Photoelectric cooperative control health assessment generation method

Abstract

The invention provides a photoelectric cooperative control health assessment generation method, and relates to the field of health assessment, and the method comprises the steps: determining a current assessment model from a preset model library according to a current use part and a current use moment; performing feature extraction on the current change value, determining current change features, performing feature extraction on the frequency change value, determining frequency change features, performing feature extraction on the body surface temperature change value, determining body surface temperature change features, performing feature extraction on the muscle activity change value, and determining muscle activity features; inputting the current change characteristics, the frequency change characteristics, the body surface temperature change characteristics and the muscle activity characteristics to a current evaluation model, and determining a current use evaluation value; and outputting the current health suggestion according to the current use evaluation value. The invention aims to solve the problem of use experience in a cooperative working state of the laser equipment and the intermediate frequency conversion equipment, and provides different health evaluations for different use states so as to improve the use experience of a user.

Description

Technical Field

[0001] The present invention relates to the field of health assessment, and in particular to a health assessment generation method for photoelectric collaborative control. Background Art

[0002] Existing laser equipment and medium frequency conversion equipment are both independently used devices that are individually adjusted and controlled. Laser equipment uses independent current control to achieve the rehabilitation of human body parts, while medium frequency conversion equipment uses independent frequency conversion control to achieve the rehabilitation of human body parts. During independent use, both cannot make real-time adjustments by selecting different usage times and usage cycles according to different usage parts, resulting in limited rehabilitation effects and reduced user experience.

[0003] Due to different usage parts, their sensitivity and tolerance to laser equipment and medium frequency conversion equipment are different. Even if the user can adjust the current output and frequency output during use, these adjustments are made after the user actually feels some discomfort. It is not possible to estimate the current usage status based on the body surface temperature and muscle tension, and it is impossible to give adjustment suggestions in time, thereby increasing the probability of user discomfort and reducing the user experience.

[0004] To sum up, the existing technology cannot give a health assessment based on the user's current usage of the body part during photoelectric collaborative control, and cannot indicate the current adjustment range and frequency adjustment range for the next use. There is currently no technical solution that can solve the above technical problems, and there is no method for generating a health assessment for photoelectric collaborative control. Summary of the invention

[0005] The present invention provides a method for generating a health assessment of optoelectronic collaborative control, which can effectively provide a current usage assessment value and current health advice based on the usage of different parts of the human body when the laser device and the medium frequency conversion device are working in collaboration, so as to find the optimal adjustment range of the current adjustment range and the frequency adjustment range when used next time, avoid usage risks, and improve user experience.

[0006] In a first aspect, the present invention provides a method for generating a health assessment of optoelectronic coordinated control, comprising:

[0007] According to the current use part and the current use time, determine the current evaluation model from the preset model library;

[0008] Extracting features from the current change value to determine the current change feature, extracting features from the frequency change value to determine the frequency change feature, extracting features from the body surface temperature change value to determine the body surface temperature change feature, and extracting features from the muscle activity change value to determine the muscle activity feature, wherein the current change value, the frequency change value, the body surface temperature change value, and the muscle activity change value are determined from the start of use to the current use time;

[0009] Inputting the current change characteristic, the frequency change characteristic, the body surface temperature change characteristic and the muscle activity characteristic into the current evaluation model, and determining the current use evaluation value output by the current evaluation model;

[0010] Upon receiving the user's instruction to end use, or when the current use evaluation value is lower than a preset threshold, the current health advice is output based on the current use evaluation value, and the current health advice is used to indicate the current adjustment range and frequency adjustment range for the next use.

[0011] According to the health assessment generation method for optoelectronic collaborative control provided by the present invention, the preset model library includes a first assessment model, a second assessment model, a third assessment model, a fourth assessment model, a fifth assessment model, a sixth assessment model, a seventh assessment model, an eighth assessment model, and a ninth assessment model;

[0012] The current evaluation model is determined from a preset model library according to the current use part and the current use time, including:

[0013] When the current use part is the neck and the current use moment is at the beginning stage of use, the current evaluation model is determined to be the first evaluation model from the preset model library; when the current use part is the neck and the current use moment is at the middle stage of use, the current evaluation model is determined to be the second evaluation model from the preset model library; when the current use part is the neck and the current use moment is at the end stage of use, the current evaluation model is determined to be the third evaluation model from the preset model library;

[0014] When the current use part is the waist and the current use time is at the beginning stage of use, the current evaluation model is determined to be the fourth evaluation model from the preset model library; when the current use part is the waist and the current use time is at the middle stage of use, the current evaluation model is determined to be the fifth evaluation model from the preset model library; when the current use part is the waist and the current use time is at the end stage of use, the current evaluation model is determined to be the sixth evaluation model from the preset model library;

[0015] When the current use part is the limbs and the current use time is in the beginning stage of use, the current evaluation model is determined from the preset model library as the seventh evaluation model; when the current use part is the limbs and the current use time is in the middle stage of use, the current evaluation model is determined from the preset model library as the eighth evaluation model; when the current use part is the limbs and the current use time is in the ending stage of use, the current evaluation model is determined from the preset model library as the ninth evaluation model.

[0016] According to the method for generating a health assessment of optoelectronic coordinated control provided by the present invention, before inputting the current change characteristic, the frequency change characteristic, the body surface temperature change characteristic, and the muscle activity characteristic into the current assessment model, the method further includes:

[0017] Obtain sample current change characteristics, sample frequency change characteristics, sample body surface temperature change characteristics, and sample muscle activity characteristics at different usage locations and different usage durations, and obtain sample evaluation values ​​at each usage location and each usage duration, wherein the sample evaluation values ​​are determined based on user ratings and preset evaluation system ratings;

[0018] Construct a sample data set according to the sample current change characteristics, sample frequency change characteristics, sample body surface temperature change characteristics and sample muscle activity characteristics at different usage parts and different usage durations, and the sample evaluation values ​​at each usage part and each usage duration, wherein the sample data set includes a sample training set and a sample test set;

[0019] Divide the sample data set according to different usage parts and different usage durations to obtain sample data sets corresponding to different evaluation models;

[0020] For each sample data set, the initial evaluation model is trained according to the sample training set, and the initial evaluation model is updated and iterated according to the sample test set and the preset loss function, the target evaluation model is determined, all sample data sets are traversed, all target evaluation models are determined, and the preset model library is constructed according to all target evaluation models.

