Automatic double-lower-limb biomechanical balance recovery system

Abstract

The invention relates to the technical field of rehabilitation engineering, in particular to an automatic double-lower-limb biomechanical balance recovery system which comprises a fixing frame, a lifting table, a scanning mechanism, a main machine and an inner air bag, the lifting table is fixedly mounted on the surface of the fixing frame, and the scanning mechanism is rotationally connected to the side face of the fixing frame; a main machine is fixedly installed on the side face of the fixing frame. According to the method, the accuracy and details of collecting the lower limb data of the user are improved by integrating the three-dimensional scanning technology and the infrared thermal imaging technology. According to the technical combination, preliminary health assessment is more accurate, an abnormal heat area can be captured, and a scientific basis is provided for subsequent pressure regulation and dynamic correction. The pressure of the air bag is adjusted to meet the requirements of the ankle joint and the foot arch, and the responsiveness and the effect of correction measures are improved. And through real-time analysis and application of a thermal imaging result, the correction precision is improved, and the rehabilitation process is optimized, so that the method is more scientific and targeted.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of rehabilitation engineering, and particularly relates to an automatic double lower limb biomechanics balance recovery system. BACKGROUND

[0002] The technical field of rehabilitation engineering involves techniques and methods that apply engineering principles and design concepts to restore lost functions or enhance body functions of human beings. This field combines multiple disciplines such as biomechanics, biomedical engineering, mechanical engineering, and electronic engineering, and is committed to developing assistive devices, prostheses, wearable devices, and software systems to help patients recover the ability from simple daily activities to complex physical movements. The double lower limb biomechanics balance recovery system belongs to a specific application in the field of rehabilitation engineering, mainly used to help patients whose lower limb functions are affected due to accidents, diseases, or other conditions.

[0003] However, the existing technology has deficiencies in data integration and processing capabilities, making it difficult to comprehensively evaluate the complex biomechanics state of patients. Such deficiencies in data processing may result in inaccurate correction measures, thereby prolonging the rehabilitation period and increasing treatment costs. In addition, the lack of comprehensive and data-supported rehabilitation programs makes it difficult to achieve highly personalized treatment, which may affect the maximization of rehabilitation effect and patient satisfaction. SUMMARY

[0004] The purpose of the present application is to solve the shortcomings in the prior art and to provide an automatic double lower limb biomechanics balance recovery system.

[0005] In order to achieve the above-mentioned purpose, the present application adopts the following technical scheme: an automatic double lower limb biomechanics balance recovery system comprises a fixing frame, a lifting platform, a scanning mechanism, a host computer, and an inner air bag, the surface of the fixing frame is fixedly installed with the lifting platform, the side of the fixing frame is rotatably connected with the scanning mechanism, the side of the fixing frame is fixedly installed with the host computer, the top surface of the fixing frame is provided with the inner air bag, the scanning mechanism is internally provided with an infrared thermal imaging scanner and an original depth-sensing camera, and one side of the inner air bag is provided with a vibration rod.

[0006] Preferably, the host computer comprises:

[0007] A shape capturing module scans the double lower limbs of a user through a three-dimensional scanning device, obtains shape data of the double lower limbs, and generates a shape data set. Based on the shape data set, the health status of the double lower limb structure is determined, and a preliminary health assessment report is established.

[0008] A thermal imaging analysis module analyzes the hot spot distribution of the double lower limbs of a user using infrared thermal imaging, excavates inflammatory or abnormal heat areas, and generates a hot spot analysis result. In combination with the hot spot analysis result and the preliminary health assessment report, potential biomechanics problems are identified, and a comprehensive thermal imaging analysis result is obtained.

