Comprehensive multi-modal physiotherapy device and method for soft tissue injuries

Abstract

The present application relates to the technical field of physiotherapy management, and specifically includes a comprehensive multi-modal physiotherapy device and method for soft tissue injury, which comprises: parameter iterative optimization of a multi-modal collaborative physiotherapy model, comparison with a five music prescription database, a soft tissue injury database and an acupoint prescription database, and output of a recommended physiotherapy scheme list. The technical problems of insufficient adaptability of physiotherapy schemes to individual physiotherapy needs of patients, inability of physiotherapy parameters to be adjusted according to changes in indicators in the patient's rehabilitation process, and difficulty in adapting to physiotherapy needs at different rehabilitation stages are solved, a multi-modal collaborative physiotherapy model is constructed by fusing music, physical and acupoint physiotherapy channels of five music, rehabilitation influencing factors are determined according to historical physiotherapy data, parameter iterative optimization of the multi-modal collaborative physiotherapy model is performed, physiotherapy parameters are dynamically adjusted with physiological indicators in the patient's rehabilitation process, individualized physiotherapy needs at different stages of the disease course are adapted, and the technical effect of improving the matching degree of physiotherapy schemes to individual physiotherapy needs of patients is achieved.

Description

Technical Field

[0001] This invention relates to the field of physiotherapy management, specifically to a comprehensive multimodal physiotherapy device and method for soft tissue injuries. Background Technology

[0002] Soft tissue injury is a common health problem among sports injuries, daily accidents, and occupational strain. Its rehabilitation effect directly affects the recovery of limb function and quality of life of patients. Conventional physiotherapy methods are no longer able to meet the needs of diverse injury symptoms, different disease stages, and individual physical differences.

[0003] Currently, soft tissue injury physiotherapy techniques are largely based on experience. Most devices focus only on physical therapy or a single auxiliary method. For example, transcutaneous electrical stimulation therapy often uses single-frequency pulse stimulation, and the five-tone therapy often remains at the level of simply listening to music. Physical therapy plans cannot adapt to individual differences and the injury repair process. In short, existing physiotherapy plans are unable to adjust the five-tone music prescriptions, acupoint prescriptions, and physical parameters in a timely manner for different injury sites, symptoms, and rehabilitation processes, further limiting the efficiency and effectiveness of rehabilitation.

[0004] In summary, existing technologies suffer from technical problems such as insufficient adaptability of physiotherapy plans to individual patient needs, inability to adjust physiotherapy parameters according to changes in indicators during the patient's recovery process, and difficulty in adapting to the physiotherapy needs of different rehabilitation stages. Summary of the Invention

[0005] This application provides a comprehensive multimodal physiotherapy device and method for soft tissue injuries, aiming to solve the technical problems in the prior art where physiotherapy programs are not well adapted to the individual physiotherapy needs of patients, physiotherapy parameters cannot be adjusted according to changes in indicators during the patient's rehabilitation process, and it is difficult to adapt to the physiotherapy needs of different rehabilitation stages.

[0006] In view of the above problems, the technical solution to achieve the present application is as follows: In a first aspect, this application provides a comprehensive multimodal physiotherapy device for soft tissue injuries, comprising: a multimodal collaborative physiotherapy model establishment module, used to establish a multimodal collaborative physiotherapy model corresponding to soft tissue injury symptoms based on music therapy channels, physical therapy channels, and acupoint therapy channels of five musical pieces, wherein the soft tissue injury symptoms include tissue contusion, tissue strain, tissue tear, and tissue inflammation; a rehabilitation influencing factor determination module, used to determine rehabilitation influencing factors including injury symptoms, disease stage, physical characteristics indicators, and physiological indicators based on historical physiotherapy data, wherein the physiological indicators include skin temperature, bioimpedance, surface electromyography, and tissue blood oxygen saturation; an iterative optimization module, used to iteratively optimize the parameters of the multimodal collaborative physiotherapy model based on the rehabilitation influencing factors until the maximum number of iterations is reached; and a recommended physiotherapy plan list output module, used to output a recommended physiotherapy plan list based on the iteratively optimized multimodal collaborative physiotherapy model and in comparison with a five musical piece prescription database, a soft tissue injury database, and an acupoint prescription database.

[0007] Preferably, the historical physiotherapy data is classified according to rehabilitation effects, wherein the historical physiotherapy data includes physiotherapy parameter configuration, physiological index change curves, VAS pain scores, and joint range of motion recovery data; based on the classified historical physiotherapy data, the rehabilitation influencing factors corresponding to the mapping relationship are obtained by using an association rule algorithm.

[0008] Preferably, the deviation between the actual rehabilitation effect and the expected effect corresponding to the collaborative physiotherapy parameters output by the multimodal collaborative physiotherapy model is used as the optimization error; the optimization error is used as the objective function for iterative optimization, and the five-tone attribute matching parameters, the intensity and frequency of transcutaneous electrical stimulation of music, the near-infrared target temperature and the acupoint stimulation combination scheme are adjusted in each iteration.