[0021] According to the method for generating a health assessment of optoelectronic coordinated control provided by the present invention, after determining the current assessment model from the preset model library, the method further includes:

[0022] The output current of the laser device is read to determine the current change value, wherein the output current of the laser device is determined in the process of use from the start of use to the current use time according to the user's real-time adjustment of the laser device;

[0023] The frequency change value is determined by reading the output frequency of the intermediate frequency conversion device, wherein the output frequency of the intermediate frequency conversion device is determined in real time according to the user adjusting the intermediate frequency conversion device during the use process from the start of use to the current use time;

[0024] Reading a temperature sensor disposed on the body surface to determine a change value of the body surface temperature;

[0025] Read the electromyographic sensor installed on the body surface to determine the change value of muscle activity.

[0026] According to the method for generating a health assessment of optoelectronic coordinated control provided by the present invention, the current change value includes a current value corresponding to each reading moment in a time series, and the feature extraction of the current change value to determine the current change feature includes:

[0027] Normalizing each current value in the time series to obtain all normalized current values;

[0028] For each normalized current value, calculating a time difference between the normalized current value and a normalized current value corresponding to a previous moment, and determining the time difference as a current change value;

[0029] All normalized current values ​​are traversed, all current change values ​​are determined, and all current change values ​​are determined as current change features.

[0030] According to the method for generating a health assessment of optoelectronic coordinated control provided by the present invention, the frequency change value includes a frequency value corresponding to each reading moment in the time series, and the feature extraction of the frequency change value to determine the frequency change feature includes:

[0031] Normalizing each frequency value in the time series to obtain all normalized frequency values;

[0032] For each normalized frequency value, calculating a frequency difference between the normalized frequency value and a normalized frequency value corresponding to a previous moment, and determining the frequency difference as a frequency change value;

[0033] All normalized frequency values ​​are traversed, all frequency change values ​​are determined, and all frequency change values ​​are determined as frequency change features.

[0034] According to the method for generating a health assessment of optoelectronic coordinated control provided by the present invention, the body surface temperature change value includes a body surface temperature value corresponding to each reading moment in the time series, and the feature extraction of the body surface temperature change value to determine the body surface temperature change feature includes:

[0035] For each body surface temperature value, determine a dimensional feature value corresponding to the body surface temperature value, the dimensional feature value includes a first dimensional feature value and a second dimensional feature value, wherein, when the body surface temperature value is greater than a preset temperature threshold, the body surface temperature value is determined to be an abnormal temperature value, and the first dimensional feature value is marked; otherwise, the second dimensional feature value is marked;

[0036] Normalizing each body surface temperature value in the time series to obtain all normalized body surface temperature values, and for each normalized body surface temperature value, calculating a body surface temperature difference between the normalized body surface temperature value and a normalized body surface temperature value corresponding to a previous moment, and determining the body surface temperature difference as a body surface temperature change value;

[0037] Traverse all normalized body surface temperature values, determine all body surface temperature change values, splice the body surface temperature change values ​​and dimensional feature values ​​corresponding to each moment, obtain the spliced ​​body surface temperature feature corresponding to each moment, and determine each spliced ​​body surface temperature feature corresponding to all moments as the body surface temperature change feature.

[0038] According to the method for generating a health assessment of optoelectronic coordinated control provided by the present invention, the muscle activity change value includes the electromyographic signal values ​​corresponding to all sampling time points in the time series, and the feature extraction of the muscle activity change value to determine the muscle activity feature includes:

[0039] For each electromyographic signal value, convert the electromyographic signal value into an electromyographic numerical value;

[0040] Determine the root mean square value of the electromyographic signal value corresponding to the sampling time point in the preset time window corresponding to each moment, which is used to characterize the degree of muscle tension, wherein the preset time window is determined after dividing the time series, and the preset time window is the time difference between the current moment and the previous moment;

[0041] Normalizing the root mean square values ​​in the time series to obtain all normalized root mean square values;

[0042] For each normalized root mean square value, calculating a root mean square value difference between the normalized root mean square value and a normalized root mean square value corresponding to a previous moment, and determining the root mean square value difference as a root mean square value change value;

[0043] All normalized root mean square values ​​are traversed, all root mean square value change values ​​are determined, and all root mean square value change values ​​are determined as muscle activity characteristics.

[0044] According to the method for generating a health assessment for optoelectronic coordinated control provided by the present invention, outputting the current health advice according to the current use assessment value includes:

[0045] Determine, according to the current use location, a preset current adjustment limit value and a preset frequency adjustment limit value corresponding to the current use location;

[0046] Determine the target current adjustment limit value corresponding to the current use part according to the current use evaluation value and the preset current adjustment limit value, and determine the target frequency adjustment limit value corresponding to the current use part according to the current use evaluation value and the preset frequency adjustment limit value;

[0047] The current health advice is generated according to the target current adjustment limit and the target frequency adjustment limit.

[0048] According to the method for generating a health assessment of optoelectronic coordinated control provided by the present invention, determining the target current regulation limit value corresponding to the current use part according to the current use assessment value and the preset current regulation limit value includes:

[0049]

[0050] Among them, I s is the target current regulation limit, I b is the preset current regulation limit, V is the current usage evaluation value, ranging from 1 to 10, and k is the first preset coefficient, ranging from 1 to 10;

[0051] The determining the target frequency adjustment limit value corresponding to the current use part according to the current use evaluation value and the preset frequency adjustment limit value includes:

[0052]

[0053] Among them, F s is the target frequency adjustment limit, F b is the preset frequency adjustment limit, p is the second preset coefficient, and its value ranges from 1 to 10.

[0054] The present invention aims to solve the user experience problem existing in the collaborative working state of laser equipment and medium frequency conversion equipment. Taking into account the different initial current adjustment ranges and initial frequency adjustment ranges in different use parts, and further considering the fact that the human body's adaptability to current and frequency will change over time, nine corresponding evaluation models are designed. Different evaluation models are used for evaluation of different parts and different use cycles, thereby greatly improving the evaluation capability of health evaluation.