[0009] a pressure adjustment module, adjusting the airbag pressure according to the comprehensive thermal imaging analysis result, and generating adjusted pressure data;

[0010] a dynamic correction module, using the airbag to correct the position of the ankle joint and the arch, performing the adjustment of the biomechanical line, continuously monitoring and fine-tuning, and establishing a final correction state according to the comprehensive thermal imaging analysis result;

[0011] a data feedback and management module, collecting and analyzing the final correction state and historical use data, updating the user's training and rehabilitation plan according to the analysis result, and establishing a personalized rehabilitation plan.

[0012] Preferably, the acquisition step of the morphology data set is:

[0013] starting a three-dimensional scanning device to scan the user's lower limbs, capturing the differences in skin texture, muscle contour and bone structure, and obtaining three-dimensional scanning results;

[0014] based on the three-dimensional scanning results, calibrating key anatomical markers, including joint position and bone length, identifying and recording the size of key parts, and forming lower limb morphology feature data;

[0015] According to the lower limb morphology feature data, the data of each key anatomical marker is integrated, and the individual data points are organized into a structured format, and the morphology data set is integrated.

[0016] Preferably, the acquisition step of the preliminary health assessment report is:

[0017] based on the morphology data set, anatomical structure comparison is carried out, the morphology data of each anatomical part is classified, the difference with the health standard is identified, and the difference analysis result is obtained;

[0018] According to the difference analysis result, the health score is calculated;

[0019] Based on the health score, the overall health status of the lower limbs is analyzed, and the preliminary health assessment report is integrated.

[0020] Preferably, the acquisition step of the hotspot analysis result is:

[0021] using infrared thermal imaging to scan the user's lower limbs, collecting temperature distribution data from the epidermis to the deep muscle, and obtaining temperature image data;

[0022] based on the temperature image data, calculating the temperature anomaly index;

[0023] According to the temperature anomaly index, identify the inflammation or abnormal heat area, and generate the hotspot analysis result.

[0024] Preferably, the step of obtaining the comprehensive thermographic analysis result is:

[0025] Integrating the hotspot analysis result and the preliminary health assessment report, analyzing the temperature distribution and structural health data of the double lower limbs, identifying the deviated areas, and obtaining a deviation analysis result;

[0026] Based on the deviation analysis result, calculating a biomechanical abnormality index;

[0027] Based on the biomechanical abnormality index, determining potential biomechanical problems of the double lower limbs, and generating a comprehensive thermographic analysis result.

[0028] Preferably, the step of obtaining the adjusted pressure data is:

[0029] By analyzing the comprehensive thermographic analysis result, identifying the temperature abnormal areas and normal temperature areas in the double lower limbs, and obtaining a gas bag adjustment requirement list;

[0030] According to the gas bag adjustment requirement list, operating the gas bag, adjusting the pressure of each gas bag one by one, recording the parameters and results of each adjustment, and obtaining real-time adjustment records;

[0031] Using the real-time adjustment records, summarizing the pressure setting data of all gas bags, and generating adjusted pressure data.

[0032] Preferably, the step of obtaining the final correction state is:

[0033] Using the gas bag, calculating the required maximum adjustment amount of the gas bag according to the comprehensive thermographic analysis result;

[0034] Based on the maximum adjustment amount, adjusting the pressure of the gas bag, monitoring the correction effect and continuously adjusting until the maximum adjustment amount is reached, forming a final correction state.

[0035] Preferably, the step of obtaining the personalized rehabilitation scheme is:

[0036] Collecting the data of the final correction state and the historical use data of the user, generating a comprehensive data report through data integration;

[0037] Based on the comprehensive data report, analyzing the progress and current rehabilitation needs of the user, comparing historical data to identify long-term trends or changes, and obtaining an updated training and rehabilitation demand analysis;

[0038] According to the updated training and rehabilitation demand analysis, designing and adjusting the training and rehabilitation plan of the user, and forming a personalized rehabilitation scheme.

