.

[0024] To ensure the stability of the acquired data, the voltage values ​​obtained by the charge-discharge integrating CV converter circuit need to be processed to filter out abrupt changes and remove noise interference. Specifically, it can be determined whether there are abrupt changes in the voltage values ​​within a continuous time period obtained by the charge-discharge integrating CV converter circuit. If so, the abrupt changes are removed; otherwise, they do not need to be removed.

[0025] In the embodiments of this application, one motion cycle of the 3D massage mechanism refers to a single movement process in which the 3D massage mechanism starts from the starting point (initial retracted position), moves towards the user's body, reaches the maximum ejection amount allowed by its mechanics and program, and then completely retracts to the starting point. In this case, there is one maximum ejection amount in one motion cycle.

[0026] By fitting the collected discrete voltage values ​​with time as the x-axis, a fitting line is obtained, as shown below. Figure 2 As shown, the fitted curve of the voltage values ​​collected during multiple motion cycles of the 3D massage mechanism has multiple peaks. Theoretically, each peak corresponds to the moment when the ejection amount of the 3D massage mechanism reaches its maximum value. Figure 3As shown, when the human body is not in contact with the sensor, the fitted line of the voltage values ​​collected during multiple motion cycles of the 3D massage mechanism is a stable straight line. The fitting method used in the embodiments of this application is discrete data linear fitting, which obtains a fitted line that approximates a curve. By calculating the slope of the rising segment before the peak of this fitted line, the pain level can be determined based on the slope range. Normally, the larger the slope of the fitted line, the weaker the pain tolerance, and the higher the corresponding pain level.

[0027] S2, obtain the ejection amount of the 3D massage mechanism within the current motion cycle. In response to the determination that the fitted line has a peak, and the ejection amount of the 3D massage mechanism at the time of the peak is the maximum value, calculate the slope of the rising segment of the fitted line before the time of the peak.

[0028] In a specific embodiment, the formula for calculating the ejection amount of the 3D massage mechanism is as follows: ; in, This represents the ejection volume at time T within the current motion cycle. A coordinate axis is constructed with the starting point of the 3D massage mechanism as the origin, and the direction parallel to the ground is used as... x The axis, with the direction perpendicular to the ground as... y axis, x and y These represent the 3D massage mechanism at time T within the current motion cycle. x shaft and y The coordinates of the axis.

[0029] Specifically, the embodiments of this application also require simultaneous acquisition of the ejection amount of the 3D massage mechanism within the current motion cycle. The acquisition frequency is consistent with the voltage value acquisition frequency, thus reducing data deviation. The ejection amount of the 3D massage mechanism can be acquired via the serial port of a microcontroller to obtain the data of the 3D massage mechanism during the current motion cycle. x shaft and y The coordinates of the axis are used to calculate the ejection amount of the 3D massage mechanism using the formula above. The 3D massage mechanism mentioned in the embodiments of this application refers to the same 3D massage mechanism used to massage the same part of the human body. Therefore, the current massaged area can also be obtained, which is for the purpose of facilitating statistical analysis and comparison of data from multiple measurements of the same person on the same area.

[0030] Due to real-world factors such as hand sweat or other physiological interference, the peak of the fitted line may not necessarily correspond to the maximum ejection amount of a 3D massage mechanism. Therefore, it is necessary to combine the ejection amount of the 3D massage mechanism with the fitted line of pressure value changing over time to measure the level of soreness felt by the human body under the action of the 3D massage mechanism. When the level of soreness felt by the human body under the action of the 3D massage mechanism reaches its maximum, it indicates that the user is gripping the sensor tightly due to soreness, and the collected pressure value is also the maximum. Therefore, we can first determine whether there is a peak in the fitted line of pressure value changing over time collected in this movement cycle. If there is, it means that the user feels pain under the action of the 3D massage mechanism. We can further determine whether the ejection amount of the 3D massage mechanism at the time of the peak is the maximum value. If so, we calculate the slope of the rising segment of the fitted line before the time of the peak. If there is no peak, it is not necessary to determine whether the ejection amount of the 3D massage mechanism at the time of the peak is the maximum value.