[0055] The present invention can not only combine the current, frequency, temperature and electromyographic signals obtained during use to perform data analysis and processing, but also give different health reference suggestions according to the different sensitivity and tolerance of different use parts, so as to find the best adjustment range of the current adjustment range and the frequency adjustment range when using it next time, avoid use risks, and improve user experience;

[0056] The present invention can also determine the corresponding preset current adjustment limit and preset frequency adjustment limit according to the current usage part, and then determine the target current adjustment limit corresponding to the current usage part according to the current usage evaluation value and the preset current adjustment limit, and determine the target frequency adjustment limit corresponding to the current usage part according to the current usage evaluation value and the preset frequency adjustment limit, thereby realizing different adjustment range control for different usage parts, and further realizing refined control processing of current and frequency regulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0058] Figure 1 It is a flow chart of the method for generating a health assessment of optoelectronic coordinated control provided by the present invention;

[0059] Figure 2 It is a structural schematic diagram of a health assessment generating device for optoelectronic coordinated control provided by the present invention;

[0060] Figure 3 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0061] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0062] Figure 1 It is one of the flow charts of the method for generating a health assessment of optoelectronic coordinated control provided by the present invention, and the method for generating a health assessment of optoelectronic coordinated control includes:

[0063] Step 101: Determine a current evaluation model from a preset model library according to the current use location and the current use time;

[0064] Step 102, extracting features from the current change value to determine the current change feature, extracting features from the frequency change value to determine the frequency change feature, extracting features from the body surface temperature change value to determine the body surface temperature change feature, and extracting features from the muscle activity change value to determine the muscle activity feature, wherein the current change value, the frequency change value, the body surface temperature change value, and the muscle activity change value are determined from the start of use to the current use time;

[0065] Step 103, inputting the current change characteristic, the frequency change characteristic, the body surface temperature change characteristic and the muscle activity characteristic into the current evaluation model, and determining the current use evaluation value output by the current evaluation model;

[0066] Step 104: upon receiving the user's instruction to end use, or when the current use evaluation value is lower than a preset threshold, output current health advice based on the current use evaluation value, wherein the current health advice is used to indicate a current adjustment range and a frequency adjustment range for the next use.

[0067] In step 101, the system first identifies the site of action of the current device, such as the neck, waist, limbs, etc., and also identifies the time of use of the current device, such as the beginning, middle or end of use. Based on this information, the system retrieves and matches the most appropriate assessment model from the preset model library. The preset model library may contain multiple models for different parts and different use stages. These models have been trained and can output accurate health assessments for specific situations. Step 101 can improve the pertinence and accuracy of the assessment because the system can select the appropriate model according to the specific use site and use time, while reducing the complexity of manual model selection and improving efficiency.

[0068] Optionally, after determining the current evaluation model from the preset model library, the method further includes:

[0069] The output current of the laser device is read to determine the current change value, wherein the output current of the laser device is determined in the process of use from the start of use to the current use time according to the user's real-time adjustment of the laser device;

[0070] The frequency change value is determined by reading the output frequency of the intermediate frequency conversion device, wherein the output frequency of the intermediate frequency conversion device is determined in real time according to the user adjusting the intermediate frequency conversion device during the use process from the start of use to the current use time;

[0071] Reading a temperature sensor disposed on the body surface to determine a change value of the body surface temperature;

[0072] Read the electromyographic sensor installed on the body surface to determine the change value of muscle activity.

[0073] Optionally, after determining the current evaluation model, the system reads the output current value of the laser device from the beginning of use to the current moment. This current value is determined after the user adjusts the laser device in real time during use, reflecting the adjustments made by the user based on usage experience and usage needs; the system also reads the output frequency value of the medium frequency conversion device from the beginning of use to the current moment. This frequency value is also determined after the user adjusts the medium frequency conversion device in real time, reflecting the user's personalized needs for different usage stages and usage effects; by means of a temperature sensor set on the body surface, the system can obtain the change value of the body surface temperature in real time; the electromyography sensor is set on the body surface to detect the change value of muscle activity, which can reflect the reaction and state of the muscle during use, and provide an important basis for health assessment. The present invention reads the output parameters (current and frequency) of the laser device and the medium frequency conversion device in real time, so that the system can more accurately reflect the actual needs and usage effects of the user during use. At the same time, combined with the changes in body surface temperature and muscle activity, the system can more comprehensively evaluate the health status and usage response of the human body in subsequent mode applications. By reading these real-time adjusted parameters, the system can provide users with more accurate health assessments and usage recommendations. By real-time monitoring of changes in body surface temperature and muscle activity, the system can promptly discover and adjust usage strategies to avoid over-stimulation or under-stimulation, providing more comprehensive and accurate data support for the health assessment generation method of optoelectronic collaborative control.

[0074] Optionally, the preset model library includes a first evaluation model, a second evaluation model, a third evaluation model, a fourth evaluation model, a fifth evaluation model, a sixth evaluation model, a seventh evaluation model, an eighth evaluation model, and a ninth evaluation model;

[0075] The current evaluation model is determined from a preset model library according to the current use part and the current use time, including:

[0076] When the current use part is the neck and the current use moment is at the beginning stage of use, the current evaluation model is determined to be the first evaluation model from the preset model library; when the current use part is the neck and the current use moment is at the middle stage of use, the current evaluation model is determined to be the second evaluation model from the preset model library; when the current use part is the neck and the current use moment is at the end stage of use, the current evaluation model is determined to be the third evaluation model from the preset model library;

[0077] When the current use part is the waist and the current use time is at the beginning stage of use, the current evaluation model is determined to be the fourth evaluation model from the preset model library; when the current use part is the waist and the current use time is at the middle stage of use, the current evaluation model is determined to be the fifth evaluation model from the preset model library; when the current use part is the waist and the current use time is at the end stage of use, the current evaluation model is determined to be the sixth evaluation model from the preset model library;

[0078] When the current use part is the limbs and the current use time is in the beginning stage of use, the current evaluation model is determined from the preset model library as the seventh evaluation model; when the current use part is the limbs and the current use time is in the middle stage of use, the current evaluation model is determined from the preset model library as the eighth evaluation model; when the current use part is the limbs and the current use time is in the ending stage of use, the current evaluation model is determined from the preset model library as the ninth evaluation model.

[0079] Optionally, the preset model library is refined into nine evaluation models, which are trained and optimized for different usage parts and usage stages. Different evaluation models use different training samples. Each evaluation model is specially trained for its specific usage part and usage stage to more accurately evaluate the health status and usage effect in that situation, so that the system can select the most matching evaluation model from the preset model library according to the current usage part and usage stage. For example, if the current usage part is the neck and it is in the initial stage of use, the first evaluation model is selected; if the current usage part is the waist and it is in the middle stage of use, the fifth evaluation model is selected.

[0080] Optionally, by refining the preset model library, each assessment model can be more focused on its specific usage location and usage phase, thereby improving the accuracy of the assessment. With the continuous accumulation of data and the continuous development of technology, each assessment model can be iterated and optimized to further improve the accuracy and reliability of the assessment.