[0039] Compared with the prior art, the advantages and positive effects of the present application are:

[0040] In the present application, by integrating three-dimensional scanning and infrared thermal imaging technology, the accuracy and detail of collecting user lower limb data are improved. This combination of technologies makes the preliminary health assessment more accurate and can capture abnormal heat areas, providing a scientific basis for subsequent pressure adjustment and dynamic correction. Adjusting the air bag pressure to meet the needs of the ankle joint and arch improves the responsiveness and effectiveness of the correction measures. The real-time analysis and application of thermal imaging results not only improve the accuracy of correction, but also optimize the rehabilitation process, making it more scientific and targeted. BRIEF DESCRIPTION OF DRAWINGS

[0041] Fig. 1 is a structural schematic diagram of the present application;

[0042] Fig. 2 is a bottom view of the present application;

[0043] Fig. 3 is a system schematic diagram of the present application.

[0044] Reference signs: 1, fixed frame; 2, lifting platform; 3, scanning mechanism; 4, main machine; 5, inner air bag. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical scheme and advantages of the present application clearer and more understandable, the present application will be further described in detail below in combination with the drawings and examples. It should be understood that the specific examples described here are only used to explain the present application and do not limit the present application.

[0046] Please refer to Figs. 1-3 The present application provides a technical scheme: an automatic double lower limb biomechanical balance recovery system, comprising a fixed frame 1, a lifting platform 2, a scanning mechanism 3, a main machine 4 and an inner air bag 5, the surface of the fixed frame 1 is fixedly installed with the lifting platform 2, the side of the fixed frame 1 is rotatably connected with the scanning mechanism 3, the side of the fixed frame 1 is fixedly installed with the main machine 4, the top surface of the fixed frame 1 is provided with the inner air bag 5, the air cylinder or electric push rod of the inner air bag 5 is installed on the top surface of the fixed frame 1, the air cylinder can control the inner air bag 5 to be pushed upward, so that the user's foot can be pressed through the lifting platform 2, thereby correcting, the top surface of the lifting platform 2 is made of elastic mesh cloth, the scanning mechanism 3 is internally provided with an infrared thermal imaging scanner and an original depth sensing camera, and one side of the inner air bag 5 is provided with a vibration rod.

[0047] The main machine 4 comprises:

[0048] The shape capture module scans the user's double lower limbs through a three-dimensional scanning device, obtains the shape data of the double lower limbs, generates a shape data set, judges the health status of the double lower limb structure based on the shape data set, and establishes a preliminary health assessment report;

[0049] The thermal imaging analysis module uses infrared thermal imaging to analyze the hotspot distribution of the user's lower limbs, excavates inflammatory or abnormal hot areas, and generates a hotspot analysis result; combined with the hotspot analysis result and the preliminary health assessment report, potential biomechanical problems are identified, and a comprehensive thermal imaging analysis result is obtained;

[0050] The pressure adjustment module adjusts the airbag pressure according to the comprehensive thermal imaging analysis result, and generates adjusted pressure data; wherein the airbags are installed equidistantly on a plane or mounting plate, and the user steps on the plane with the installed airbags for correction.

[0051] The dynamic correction module uses airbags to correct the position of the ankle joint and arch according to the comprehensive thermal imaging analysis result, performs biomechanical line adjustment, continuously monitors and fine-tunes, and establishes a final correction state;

[0052] The data feedback and management module collects and analyzes the final correction state and historical use data, updates the user's training and rehabilitation plan according to the analysis result, and establishes a personalized rehabilitation plan.

[0053] The acquisition steps of the morphological data set are:

[0054] Start the three-dimensional scanning device to scan the user's lower limbs, capture the differences in skin texture, muscle contour and bone structure, and obtain three-dimensional scanning results;

[0055] Based on the three-dimensional scanning results, key anatomical markers are calibrated, including joint position and bone length, the size of key parts is identified and recorded, and a lower limb morphological feature data set is formed;

[0056] According to the lower limb morphological feature data, data integration is performed on each key anatomical marker, and the individual data points are organized into a structured format to integrate the morphological data set.