[0031] In specific embodiments, it also includes: In response to the determination that the fitted line has a peak and the ejection amount of the 3D massage mechanism at the time of the peak is not at its maximum value, it is determined whether the maximum value of the ejection amount of the 3D massage mechanism is within the time threshold before and after the time of the peak. If so, the fitted line is offset and calibrated so that the ejection amount of the 3D massage mechanism at the time of the peak is at its maximum value, and then the slope of the rising segment of the fitted line before the time of the peak is calculated; otherwise, the slope of the rising segment of the fitted line before the time of the peak is not calculated.

[0032] Specifically, in order to avoid deviations caused by calculation delays, in the embodiments of this application, the collected voltage value and the ejection amount of the 3D massage mechanism can be temporarily stored in a data chain list, and the calculation of step S2 can be performed after all the data in the motion cycle is acquired.

[0033] Furthermore, due to communication delays and other factors, there may be a discrepancy between the moment when the fitted line showing the pressure value changes over time peaks and the moment corresponding to the maximum ejection amount of the 3D massage mechanism. In other words, the two moments may not be consistent. Specifically, the ejection amount of the 3D massage mechanism may not be at its maximum value at the moment the fitted line shows the peak. If the deviation between the moment of the peak and the moment corresponding to the maximum ejection amount is not significant (i.e., the maximum ejection amount is within the time threshold before and after the peak), then offset calibration can be used to shift the two data points so that the ejection amount at the peak is at its maximum value. Further calculation of the slope of the rising segment of the fitted line before the peak can then resolve the communication delay issue. If the deviation between the moment of the peak and the moment corresponding to the maximum ejection amount is too large, it indicates the presence of other errors, and in this case, it is unnecessary to calculate the slope of the rising segment of the fitted line before the peak.

[0034] S3 determines the soreness level within the current exercise cycle based on the slope of the rising segment of the fitted line.

[0035] In a specific embodiment, step S3 specifically includes: In response to the slope of the rising segment of the fitted line being less than or equal to a first threshold, the soreness level in the current exercise cycle is determined to be mild. In response to the fact that the slope of the rising segment of the fitted line is greater than the first threshold and less than or equal to the second threshold, the soreness level in the current exercise cycle is determined to be moderate. If the slope of the rising segment of the fitted line is greater than the second threshold, the soreness level in the current exercise cycle is determined to be severe.

[0036] Specifically, the first and second thresholds in the embodiments of this application can be obtained through surveys and statistics. In one example, the first threshold in the embodiments of this application can be 0.01, and the second threshold can be 0.5. That is, if the slope of the rising segment of the fitted line before the time of the peak is less than or equal to 0.01, the pain level is determined to be mild; if the slope of the rising segment of the fitted line before the time of the peak is greater than 0.01 and less than or equal to 0.5, the pain level is determined to be moderate; and if the slope of the rising segment of the fitted line before the time of the peak is greater than 0.5, the pain level is determined to be severe.

[0037] S4. Repeat the above steps for the same 3D massage mechanism on the same massage area to obtain the soreness level in multiple motion cycles, and perform statistical and filtering processing to obtain the final soreness level.

[0038] In a specific embodiment, the statistics include taking the mode.

[0039] In a specific embodiment, the filtering process includes: If the current pain level differs from the previous pain level by 2 levels, the final pain level will be set to moderate. If the current pain level is less than 2 levels different from the previous pain level, then the current pain level will be set as the final pain level.

[0040] Specifically, the same 3D massage motor is used to repeatedly perform multiple massage cycles on the same massage area, and the above steps are repeated to obtain the soreness levels within multiple massage cycles. These levels are then statistically analyzed to obtain the final soreness level. In one example, the statistical method used is to take the mode. For example, if the same massage area on the same person is repeatedly massaged by the same 3D massage motor 8 times, 8 soreness levels can be obtained, such as: severe, moderate, severe, severe, moderate, severe, severe, moderate, moderate; taking the mode means selecting the soreness level that occurs most frequently, so the statistically obtained soreness level is severe.

[0041] The same person may experience different levels of soreness under different postures and movements. In order to eliminate data abrupt changes in a certain posture or movement, the embodiments of this application designed a filtering algorithm, which compares the currently obtained soreness level with the previously obtained soreness level.