[0081] Optionally, before inputting the current change characteristic, the frequency change characteristic, the body surface temperature change characteristic, and the muscle activity characteristic into the current evaluation model, the method further includes:

[0082] Obtain sample current change characteristics, sample frequency change characteristics, sample body surface temperature change characteristics, and sample muscle activity characteristics at different usage locations and different usage durations, and obtain sample evaluation values ​​at each usage location and each usage duration, wherein the sample evaluation values ​​are determined based on user ratings and preset evaluation system ratings;

[0083] Construct a sample data set according to the sample current change characteristics, sample frequency change characteristics, sample body surface temperature change characteristics and sample muscle activity characteristics at different usage parts and different usage durations, and the sample evaluation values ​​at each usage part and each usage duration, wherein the sample data set includes a sample training set and a sample test set;

[0084] Divide the sample data set according to different usage parts and different usage durations to obtain sample data sets corresponding to different evaluation models;

[0085] For each sample data set, the initial evaluation model is trained according to the sample training set, and the initial evaluation model is updated and iterated according to the sample test set and the preset loss function, the target evaluation model is determined, all sample data sets are traversed, all target evaluation models are determined, and the preset model library is constructed according to all target evaluation models.

[0086] This embodiment specifically describes the process of constructing the preset model library. Specifically, the present invention comprehensively considers the current change characteristics, frequency change characteristics, body surface temperature change characteristics and muscle activity characteristics to accurately evaluate the use effect and user experience of the optoelectronic collaborative device, and pre-constructs a model for constructing and training multiple evaluation models specific to different usage parts and usage durations. In the data collection stage, the current change characteristics, frequency change characteristics, body surface temperature change characteristics and muscle activity characteristics in different usage parts (such as arms, legs, back, etc.) and different usage durations (such as short time, medium time, long time) are collected, and sample evaluation values ​​are obtained for each usage part and each usage duration. These evaluation values ​​are based on user scores and preset evaluation system evaluations. The method is comprehensively determined, reflecting the user's satisfaction or effect evaluation of the use of the device. The collected feature data and evaluation values ​​are combined into a sample data set, including a sample training set for training and a sample test set for testing. According to the different use sites and use durations, the sample data set is further divided into multiple subsets, each subset corresponds to a specific evaluation model. In the model training and update stage, for each sample data set, the initial evaluation model is trained using its sample training set, and the model is updated and iterated according to the sample test set and the preset loss function to minimize the prediction error, thereby determining the target evaluation model, traversing all sample data sets, determining a target evaluation model for each subset, and finally constructing a preset model library containing multiple target evaluation models. The present invention can more accurately evaluate the use effect or user experience of the device by comprehensively considering multiple physiological characteristics and use conditions. Since the model is trained according to different use sites and use durations, it can provide personalized evaluation results to meet the needs and preferences of different users.

[0087] In step 102, the present invention obtains the current change value, frequency change value, body surface temperature change value and muscle activity change value from the sensor module, and performs feature extraction on the above-obtained data, including calculating statistical features such as average value, standard deviation, maximum value, minimum value, and other possible complex features, such as trend and periodicity in time series analysis, to extract useful feature information from the original data and provide input for the subsequent evaluation model. Since the current change value, frequency change value, body surface temperature change value and muscle activity change value are determined from the start of use to the current use time, the acquired data will be used as data input to match the current evaluation model.

[0088] Optionally, the current change value includes a current value corresponding to each reading moment in the time series, and the feature extraction of the current change value to determine the current change feature includes:

[0089] Normalizing each current value in the time series to obtain all normalized current values;

[0090] For each normalized current value, calculating a time difference between the normalized current value and a normalized current value corresponding to a previous moment, and determining the time difference as a current change value;

[0091] All normalized current values ​​are traversed, all current change values ​​are determined, and all current change values ​​are determined as current change features.

[0092] Optionally, the present invention normalizes each current value in the time series. Normalization is a common data preprocessing technology, which can convert data of different magnitudes or ranges to the same magnitude or range to facilitate subsequent processing and analysis. All current values ​​are converted into normalized current values, which are between 0 and 1, thereby eliminating the magnitude differences between the original current values. For each normalized current value, the time difference between it and the corresponding normalized current value at the previous moment is calculated, and the time difference reflects the change in the current value between adjacent moments. All normalized current values ​​are traversed, and the above-mentioned step of calculating the time difference is performed for each normalized current value to obtain all current change values. Finally, these current change values ​​are determined as current change characteristics to reflect the change trend and fluctuation of the current value in the entire time series.

[0093] Optionally, the frequency change value includes a frequency value corresponding to each reading moment in the time series, and the feature extraction of the frequency change value to determine the frequency change feature includes:

[0094] Normalizing each frequency value in the time series to obtain all normalized frequency values;

[0095] For each normalized frequency value, calculating a frequency difference between the normalized frequency value and a normalized frequency value corresponding to a previous moment, and determining the frequency difference as a frequency change value;

[0096] All normalized frequency values ​​are traversed, all frequency change values ​​are determined, and all frequency change values ​​are determined as frequency change features.

[0097] Optionally, similar to the processing method of current change characteristics, each frequency value in the time series is normalized, and for each normalized frequency value, the frequency difference between it and the corresponding normalized frequency value at the previous moment is calculated to reflect the change in frequency over time, that is, the frequency change value. By calculating the frequency difference, the dynamic change of frequency in the time series can be captured, which is of great significance for analyzing the working status of the equipment in different time periods. All normalized frequency values ​​are traversed, all frequency change values ​​are determined, and all frequency change values ​​are used as frequency change characteristics. The present invention can accurately capture the dynamic change of frequency in the time series through feature extraction, and provide strong data support for the model input of subsequent frequency characteristics.

[0098] Optionally, the body surface temperature change value includes a body surface temperature value corresponding to each reading time in the time series, and the feature extraction of the body surface temperature change value to determine the body surface temperature change feature includes:

[0099] For each body surface temperature value, determine a dimensional feature value corresponding to the body surface temperature value, the dimensional feature value includes a first dimensional feature value and a second dimensional feature value, wherein, when the body surface temperature value is greater than a preset temperature threshold, the body surface temperature value is determined to be an abnormal temperature value, and the first dimensional feature value is marked; otherwise, the second dimensional feature value is marked;

[0100] Normalizing each body surface temperature value in the time series to obtain all normalized body surface temperature values, and for each normalized body surface temperature value, calculating a body surface temperature difference between the normalized body surface temperature value and a normalized body surface temperature value corresponding to a previous moment, and determining the body surface temperature difference as a body surface temperature change value;

[0101] Traverse all normalized body surface temperature values, determine all body surface temperature change values, splice the body surface temperature change values ​​and dimensional feature values ​​corresponding to each moment, obtain the spliced ​​body surface temperature feature corresponding to each moment, and determine each spliced ​​body surface temperature feature corresponding to all moments as the body surface temperature change feature.