[0057] Specifically, start the three-dimensional scanner, scan the user's lower limbs, capture every detail, including skin texture, muscle contour and bone structure changes, perform preliminary image sharpening processing, adjust light reflection and shadow effect to ensure image quality meets analysis requirements; Next, edge detection is performed, the contrast sensitivity threshold is set to identify the boundary lines of different muscles and bones, and this threshold is set according to the pre-tested safety standard to ensure that subtle anatomical structure differences can be distinguished; clear and specific three-dimensional image data is generated.

[0058] Based on the obtained three-dimensional image data, key anatomical markers are directly identified, including measuring joint position and bone length, these key parts are calibrated through edge recognition and shape matching; then, the size of each key part is recorded, through comparative analysis, the accuracy range of size measurement is set, to ensure that all records are within the safe error range, finally, the structured lower limb morphological feature data is organized.

[0059] According to the morphological characteristics data of the lower limbs, data integration is performed. Firstly, the position and attribute of each key anatomical marker are confirmed, and through setting data classification and matching standards, it is ensured that each data point is correctly classified into the corresponding anatomical structure. Then, quality inspection is implemented on each type of anatomical data to eliminate data entry errors and repeated data items, and through the set data integrity checking program, it is ensured that the data is accurate and correct. All key anatomical data is integrated into a unified morphological data set.

[0060] The obtaining step of the preliminary health assessment report is:

[0061] Based on the morphological data set, anatomical structure comparison is performed, the morphological data of each anatomical part is classified, the differences with the health standard are identified, and the difference analysis result is obtained;

[0062] According to the difference analysis result, the health score is calculated, and the calculation formula is:

[0063]

[0064] Among them, H represents the health score, m i represents the measured value, n i represents the health standard value, w i represents the weight of the i th anatomical part, and k represents the total number of anatomical parts;

[0065] Based on the health score, the overall health status of the lower limbs is analyzed, and a preliminary health assessment report is integrated.

[0066] Specifically, through the three-dimensional image obtained by scanning, the joint position, muscle boundary and bone length are identified, and then these data are compared with the health standard database to identify the differences with the health model. The difference analysis is performed by comparing the difference between the actual size of each part and the standard size. The safety threshold is defined according to biomechanics and clinical data, and is usually set within the range of plus or minus 5%. The differences beyond this range are considered as potential health risks. These difference data are classified and recorded by part to form a detailed difference analysis result.

[0067] The advantage of the formula is that by introducing the square root operation, the sensitivity to abnormal values is enhanced, and the score can better reflect the slight changes of the actual health status. H represents the health score, reflecting the overall health level of the lower limb structure, m i represents the measured data of each anatomical part, n i represents the health standard value of each part, which is obtained by querying the health database, w i is the weight, which is distributed according to the importance of each part in biomechanics, and k is the total number of anatomical parts, which is determined as the number of key parts;

[0068] The calculation process: the ankle joint data m1 = 45mm is obtained by scanning, the health standard value n1 = 50mm, the weight w1 = 0.3, and the formula is calculated, and the total health score is calculated by repeating the process for all key parts; the result shows that if the health score H reaches a value close to 1, it indicates that the structure of the lower limbs is close to the perfect health state, and if the H value is low, it indicates that there is a big health problem, which needs further treatment;

[0069] After obtaining the health score, the overall health status of the lower limbs is evaluated, and the measured anatomical data and the calculated health score are considered comprehensively to write a preliminary health assessment report, including the specific deviation from the health standard, and the specific value of the health score indicates the overall health status of the lower limbs, such as a score close to 1 indicating a perfect health state, and below 0.8 usually indicating the need for further medical evaluation, which is performed by directly comparing the difference between the standard value and the measured value of each part.