[0042] Assuming the previous pain level is A and the current pain level is B, if level B differs from level A by 2 levels, it is determined that the posture and movement are incorrect, and the final pain level is moderate. If level B differs from level A by 1 level or is the same, the final pain level is adjusted from level A to level B.

[0043] Further reference Figure 4 As an implementation of the methods shown in the above figures, this application provides an embodiment of a pain level recognition device based on the ejection amount of a 3D massage mechanism. This device embodiment is similar to... Figure 1 Corresponding to the method embodiments shown, this device can be specifically applied to various electronic devices.

[0044] This application provides a pain level recognition device based on the amount of pressure exerted by a 3D massage mechanism, comprising: Data processing module 1 is configured to acquire the capacitance changes of the human body collected during the current motion cycle of the 3D massage mechanism and convert them into voltage values ​​at each moment, fit the voltage values ​​at each moment, and obtain a fitting line of voltage value change over time. Data calculation module 2 is configured to obtain the ejection amount of the 3D massage mechanism within the current motion cycle. In response to determining that there is a peak in the fitted line and that the ejection amount of the 3D massage mechanism at the time of the peak is the maximum value, the slope of the rising segment of the fitted line before the time of the peak is calculated. Module 3 is configured to determine the level of soreness in the current exercise cycle based on the slope of the rising segment of the fitted line. The pain level determination module 4 is configured to repeat the above steps for the same 3D massage mechanism on the same massage area to obtain the pain level within multiple motion cycles, and perform statistical and filtering processing to obtain the final pain level.

[0045] Figure 5 This is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present invention. For example... Figure 5 As shown, the electronic device of this embodiment includes a processor 501 and a memory 502; wherein the memory 502 is used to store computer execution instructions; and the processor 501 is used to execute the computer execution instructions stored in the memory to implement the various steps performed by the electronic device in the above embodiment. For details, please refer to the relevant descriptions in the foregoing method embodiments.

[0046] Alternatively, the memory 502 can be either standalone or integrated with the processor 501.

[0047] When the memory 502 is set up independently, the electronic device also includes a bus 503 for connecting the memory 502 and the processor 501.

[0048] This invention also provides a computer storage medium storing computer execution instructions, which, when executed by processor 501, implement the above method.

[0049] This invention also provides a computer program product, including a computer program that, when executed by a processor 501, implements the above-described method.

[0050] In the embodiments provided by this invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or modules, and may be electrical, mechanical, or other forms.

[0051] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to implement the solution of this embodiment according to actual needs.

[0052] Furthermore, the functional modules in the various embodiments of this invention can be integrated into one processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit. The unit formed by the above modules can be implemented in hardware or in the form of hardware plus software functional units.

[0053] The integrated modules implemented as software functional modules described above can be stored in a computer-readable storage medium. These software functional modules, stored in a storage medium, include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor 501 to execute some steps of the methods of the various embodiments of this application.

[0054] It should be understood that the processor 501 described above can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor, or the processor 501 can be any conventional processor 501. The steps of the method disclosed in this invention can be directly manifested as the hardware processor 501 executing the steps, or as a combination of hardware and software modules within the processor 501 executing the steps.

[0055] The memory 502 may include high-speed RAM memory, and may also include non-volatile memory (NVM), such as disk storage, and may also be a USB flash drive, external hard drive, read-only memory, disk or optical disc, etc.

[0056] Bus 503 can be an Industry Standard Architecture (ISA), a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Bus 503 can be divided into address bus, data bus, control bus, etc. For ease of illustration, the bus 503 in the accompanying drawings of this application is not limited to only one bus 503 or one type of bus 503.

[0057] The aforementioned storage medium can be implemented from any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The storage medium can be any available medium accessible to general-purpose or special-purpose computers.

[0058] An exemplary storage medium is coupled to processor 501, enabling processor 501 to read information from and write information to the storage medium. Alternatively, the storage medium can be an integral part of processor 501. Processor 501 and storage medium can reside in application-specific integrated circuits (ASICs). Alternatively, processor 501 and storage medium can exist as discrete components in an electronic device or host device.