[0009] Preferably, the multimodal synergistic physiotherapy model is used to integrate the synergistic physiotherapy effects of five-tone therapy, transcutaneous electrical stimulation of music, near-infrared photothermal therapy, and acupoint targeted stimulation.

[0010] Preferably, a reinforcement learning mechanism is introduced, which uses the reduction of optimization error and the improvement of rehabilitation indicators as reward signals, and the increase of optimization error and abnormal physiological indicators as punishment signals, and dynamically adjusts the weight coefficients of the music therapy channel, physical therapy channel and acupoint therapy channel of the five musical pieces.

[0011] Preferably, the rehabilitation difficulty index is assessed based on the severity and stage of the soft tissue injury; the maximum number of iterations is dynamically configured according to the rehabilitation difficulty index.

[0012] Preferably, a multimodal detection terminal is connected to mark the soft tissue injury area; based on the soft tissue injury area, the corresponding five-music music prescription, physical parameter configuration scheme and acupoint stimulation prescription are matched with the five-music music prescription database, soft tissue injury database and acupoint prescription database to construct a differential physiotherapy basic framework.

[0013] In a second aspect, this application provides a comprehensive multimodal physiotherapy method for soft tissue injuries. The method includes: establishing a multimodal collaborative physiotherapy model corresponding to soft tissue injury conditions based on music therapy channels, physical therapy channels, and acupoint therapy channels of five musical pieces. These soft tissue injury conditions include tissue contusion, tissue strain, tissue tear, and tissue inflammation. Based on historical physiotherapy data, rehabilitation influencing factors are determined, including injury condition, disease stage, physical characteristics, and physiological indicators. These physiological indicators include skin temperature, bioimpedance, surface electromyography, and tissue oxygen saturation. Based on these rehabilitation influencing factors, the multimodal collaborative physiotherapy model undergoes iterative parameter optimization until the maximum number of iterations is reached. Using the iteratively optimized multimodal collaborative physiotherapy model, a list of recommended physiotherapy plans is output by comparing it with a five-musical-piece prescription database, a soft tissue injury database, and an acupoint prescription database.

[0014] In summary, one or more technical solutions provided in this application realize the integration of music, physical therapy, and acupoint therapy channels of five musical pieces to construct a multimodal collaborative physiotherapy model. Based on historical physiotherapy data, rehabilitation influencing factors are determined, and the parameters of the multimodal collaborative physiotherapy model are iteratively optimized. This enables the physiotherapy parameters to be dynamically adjusted with the physiological indicators of the patient during the rehabilitation process, adapting to the personalized physiotherapy needs of different disease stages, and improving the technical effect of matching the physiotherapy plan with the individual physiotherapy needs of the patient. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely exemplary. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0016] Figure 1 This application provides a structural schematic diagram of a comprehensive multimodal physiotherapy device for soft tissue injuries.

[0017] Figure 2 This application provides a flowchart of a comprehensive multimodal physical therapy method for soft tissue injuries.

[0018] Figure labeling: Module 11 for establishing a multimodal collaborative physiotherapy model, Module 12 for determining rehabilitation influencing factors, Module 13 for iterative optimization, and Module 14 for outputting a list of recommended physiotherapy plans. Detailed Implementation

[0019] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. It should be understood that this application is not limited to the exemplary embodiments described herein. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0020] Example 1: The present application will be described in detail below with reference to the accompanying drawings, as follows... Figure 1 As shown, this application provides a comprehensive multimodal physical therapy device for soft tissue injuries, the device comprising: The multimodal collaborative physiotherapy model establishment module 11 is used to establish a multimodal collaborative physiotherapy model corresponding to soft tissue injury symptoms based on the music physiotherapy channel, physical physiotherapy channel, and acupoint physiotherapy channel of five musical pieces. The soft tissue injury symptoms include tissue contusion, tissue strain, tissue tear, and tissue inflammation. The rehabilitation influencing factor determination module 12 is used to determine rehabilitation influencing factors including injury symptoms, disease stage, physical characteristics indicators, and physiological indicators based on historical physiotherapy data. The physiological indicators include skin temperature, bioimpedance, surface electromyography, and tissue blood oxygen saturation.

[0021] It is important to understand that existing soft tissue injury physiotherapy techniques are largely based on experience. Most devices focus only on physical therapy or a single auxiliary method. Specifically, transcutaneous electrical stimulation (TES) often uses single-frequency pulse stimulation, and the Five-Tone Therapy often remains at the level of simply listening to music, failing to leverage the dual-mode physiotherapy mechanism of Five-Tone Therapy + Music Transcutaneous Electrical Stimulation to overcome the tolerance or adaptability of single-frequency pulse stimulation. Furthermore, it neglects the fact that most acupoints can receive simultaneous acupuncture and moxibustion stimulation, thus failing to leverage the synergistic enhancement effect of acupuncture and moxibustion. Many techniques employ fixed parameter combinations, making it impossible to adapt the physiotherapy plan to individual differences and dynamically adjust to the injury repair process. Finally, an intelligent closed-loop feedback physiotherapy system integrating the synergistic effects of Five-Tone Therapy, Music Transcutaneous Electrical Stimulation, Near-Infrared Light, and Heat has not been formed, making it difficult to simultaneously and systematically address pain, inflammation, and soft tissue repair issues. The reliance on physicians' subjective experience in formulating treatment plans leads to a mismatch between physiotherapy parameters and patients' actual rehabilitation needs. For example, patients in the acute phase may experience increased inflammation due to excessive stimulation intensity. It is also difficult to accurately mark the damaged area and match the physiotherapy plan in real time. Furthermore, it is difficult to adjust the prescriptions for the five musical pieces, acupoints, and physical parameters in a timely manner according to different injury sites, symptoms, and rehabilitation processes, which further limits the efficiency and effectiveness of rehabilitation.