[0070] The steps for obtaining the hotspot analysis result are:

[0071] The user's lower limbs are scanned by infrared thermal imaging, and temperature distribution data from the skin to the deep muscle are collected to obtain temperature image data;

[0072] Based on the temperature image data, the temperature anomaly index is calculated, and the calculation formula is:

[0073]

[0074] Where E represents the temperature anomaly index, T i represents the temperature value of the i-th pixel point, T avg represents the average temperature of the entire scanning area, and σ represents the standard deviation of the temperature;

[0075] According to the temperature anomaly index, the inflammation or abnormal heat area is identified, and the hotspot analysis result is generated.

[0076] Specifically, the user's lower limbs are scanned comprehensively by infrared thermal imaging, and the scanning device sensitivity and resolution are adjusted to ensure that every detail from the skin to the deep muscle can be captured, and temperature data is collected from each pixel point. These data are converted into digital signals by infrared sensors, converted into corresponding temperature values, and mapped to the position of the lower limbs to form temperature image data. At the same time, the temperature value of each pixel point is standardized, and whether the temperature is within the normal physiological range is judged by setting a safety threshold, wherein the normal body temperature safety range is set to 30℃ to 37℃, and the temperature value exceeding this range will be marked as abnormal by the system;

[0077] The formula is beneficial in that it can more sensitively identify abnormal hot spot areas by maximizing the ratio of absolute temperature deviation to standard deviation, providing an efficient analysis method for analyzing potential inflammation or other abnormal heat zones; T i The parameter acquisition step is to collect temperature values of the surfaces of both lower limbs using an infrared camera, T avg The parameter acquisition step is to calculate the average temperature of all collected temperature values, and the parameter acquisition step is to calculate the standard deviation of all temperature values.

[0078] Calculation process: T i ranges from 30°C to 40°C, T avg is 35°C, and the standard deviation σ is 2°C, which gives a result of 2.5 when substituted into the formula. This result indicates that the temperature anomaly index is 2.5, representing that the temperature deviation of the region is 2.5 times the average temperature standard deviation, and there may be inflammation or other physiological abnormalities.

[0079] According to the calculated temperature anomaly index, identify the hot spot areas of temperature anomalies. In the process of generating the hot spot distribution map, these identified high temperature areas are visually marked on the image of the lower limbs, and color coding is used to distinguish different levels of hot spots, such as red for high-risk areas and yellow for medium-risk areas. The generated hot spot distribution map displays all significant hot spot areas.

[0080] The acquisition step of the comprehensive thermographic analysis result is:

[0081] Integrate the hot spot analysis result and the preliminary health assessment report, analyze the temperature distribution and structural health data of the lower limbs, identify the deviated areas, and obtain the deviation analysis result;

[0082] Based on the deviation analysis result, calculate the biomechanical abnormality index, and the calculation formula is:

[0083]

[0084] Where B represents the biomechanical abnormality index, H i represents the health score, E i represents the temperature anomaly index, and Z represents the number of evaluated areas.

[0085] Based on the biomechanical abnormality index, determine the potential biomechanical problems of the lower limbs, and generate the comprehensive thermographic analysis result.

[0086] Specifically, the hotspot analysis results are integrated with the preliminary health assessment report for detailed analysis of the lower limbs. First, the temperature data of each region are extracted from the infrared thermal imaging results, which reflect the thermal distribution of the skin and tissues. Then, the temperature deviation and structural deviation from the health model are calculated by comparing the structural data in the health assessment report, such as bone density and joint position. Using difference analysis method, the regions with significant temperature or structural abnormalities are identified, with a standard deviation threshold of ±2°C of normal body temperature. Any deviation beyond this range is considered a potential risk area. This threshold is set based on the common inflammation temperature standard in clinical practice, and the deviation analysis results are obtained.

[0087] The formula is beneficial in that it combines the health assessment value with the ratio of hotspot abnormal values, enhancing the sensitivity to health problems while ensuring the accuracy of data processing.