[0102] Optionally, for each body surface temperature value in the time series, first determine whether it is greater than a preset temperature threshold. If it is greater than the preset temperature threshold, the body surface temperature value is considered to be an abnormal temperature value and is marked as a first dimension characteristic value. If it is not greater than the preset temperature threshold, it is marked as a second dimension characteristic value. Then, each body surface temperature value in the time series is normalized. The normalized body surface temperature value will be used for subsequent calculation of the body surface temperature change value. For each body surface temperature value after normalization, calculate the difference between it and the normalized body surface temperature value corresponding to the previous moment to obtain the body surface temperature change value. Traverse all normalized body surface temperature values ​​to determine all body surface temperature change values. The body surface temperature change value corresponding to each moment is spliced ​​with the previously determined dimensional characteristic value to obtain the spliced ​​body surface temperature feature corresponding to each moment. The spliced ​​body surface temperature features corresponding to all moments together constitute the body surface temperature change feature.

[0103] Optionally, the muscle activity change value includes electromyographic signal values ​​corresponding to all sampling time points in the time series, and the feature extraction of the muscle activity change value to determine the muscle activity feature includes:

[0104] For each electromyographic signal value, convert the electromyographic signal value into an electromyographic numerical value;

[0105] Determine the root mean square value of the electromyographic signal value corresponding to the sampling time point in the preset time window corresponding to each moment, which is used to characterize the degree of muscle tension, wherein the preset time window is determined after dividing the time series, and the preset time window is the time difference between the current moment and the previous moment;

[0106] Normalizing the root mean square values ​​in the time series to obtain all normalized root mean square values;

[0107] For each normalized root mean square value, calculating a root mean square value difference between the normalized root mean square value and a normalized root mean square value corresponding to a previous moment, and determining the root mean square value difference as a root mean square value change value;

[0108] All normalized root mean square values ​​are traversed, all root mean square value change values ​​are determined, and all root mean square value change values ​​are determined as muscle activity characteristics.

[0109] Optionally, for each EMG signal value in the time series, convert it into an EMG numerical value to ensure the accuracy and consistency of subsequent analysis. Then, determine the root mean square (RMS) value of the EMG signal value corresponding to the sampling time point in the preset time window at each moment. The root mean square value is a commonly used signal processing method used to characterize the energy or intensity of the signal. Here it is used to characterize the degree of muscle tension. The preset time window is determined after dividing the time series. It represents the time difference between the current moment and the previous moment. The root mean square values ​​in the time series are normalized to obtain all normalized root mean square values. For each normalized root mean square value, calculate its root mean square value difference with the normalized root mean square value corresponding to the previous moment. This difference is determined as the root mean square value change value. Traverse all normalized root mean square values, determine all root mean square value change values, and determine these change values ​​as muscle activity characteristics to reflect the dynamic changes of muscle activity, so as to provide strong data support for the model input of subsequent muscle activity characteristics.

[0110] In step 103, during the use process, as time goes by, the degree of adaptation of the human body to the medium frequency current will change. Therefore, it is necessary to adjust the frequency according to the use time to maintain the use effect. For example, at the beginning of use, a lower frequency is used, and the frequency is gradually increased so that the human body gradually adapts to the stimulation of the medium frequency current; in the middle stage of use, a certain frequency is maintained, and fine-tuning is performed according to the physiological parameters detected by the sensor module to achieve the best use effect; at the end of use, the frequency is gradually reduced so that the human body gradually returns to a normal state. In another optional embodiment, in different use cycles, the physiological state of the human body and the reaction to the medium frequency current will also be different, so it is necessary to adjust the frequency according to the use cycle to adapt to the changes of the human body, for example, in the early stage of use, a lower frequency and a smaller current intensity are used, and the frequency and current intensity are gradually increased so that the human body gradually adapts to the stimulation of the medium frequency current; in the middle stage of use, a certain frequency and current intensity are maintained, and fine-tuning is performed according to the physiological parameters detected by the sensor module to achieve the best use effect; in the later stage of use, the frequency and current intensity are gradually reduced so that the human body gradually returns to a normal state.

[0111] Precisely because of the above situation, in step 103, the present invention inputs the current change characteristics, the frequency change characteristics, the body surface temperature change characteristics and the muscle activity characteristics extracted in step 102 into the current evaluation model determined in step 101. The evaluation model performs calculations based on the input characteristics and outputs a current usage evaluation value. The current usage evaluation value can be a numerical value representing a health status or a classification label. The current usage evaluation value is automatically evaluated according to the usage time, usage cycle and usage site, thereby realizing the adjustment of the frequency and current limit values, so as to better adapt to the physiological changes of the human body and improve the usage effect.

[0112] In another optional embodiment, the present invention can also adopt a method of gradually increasing and decreasing the frequency, which can reduce the human body's discomfort with the medium frequency current and improve user comfort. As the use time goes by and the use cycle changes, the frequency can be changed automatically or under the adjustment of the user, and adapt to the physiological reactions of the human body at different use stages in real time. At the beginning of use, a low frequency can allow the user to gradually adapt to the use process and reduce discomfort; as use progresses, the frequency is gradually increased to enhance the use effect; at the end of use, the frequency is reduced to allow the body to recover smoothly. This dynamic adjustment ensures the accuracy and safety of use.

[0113] Similarly, for laser equipment, adjusting the current according to the usage cycle can enable precise use according to the physiological changes of the human body at different stages. In the early stage of use, a smaller current intensity can help users gradually adapt to use; in the middle stage of use, a stable current intensity can continue to play a role; in the later stage of use, gradually reducing the current intensity will help consolidate the use effect.

[0114] In step 104, when the user's instruction to end use is received or the current use evaluation value is lower than a preset threshold, the system generates a current health recommendation based on the current use evaluation value. Optionally, when the user's instruction to end use is received, it is considered that the user has stopped using the device. In order to enable the user to obtain a better use experience the next time the device is used, the present invention will trigger the generation of the current health recommendation. When it is determined that the current use evaluation value is lower than the preset threshold, it is considered that the user is experiencing an uncomfortable use experience, or will experience an uncomfortable use experience if the device is continued to be used. At this time, the generation of the current health recommendation will also be triggered. The health recommendation may include the current adjustment range, frequency adjustment range and other possible suggestions for the next use, such as increasing the use time, changing the use site, etc. The health recommendation provides users with personalized guidance to help them better utilize the optoelectronic collaboratively controlled device, and then adjust the use parameters to adapt to the physiological changes and needs of different users, thereby improving the use effect and user experience.

[0115] The present invention can automatically adjust to the most suitable initial frequency range for different parts of the body according to the different parts of the body, taking into full account the differences in sensitivity of various parts of the body to the medium-frequency current, and realizing truly personalized use. For example, for the more sensitive neck and waist, a lower initial frequency range is used to avoid discomfort caused by excessive stimulation; while for the limbs with relatively high tolerance, a higher initial frequency range can be used to achieve better use effects.