[0059] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0060] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for identifying the level of soreness based on the ejection amount of a 3D massage mechanism, characterized in that, Includes the following steps: The capacitance changes of the human body collected during the current motion cycle of the 3D massage mechanism are obtained and converted into voltage values ​​at each moment. The voltage values ​​at each moment are fitted to obtain a fitted line of voltage value change over time. Obtain the ejection amount of the 3D massage mechanism within the current motion cycle. In response to determining that the fitted line has a peak and that the ejection amount of the 3D massage mechanism at the time of the peak is the maximum value, calculate the slope of the rising segment of the fitted line before the time of the peak. The soreness level within the current exercise cycle is determined based on the slope of the rising segment of the fitted line. The above steps are repeated for the same 3D massage mechanism on the same massage area to obtain the soreness level in multiple exercise cycles. The results are then statistically analyzed and filtered to obtain the final soreness level.

2. The method for identifying pain level based on the ejection amount of a 3D massage mechanism according to claim 1, characterized in that, The soreness level within the current exercise cycle is determined based on the slope of the rising segment of the fitted line, specifically including: In response to determining that the slope of the rising segment of the fitted line is less than or equal to a first threshold, the soreness level in the current exercise cycle is determined to be mild. In response to determining that the slope of the rising segment of the fitted line is greater than a first threshold and less than or equal to a second threshold, the soreness level in the current exercise cycle is determined to be moderate. In response to determining that the slope of the rising segment of the fitted line is greater than a second threshold, the soreness level in the current exercise cycle is determined to be severe.

3. The method for identifying the level of soreness based on the ejection amount of a 3D massage mechanism according to claim 1, characterized in that, The statistics include the mode.

4. The method for identifying the level of soreness based on the ejection amount of a 3D massage mechanism according to claim 3, characterized in that, The filtering process includes: If the current pain level differs from the previous pain level by 2 levels, then the final pain level will be set as moderate. If the current pain level is less than 2 levels different from the previous pain level, then the current pain level will be set as the final pain level.

5. The method for identifying pain level based on the ejection amount of a 3D massage mechanism according to claim 1, characterized in that, Also includes: In response to determining that the fitted line has a peak, and that the ejection amount of the 3D massage mechanism at the time of the peak is not at its maximum value, it is determined whether the maximum value of the ejection amount of the 3D massage mechanism is within the time threshold before and after the time of the peak. If so, the fitted line is offset and calibrated so that the ejection amount of the 3D massage mechanism at the time of the peak is at its maximum value, and then the slope of the rising segment of the fitted line before the time of the peak is calculated; otherwise, the slope of the rising segment of the fitted line before the time of the peak is not calculated.

6. The method for identifying the level of soreness based on the ejection amount of a 3D massage mechanism according to claim 1, characterized in that, The voltage value has the same sampling frequency as the ejection amount of the 3D massage mechanism. The voltage value is obtained by a charge-discharge integral CV conversion circuit and filtered after data processing. The calculation formula for the ejection amount of the 3D massage mechanism is as follows: ； in, This represents the ejection volume at time T within the current motion cycle. A coordinate axis is constructed with the starting point of the 3D massage mechanism as the origin, and the direction parallel to the ground is used as... x The axis, with the direction perpendicular to the ground as... y axis, x and y These represent the 3D massage mechanism at time T within the current motion cycle. x shaft and y The coordinates of the axis.

7. A pain level recognition device based on the ejection amount of a 3D massage mechanism, characterized in that, include: The data processing module is configured to acquire the capacitance changes of the human body collected during the current motion cycle of the 3D massage mechanism and convert them into voltage values ​​at each moment, and to fit the voltage values ​​at each moment to obtain a fitting line of voltage value change over time. The data calculation module is configured to obtain the ejection amount of the 3D massage mechanism within the current motion cycle. In response to determining that the fitted line has a peak and that the ejection amount of the 3D massage mechanism at the time of the peak is the maximum value, the module calculates the slope of the rising segment of the fitted line before the time of the peak. The judgment module is configured to determine the level of soreness in the current exercise cycle based on the slope of the rising segment of the fitted line. The pain level determination module is configured to repeat the above steps for the same 3D massage mechanism on the same massage area to obtain the pain level within multiple motion cycles, and perform statistical and filtering processing to obtain the final pain level.

8. An electronic device, comprising: One or more processors; Storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1-6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1-6.

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