[0088] Calculation process: One lower limb is divided into 3 regions (Z=3). i The values are {0.9, 0.95, 0.85}, representing the health scores of the three regions. i The values are {1.0, 0.5, 1.5}, representing the temperature abnormality index.

[0089] Now let's calculate the formula: 0.1397. This result indicates that the biomechanical abnormality index is 0.1397, indicating that the overall biomechanical status of the lower limbs is good, but there are minor problems. The larger this value, the more serious the problem. When B is higher than 0.2, there is a significant biomechanical abnormality.

[0090] Based on the calculated biomechanical abnormality index, the biomechanical condition of the lower limbs is comprehensively evaluated, with special attention to indices exceeding 0.2. For regions exceeding this threshold, labeling and recording are performed. Each labeled region will be displayed in the comprehensive thermal imaging analysis results, including the specific location and abnormality index value.

[0091] The steps to obtain the adjusted pressure data are:

[0092] By analyzing the comprehensive thermal imaging analysis results, identify the regions with temperature abnormalities and normal temperature regions in the lower limbs, and obtain the airbag adjustment requirement list;

[0093] According to the airbag adjustment requirement list, operate the airbags to adjust the pressure of each airbag one by one, record the parameters and results of each adjustment, and obtain the real-time adjustment record;

[0094] Where the airbags are installed equidistantly on a plane, and the user steps on this airbag-installed plane for correction;

[0095] Using the real-time adjustment record, summarize all airbag pressure setting data to generate adjusted pressure data.

[0096] Specifically, identify areas of the lower extremities with abnormally high temperatures, mark these areas as high-pressure zones, and increase the pressure of the corresponding airbags to reduce potential compression or pain. Similarly, identify areas with normal temperatures and ensure that the airbags in these areas maintain their original settings or are slightly reduced in pressure to maintain an even pressure distribution. During this process, detailed temperature data for each area and its deviation from the normal temperature are recorded to form an airbag adjustment requirement list.

[0097] Based on the airbag adjustment requirement list, adjust the pressure of each airbag one by one. For each specified airbag, increase or decrease the pressure according to the instructions on the requirement list to ensure that the pressure adjustment of each airbag is based on the specific needs of its corresponding area. During the adjustment process, the initial pressure and adjusted pressure of each airbag are recorded.

[0098] Using real-time adjustment records, compile the final pressure settings of all airbags to generate an adjusted pressure data report. This report contains the final pressure values and adjustment details for each airbag's corresponding area. By organizing these data, the pressure distribution of each airbag and the overall pressure adjustment results can be clearly displayed, providing users with a clear, personalized wearing solution adjusted according to their specific physiological and biomechanical needs.

[0099] The final correction state acquisition step is:

[0100] Using airbags, calculate the required maximum adjustment amount of the airbags based on the comprehensive thermal imaging analysis results. The calculation formula is:

[0101]

[0102] where A represents the required maximum adjustment amount, δx i represents the deviation from the ideal position, s i represents the tolerance standard of the deviation, and c i represents the adjustment factor.

[0103] Based on the maximum adjustment amount, adjust the pressure of the airbags, monitor the correction effect, and continuously adjust until the maximum adjustment amount is reached to form the final correction state.

[0104] Specifically, the formula has the benefit of calculating the required maximum adjustment amount, taking into account the differences between individuals to ensure the individualization and accuracy of the correction measures. A represents the required maximum adjustment amount, indicating the limit of adjustment to ensure that excessive correction does not cause harm. δx i represents the deviation from the ideal position, which is obtained through actual measurement, s i represents the tolerance standard of the deviation, which is a safety parameter set based on past experience to ensure the safety and reliability of the correction process, and c irepresents an adjustment factor, adjusted according to past correction experience and feedback in actual operation, used to fine-tune the pressure setting to adapt to the specific needs of different patients;