[0116] Optionally, outputting the current health advice according to the current usage evaluation value includes:

[0117] Determine, according to the current use location, a preset current adjustment limit value and a preset frequency adjustment limit value corresponding to the current use location;

[0118] Determine the target current adjustment limit value corresponding to the current use part according to the current use evaluation value and the preset current adjustment limit value, and determine the target frequency adjustment limit value corresponding to the current use part according to the current use evaluation value and the preset frequency adjustment limit value;

[0119] The current health advice is generated according to the target current adjustment limit and the target frequency adjustment limit.

[0120] Optionally, different parts of use have different sensitivities to medium-frequency current, so it is necessary to determine the initial frequency range according to the part of use. For example, for sensitive parts such as the neck and waist, a lower initial frequency range can be used; for parts such as the limbs, a higher initial frequency range can be used. According to the current part of use, the preset current adjustment limit and the preset frequency adjustment limit corresponding to the part are determined. These preset limits are set based on the sensitivity of different parts to medium-frequency current and safety considerations. According to the current use evaluation value and the preset current adjustment limit, the target current adjustment limit corresponding to the current part of use is determined. Similarly, according to the current use evaluation value and the preset frequency adjustment limit, the target frequency adjustment limit corresponding to the current part of use is determined. Finally, according to the determined target current adjustment limit and target frequency adjustment limit, the current health advice is generated.

[0121] Optionally, determining the target current regulation limit value corresponding to the current use part according to the current use evaluation value and a preset current regulation limit value includes:

[0122]

[0123] Among them, I s is the target current regulation limit, I b is the preset current regulation limit, V is the current usage evaluation value, ranging from 1 to 10, and k is the first preset coefficient, ranging from 1 to 10;

[0124] The determining the target frequency adjustment limit value corresponding to the current use part according to the current use evaluation value and the preset frequency adjustment limit value includes:

[0125]

[0126] Among them, F s is the target frequency adjustment limit, F b is the preset frequency adjustment limit, p is the second preset coefficient, and its value ranges from 1 to 10.

[0127] Optionally, when the current use evaluation value is getting larger and larger, it is considered that the user's predicted experience is good, and the amplitude of the preset current adjustment limit is adjusted to a smaller value. When the current use evaluation value is getting smaller and smaller, it is considered that the user's predicted experience is poor, and the amplitude of the preset current adjustment limit is adjusted to a larger value. Similarly, when the current use evaluation value is getting larger and larger, it is considered that the user's predicted experience is good, and the amplitude of the preset frequency adjustment limit is adjusted to a smaller value. When the current use evaluation value is getting smaller and smaller, it is considered that the user's predicted experience is poor, and the amplitude of the preset frequency adjustment limit is adjusted to a larger value. By dynamically adjusting the adjustment limits of current and frequency, the needs of different use stages and use parts can be more accurately adapted. Dynamic adjustment can also ensure that the best use effect is always maintained during use, avoiding the problem of poor user experience caused by excessive stimulation.

[0128] The present invention aims to solve the user experience problem existing in the collaborative working state of laser equipment and medium frequency conversion equipment. Taking into account the different initial current adjustment ranges and initial frequency adjustment ranges in different use parts, and further considering the fact that the human body's adaptability to current and frequency will change over time, nine corresponding evaluation models are designed. Different evaluation models are used for evaluation of different parts and different use cycles, thereby greatly improving the evaluation capability of health evaluation.

[0129] The present invention can not only combine the current, frequency, temperature and electromyographic signals obtained during use to perform data analysis and processing, but also give different health reference suggestions according to the different sensitivity and tolerance of different use parts, so as to find the best adjustment range of the current adjustment range and the frequency adjustment range when using it next time, avoid use risks, and improve user experience;

[0130] The present invention can also determine the corresponding preset current adjustment limit and preset frequency adjustment limit according to the current usage part, and then determine the target current adjustment limit corresponding to the current usage part according to the current usage evaluation value and the preset current adjustment limit, and determine the target frequency adjustment limit corresponding to the current usage part according to the current usage evaluation value and the preset frequency adjustment limit, thereby realizing different adjustment range control for different usage parts, and further realizing refined control processing of current and frequency regulation.

[0131] Figure 2 It is a structural schematic diagram of the optoelectronic collaboratively controlled health assessment generation device provided by the present invention, and the optoelectronic collaboratively controlled health assessment generation device includes a determination unit 1, and the determination unit 1 is used to determine the current assessment model from a preset model library according to the current usage part and the current usage time. The working principle of the determination unit 1 can refer to the aforementioned step 101 and will not be repeated here.

[0132] The photoelectric collaborative control health assessment generation device includes an extraction unit 2, which is used to perform feature extraction on the current change value to determine the current change characteristics, perform feature extraction on the frequency change value to determine the frequency change characteristics, perform feature extraction on the body surface temperature change value to determine the body surface temperature change characteristics, perform feature extraction on the muscle activity change value to determine the muscle activity characteristics, wherein the current change value, the frequency change value, the body surface temperature change value and the muscle activity change value are determined from the start of use to the current use time. The working principle of the extraction unit 2 can refer to the aforementioned step 102 and will not be repeated here.

[0133] The photoelectric collaborative control health assessment generation device also includes an input unit 3, which is used to input the current change characteristics, the frequency change characteristics, the body surface temperature change characteristics and the muscle activity characteristics into the current assessment model to determine the current use assessment value output by the current assessment model. The working principle of the input unit 3 can refer to the aforementioned step 103 and will not be repeated here.

[0134] The photoelectric collaborative control health assessment generation device also includes an indication unit 4, which is used to output current health advice based on the current usage evaluation value when receiving the user's end-of-use instruction or when the current usage evaluation value is lower than a preset threshold. The current health advice is used to indicate the current adjustment range and frequency adjustment range for the next use. The working principle of the indication unit 4 can refer to the aforementioned step 104 and will not be repeated here.

[0135] The present invention aims to solve the user experience problem existing in the collaborative working state of laser equipment and medium frequency conversion equipment. Taking into account the different initial current adjustment ranges and initial frequency adjustment ranges in different use parts, and further considering the fact that the human body's adaptability to current and frequency will change over time, nine corresponding evaluation models are designed. Different evaluation models are used for evaluation of different parts and different use cycles, thereby greatly improving the evaluation capability of health evaluation.

[0136] The present invention can not only combine the current, frequency, temperature and electromyographic signals obtained during use to perform data analysis and processing, but also give different health reference suggestions according to the different sensitivity and tolerance of different use parts, so as to find the best adjustment range of the current adjustment range and the frequency adjustment range when using it next time, avoid use risks, and improve user experience;

[0137] The present invention can also determine the corresponding preset current adjustment limit and preset frequency adjustment limit according to the current usage part, and then determine the target current adjustment limit corresponding to the current usage part according to the current usage evaluation value and the preset current adjustment limit, and determine the target frequency adjustment limit corresponding to the current usage part according to the current usage evaluation value and the preset frequency adjustment limit, thereby realizing different adjustment range control for different usage parts, and further realizing refined control processing of current and frequency regulation.

[0138] Optionally, the present invention further provides a health assessment generation system of photoelectric coordinated control, comprising a medium frequency conversion device, a laser device, a temperature sensor disposed on the body surface, used to determine the change value of the body surface temperature, and an electromyographic sensor disposed on the body surface, used to determine the change value of muscle activity, wherein the medium frequency conversion device includes but is not limited to a medium frequency conversion rehabilitation device, the laser device includes but is not limited to a laser rehabilitation device, and further includes:

[0139] Time module, used to record usage time and usage cycle;

[0140] The human-computer interaction module includes a display screen and operation buttons, which are used to set usage parameters and display usage information.

[0141] Figure 3 Schematic diagram of the structure of the electronic device provided by the present invention. Figure 3As shown, the electronic device may include: a processor (processor) 110, a communication interface (Communications Interface) 120, a memory (memory) 130 and a communication bus 140, wherein the processor 110, the communication interface 120, and the memory 130 communicate with each other through the communication bus 140. The processor 110 can call the logic instructions in the memory 130 to execute the health assessment generation method for photoelectric collaborative control, which includes: determining a current assessment model from a preset model library according to the current use part and the current use time; performing feature extraction on the current change value to determine the current change feature, performing feature extraction on the frequency change value to determine the frequency change feature, performing feature extraction on the body surface temperature change value to determine the body surface temperature change feature, performing feature extraction on the muscle activity change value to determine the muscle activity feature, wherein the current change value, the frequency change value, the body surface temperature change value and the muscle activity change value are determined from the start of use to the current use time; inputting the current change feature, the frequency change feature, the body surface temperature change feature and the muscle activity feature into the current assessment model to determine the current use assessment value output by the current assessment model; upon receiving the user's end of use instruction, or, when the current use assessment value is lower than a preset threshold, outputting a current health recommendation according to the current use assessment value, and the current health recommendation is used to indicate the current adjustment range and the frequency adjustment range for the next use.

[0142] In addition, the logic instructions in the above-mentioned memory 130 can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the 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, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0143] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute a photoelectric collaborative control health assessment generation method provided by the above methods, the method comprising: determining a current assessment model from a preset model library based on the current usage part and the current usage time; extracting features of current change values ​​to determine current change features, extracting features of frequency change values ​​to determine frequency change features, extracting features of body surface temperature change values ​​to determine body surface temperature change features, and extracting features of muscle activity change values. Feature extraction, determining muscle activity characteristics, wherein the current change value, the frequency change value, the body surface temperature change value and the muscle activity change value are determined from the start of use to the current use time; inputting the current change characteristics, the frequency change characteristics, the body surface temperature change characteristics and the muscle activity characteristics into the current evaluation model to determine the current use evaluation value output by the current evaluation model; upon receiving the user's end of use instruction, or, when the current use evaluation value is lower than a preset threshold, outputting a current health recommendation based on the current use evaluation value, the current health recommendation being used to indicate the current adjustment range and the frequency adjustment range for the next use.

[0144] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the health assessment generation method for optoelectronic collaborative control provided by the above-mentioned methods, the method comprising: determining a current assessment model from a preset model library according to a current use part and a current use time; performing feature extraction on a current change value to determine a current change feature, performing feature extraction on a frequency change value to determine a frequency change feature, performing feature extraction on a body surface temperature change value to determine a body surface temperature change feature, performing feature extraction on a muscle activity change value to determine a muscle activity feature, wherein , the current change value, the frequency change value, the body surface temperature change value and the muscle activity change value are determined from the start of use to the current use time; the current change characteristics, the frequency change characteristics, the body surface temperature change characteristics and the muscle activity characteristics are input into the current evaluation model to determine the current use evaluation value output by the current evaluation model; upon receiving the user's end of use instruction, or, when the current use evaluation value is lower than a preset threshold, a current health recommendation is output according to the current use evaluation value, and the current health recommendation is used to indicate the current adjustment range and the frequency adjustment range for the next use.

[0145] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0146] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0147] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for generating a health assessment for optoelectronic coordinated control, characterized in that: include: According to the current use part and the current use time, determine the current evaluation model from the preset model library; Extracting features from the current change value to determine the current change feature, extracting features from the frequency change value to determine the frequency change feature, extracting features from the body surface temperature change value to determine the body surface temperature change feature, and extracting features from the muscle activity change value to determine the muscle activity feature, wherein the current change value, the frequency change value, the body surface temperature change value, and the muscle activity change value are determined from the start of use to the current use time; Inputting the current change characteristic, the frequency change characteristic, the body surface temperature change characteristic and the muscle activity characteristic into the current evaluation model, and determining the current use evaluation value output by the current evaluation model; Upon receiving the user's instruction to end use, or when the current use evaluation value is lower than a preset threshold, a current health recommendation is output based on the current use evaluation value, and the current health recommendation is used to indicate the current adjustment range and frequency adjustment range for the next use.

2. The method for generating a health assessment for optoelectronic coordinated control according to claim 1, characterized in that: The preset model library includes a first evaluation model, a second evaluation model, a third evaluation model, a fourth evaluation model, a fifth evaluation model, a sixth evaluation model, a seventh evaluation model, an eighth evaluation model, and a ninth evaluation model; The current evaluation model is determined from a preset model library according to the current use part and the current use time, including: When the current use part is the neck and the current use moment is at the beginning stage of use, the current evaluation model is determined to be the first evaluation model from the preset model library; when the current use part is the neck and the current use moment is at the middle stage of use, the current evaluation model is determined to be the second evaluation model from the preset model library; when the current use part is the neck and the current use moment is at the end stage of use, the current evaluation model is determined to be the third evaluation model from the preset model library; When the current use part is the waist and the current use time is at the beginning stage of use, the current evaluation model is determined to be the fourth evaluation model from the preset model library; when the current use part is the waist and the current use time is at the middle stage of use, the current evaluation model is determined to be the fifth evaluation model from the preset model library; when the current use part is the waist and the current use time is at the end stage of use, the current evaluation model is determined to be the sixth evaluation model from the preset model library; When the current use part is the limbs and the current use time is in the beginning stage of use, the current evaluation model is determined from the preset model library as the seventh evaluation model; when the current use part is the limbs and the current use time is in the middle stage of use, the current evaluation model is determined from the preset model library as the eighth evaluation model; when the current use part is the limbs and the current use time is in the ending stage of use, the current evaluation model is determined from the preset model library as the ninth evaluation model.