[0105] Calculation process: in a certain correction, the deviation of the measured ankle position from the ideal position is 2mm, the tolerance standard is 1mm, and the adjustment factor is 0.05. The adjustment amount is calculated as 2.012, which indicates that the maximum pressure adjustment amount that needs to be increased is 2.012 units. This means that if the adjustment amount is greater than this value, it may lead to overcorrection, and if it is less than this value, it may not achieve the ideal correction effect;

[0106] After calculating the required maximum adjustment amount, adjust the pressure of the air bag to meet this requirement. Monitor the correction effect of each step closely during the process, and make necessary adjustments based on real-time data. For example, if the initial pressure setting of a certain air bag leads to insufficient correction of the ankle position, the pressure of the air bag will be automatically increased based on the continuously collected correction data until the air bag reaches the maximum adjustment amount calculated above. During this adjustment process, the adjustment record of each air bag is detailed, including the pressure increase or decrease value, the position deviation before and after adjustment, and the patient's comfort feedback. The record of adjustment details ensures that each adjustment is based on the latest biomechanical data and the patient's specific response, gradually guiding the ankle and arch to the ideal correction position until a stable correction state is formed.

[0107] The steps to obtain the personalized rehabilitation plan are as follows:

[0108] Collect data of the final correction state and user's historical use data, and generate a comprehensive data report through data integration;

[0109] Based on the comprehensive data report, analyze the user's progress and current rehabilitation needs, compare historical data to identify long-term trends or changes, and obtain updated training and rehabilitation needs analysis;

[0110] According to the updated training and rehabilitation needs analysis, design and adjust the user's training and rehabilitation plan to form a personalized rehabilitation plan.

[0111] Specifically, sort and verify the data of the final correction state and the user's historical use data to ensure the accuracy and completeness of all data, and then standardize the data. Convert data at different time points to a unified format for analysis.

[0112] After obtaining the comprehensive data report, analyze the key data in the report in detail, especially those data points that show significant changes or trends, evaluate the user's rehabilitation effect at different stages, and in addition, perform long-term trend analysis, such as identifying long-term change trends in data through moving average and difference techniques. From these in-depth analyses, obtain updated training and rehabilitation needs analysis.

[0113] According to the latest training and rehabilitation needs analysis, develop adjustment strategies, including designing customized training tasks for specific demand areas, adjusting training intensity to match the user's current rehabilitation status, optimizing training frequency and duration, ensuring that each training link can effectively promote the user's rehabilitation process, in addition, considering the user's feedback and historical training response, adjusting various parameters, such as adjusting the pressure setting and support strength of the airbag.

Claims

1. An automated dual lower limb biomechanical balance recovery system, characterized in that, Including fixed frame (1), lifting platform (2), scanning mechanism (3), main machine (4) and inner air bag (5), the surface of fixed frame (1) is fixedly installed with lifting platform (2), the side of fixed frame (1) is rotatably connected with scanning mechanism (3), the side of fixed frame (1) is fixedly installed with main machine (4), the top of fixed frame (1) is equipped with inner air bag (5), scanning mechanism (3) is equipped with infrared thermal imaging scanner and original deep sense camera, one side of inner air bag (5) is equipped with vibrating rod.

2. The automated dual lower limb biomechanical balance recovery system according to claim 1, wherein, The main machine (4) comprises: The morphology capture module scans the user's lower limbs by a three-dimensional scanning device, obtains the morphology data of the lower limbs, and generates a morphology data set; based on the morphology data set, the health status of the lower limb structure is determined, and a preliminary health assessment report is established; The thermal imaging analysis module uses infrared thermal imaging to analyze the hotspot distribution of the user's lower limbs, excavates inflammatory or abnormal heat areas, and generates a hotspot analysis result; combined with the hotspot analysis result and the preliminary health assessment report, potential biomechanical problems are identified, and a comprehensive thermal imaging analysis result is obtained; The pressure adjustment module adjusts the air bag pressure according to the comprehensive thermal imaging analysis result, and generates adjusted pressure data; The dynamic correction module uses the air bag to correct the position of the ankle joint and the arch according to the comprehensive thermal imaging analysis result, performs biomechanical line adjustment, continuously monitors and fine-tunes, and establishes a final correction state; The data feedback and management module collects and analyzes the final correction state and historical use data, updates the user's training and rehabilitation plan according to the analysis result, and establishes a personalized rehabilitation scheme.

3. The automated dual lower limb biomechanical balance recovery system according to claim 2, wherein, The morphology data set acquisition step is: Start the three-dimensional scanning device, scan the user's lower limbs, capture the differences in skin texture, muscle contour and bone structure, and obtain three-dimensional scanning results; Based on the three-dimensional scanning results, calibrate key anatomical markers, including joint position and bone length, identify and record the size of key parts, and form lower limb morphology feature data; According to the lower limb morphology feature data, integrate the data of each key anatomical marker into a structured format, and integrate the morphology data set.

4. The automated dual lower limb biomechanics balance recovery system of claim 2, wherein, The preliminary health assessment report acquisition step is: Based on the morphology data set, compare the anatomical structure, classify the morphology data of each anatomical part, identify the differences with the health standard, and obtain the difference analysis result; According to the difference analysis result, calculate the health score; Based on the health score, analyze the overall health status of the lower limbs, and integrate into a preliminary health assessment report.

5. The automated dual lower limb biomechanics balance recovery system of claim 2, wherein, The hotspot analysis result acquisition step is: Scan the user's lower limbs using infrared thermal imaging, collect temperature distribution data from the epidermis to the deep muscles, and obtain temperature image data; Based on the temperature image data, calculate the temperature anomaly index; According to the temperature anomaly index, identify the inflammatory or abnormal heat area, and generate the hotspot analysis result.

6. The automated dual lower limb biomechanics balance recovery system of claim 2, wherein, The comprehensive thermal imaging analysis result acquisition step is: Integrate the hotspot analysis result and the preliminary health assessment report, analyze the temperature distribution and structural health data of the double lower limbs, identify the deviated areas, and obtain a deviation analysis result; Based on the deviation analysis result, calculate a biomechanics abnormality index; Based on the biomechanics abnormality index, determine the potential biomechanics problems of the double lower limbs, and generate a comprehensive thermography analysis result.

7. The automated dual lower limb biomechanics balance recovery system of claim 2, wherein, The step of obtaining the adjusted pressure data is: By analyzing the comprehensive thermography analysis result, identify the temperature abnormal areas and normal temperature areas in the double lower limbs, and obtain a gas bag adjustment requirement list; According to the gas bag adjustment requirement list, operate the gas bags, adjust the pressure of each gas bag one by one, record the parameters and results of each adjustment, and obtain real-time adjustment records; Use the real-time adjustment records to summarize the pressure setting data of all gas bags, and generate adjusted pressure data.

8. The automated dual lower limb biomechanics balance recovery system of claim 2, wherein, The step of obtaining the final correction state is: Use the gas bags to calculate the required maximum adjustment amount of the gas bags according to the comprehensive thermography analysis result; Based on the maximum adjustment amount, adjust the pressure of the gas bags, monitor the correction effect and continuously adjust until the maximum adjustment amount is reached, and form a final correction state.

9. The automated dual lower limb biomechanical balance recovery system according to claim 2, wherein, The step of obtaining the personalized rehabilitation scheme is: Collect the data of the final correction state and the historical use data of the user, integrate the data to generate a comprehensive data report; Based on the comprehensive data report, analyze the progress and current rehabilitation needs of the user, compare the historical data to identify long-term trends or changes, and obtain an updated training and rehabilitation needs analysis; According to the updated training and rehabilitation needs analysis, design and adjust the training and rehabilitation plan of the user, and form a personalized rehabilitation scheme.

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