3. The method for generating a health assessment for optoelectronic coordinated control according to claim 2, characterized in that: Before inputting the current change characteristic, the frequency change characteristic, the body surface temperature change characteristic, and the muscle activity characteristic into the current evaluation model, the method further includes: Obtain sample current change characteristics, sample frequency change characteristics, sample body surface temperature change characteristics, and sample muscle activity characteristics at different usage locations and different usage durations, and obtain sample evaluation values ​​at each usage location and each usage duration, wherein the sample evaluation values ​​are determined based on user ratings and preset evaluation system ratings; Construct a sample data set according to the sample current change characteristics, sample frequency change characteristics, sample body surface temperature change characteristics and sample muscle activity characteristics at different usage parts and different usage durations, and the sample evaluation values ​​at each usage part and each usage duration, wherein the sample data set includes a sample training set and a sample test set; Divide the sample data set according to different usage parts and different usage durations to obtain sample data sets corresponding to different evaluation models; For each sample data set, the initial evaluation model is trained according to the sample training set, and the initial evaluation model is updated and iterated according to the sample test set and the preset loss function, the target evaluation model is determined, all sample data sets are traversed, all target evaluation models are determined, and the preset model library is constructed according to all target evaluation models.

4. The method for generating health assessment of optoelectronic coordinated control according to claim 1, characterized in that: After determining the current evaluation model from the preset model library, the method further includes: The output current of the laser device is read to determine the current change value, wherein the output current of the laser device is determined in the process of use from the start of use to the current use time according to the user's real-time adjustment of the laser device; The frequency change value is determined by reading the output frequency of the intermediate frequency conversion device, wherein the output frequency of the intermediate frequency conversion device is determined in real time according to the user adjusting the intermediate frequency conversion device during the use process from the start of use to the current use time; Reading a temperature sensor disposed on the body surface to determine a change value of the body surface temperature; Read the electromyographic sensor installed on the body surface to determine the change value of muscle activity.

5. The method for generating health assessment of optoelectronic coordinated control according to claim 1, characterized in that: The current change value includes the current value corresponding to each reading moment in the time series, and the feature extraction of the current change value to determine the current change feature includes: Normalizing each current value in the time series to obtain all normalized current values; For each normalized current value, calculating a time difference between the normalized current value and a normalized current value corresponding to a previous moment, and determining the time difference as a current change value; All normalized current values ​​are traversed, all current change values ​​are determined, and all current change values ​​are determined as current change features.

6. The method for generating health assessment of optoelectronic coordinated control according to claim 1, characterized in that: The frequency change value includes a frequency value corresponding to each reading moment in the time series, and the feature extraction of the frequency change value to determine the frequency change feature includes: Normalizing each frequency value in the time series to obtain all normalized frequency values; For each normalized frequency value, calculating a frequency difference between the normalized frequency value and a normalized frequency value corresponding to a previous moment, and determining the frequency difference as a frequency change value; All normalized frequency values ​​are traversed, all frequency change values ​​are determined, and all frequency change values ​​are determined as frequency change features.

7. The method for generating health assessment of optoelectronic coordinated control according to claim 1, characterized in that: The body surface temperature change value includes the body surface temperature value corresponding to each reading time in the time series, and the feature extraction of the body surface temperature change value to determine the body surface temperature change feature includes: For each body surface temperature value, determine a dimensional feature value corresponding to the body surface temperature value, the dimensional feature value includes a first dimensional feature value and a second dimensional feature value, wherein, when the body surface temperature value is greater than a preset temperature threshold, the body surface temperature value is determined to be an abnormal temperature value, and the first dimensional feature value is marked; otherwise, the second dimensional feature value is marked; Normalizing each body surface temperature value in the time series to obtain all normalized body surface temperature values, and for each normalized body surface temperature value, calculating a body surface temperature difference between the normalized body surface temperature value and a normalized body surface temperature value corresponding to a previous moment, and determining the body surface temperature difference as a body surface temperature change value; Traverse all normalized body surface temperature values, determine all body surface temperature change values, splice the body surface temperature change values ​​and dimensional feature values ​​corresponding to each moment, obtain the spliced ​​body surface temperature feature corresponding to each moment, and determine each spliced ​​body surface temperature feature corresponding to all moments as the body surface temperature change feature.

8. The method for generating health assessment of optoelectronic coordinated control according to claim 1, characterized in that: The muscle activity change value includes the electromyographic signal values ​​corresponding to all sampling time points in the time series, and the feature extraction of the muscle activity change value to determine the muscle activity feature includes: For each electromyographic signal value, convert the electromyographic signal value into an electromyographic numerical value; Determine the root mean square value of the electromyographic signal value corresponding to the sampling time point in the preset time window corresponding to each moment, which is used to characterize the degree of muscle tension, wherein the preset time window is determined after dividing the time series, and the preset time window is the time difference between the current moment and the previous moment; Normalizing the root mean square values ​​in the time series to obtain all normalized root mean square values; For each normalized root mean square value, calculating a root mean square value difference between the normalized root mean square value and a normalized root mean square value corresponding to a previous moment, and determining the root mean square value difference as a root mean square value change value; All normalized root mean square values ​​are traversed, all root mean square value change values ​​are determined, and all root mean square value change values ​​are determined as muscle activity characteristics.

9. The method for generating health assessment of optoelectronic coordinated control according to claim 1, characterized in that: Outputting the current health advice according to the current usage evaluation value includes: Determine, according to the current use location, a preset current adjustment limit value and a preset frequency adjustment limit value corresponding to the current use location; Determine the target current adjustment limit value corresponding to the current use part according to the current use evaluation value and the preset current adjustment limit value, and determine the target frequency adjustment limit value corresponding to the current use part according to the current use evaluation value and the preset frequency adjustment limit value; The current health advice is generated according to the target current adjustment limit and the target frequency adjustment limit.

10. The method for generating health assessment of optoelectronic coordinated control according to claim 9, characterized in that: The determining the target current adjustment limit value corresponding to the current use part according to the current use evaluation value and the preset current adjustment limit value includes: Among them, I s is the target current regulation limit, I b is the preset current regulation limit, V is the current usage evaluation value, ranging from 1 to 10, and k is the first preset coefficient, ranging from 1 to 10; The determining the target frequency adjustment limit value corresponding to the current use part according to the current use evaluation value and the preset frequency adjustment limit value includes: Among them, F s is the target frequency adjustment limit, F b is the preset frequency adjustment limit, p is the second preset coefficient, and its value ranges from 1 to 10.

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