[0022] In one embodiment, the multimodal synergistic physiotherapy model refers to integrating three different types of physiotherapy methods—music therapy, physical therapy, and acupoint therapy—into a unified model. Through synergistic effects, it achieves comprehensive physiotherapy for soft tissue injuries. Specifically, the music therapy channel of the five musical pieces uses music with specific five-tone attributes (including Gong, Shang, Jiao, Zhi, and Yu tones with different frequencies and rhythmic characteristics) to regulate the patient's psychology and physiology. The physical therapy channel promotes local blood circulation and tissue repair through physical means such as photothermal therapy and transcutaneous electrical stimulation of music. The acupoint therapy channel regulates the body's meridian system by stimulating specific acupoints.

[0023] Soft tissue injury conditions include contusions, sprains, tears, and inflammation. These conditions are used to assess the type and severity of the injury, providing foundational data for establishing physiotherapy models. Rehabilitation influencing factors refer to various factors affecting the patient's rehabilitation process, including the type of injury, the stage of the injury, physical characteristics, and physiological indicators. These factors are obtained through analysis of historical physiotherapy data and are used to optimize the parameter configuration of the multimodal collaborative physiotherapy model. Injury types include contusions, sprains, tears, and inflammation; the stage of the injury includes the acute phase, subacute phase, and recovery phase; physical characteristics include age, gender, and body mass index; and physiological indicators include skin temperature, bioimpedance, surface electromyography, and tissue oxygen saturation.

[0024] Optionally, by detecting specific symptoms of soft tissue injuries, including contusions, sprains, and inflammation, a comprehensive multimodal collaborative physiotherapy model can be established. This model integrates music therapy channels, physical therapy channels, and acupoint therapy channels, enabling simultaneous physiotherapy for patients from multiple dimensions, including psychological adjustment, physiological repair, and meridian unblocking. By analyzing historical physiotherapy data, key factors influencing rehabilitation can be identified, including injury symptoms, disease stage, physical characteristics, and physiological indicators. Specifically, for patients with acute soft tissue injuries, elevated skin temperature and changes in bioimpedance are important indicators that help the model accurately adjust physiotherapy parameters. Through comprehensive analysis of these multidimensional factors, the model can generate personalized physiotherapy plans for each patient, significantly improving the suitability of the physiotherapy plan and the rehabilitation effect.

[0025] The iterative optimization module 13 is used to iteratively optimize the parameters of the multimodal collaborative physiotherapy model based on the rehabilitation influencing factors until the maximum number of iterations is reached; the recommended physiotherapy plan list output module 14 is used to output a recommended physiotherapy plan list based on the iteratively optimized multimodal collaborative physiotherapy model and the five-music prescription database, soft tissue injury database and acupoint prescription database.

[0026] In one embodiment, parameter iterative optimization refers to minimizing the deviation between the actual rehabilitation effect and the expected effect of the model output by using key parameters in the multimodal collaborative physiotherapy model, including the musical attributes of the five musical pieces, the intensity and frequency of transcutaneous electrical stimulation of the music, the target temperature of near-infrared photothermal therapy, and the combination of acupoint stimulation. This is usually achieved using optimization algorithms such as gradient descent and genetic algorithms. Each iteration adjusts the parameters based on the feedback error until the preset maximum number of iterations is reached or the error converges. The five musical piece prescription database is a database that stores the musical frequencies and rhythmic combinations of different five musical pieces. Different five musical piece prescriptions are targeted at specific injury symptoms and rehabilitation stages, and can regulate the patient's psychological state and physiological response. For example, the Gong tone is suitable for relieving anxiety, and the Jiao tone helps relax muscles. The Gong tone refers to low frequencies, and the Jiao tone refers to mid-frequency frequencies.

[0027] The soft tissue injury database records the characteristics and corresponding physiotherapy parameter configurations of different injury conditions, including contusions, sprains, tears, and inflammation, providing reference data for the model. The acupoint prescription database stores acupoint stimulation programs for different injury sites and rehabilitation stages, including information such as single acupoints or combinations of several acupoints, acupoint locations, stimulation intensity and frequency, and near-infrared photothermal therapy target temperature. The recommended physiotherapy program list is a collection of personalized physiotherapy programs output by the optimized model. Each program includes specific music, physical, and acupoint physiotherapy parameters for the intelligent system to refer to and select.

[0028] Optionally, after the multimodal collaborative physiotherapy model is established, the parameters of the multimodal collaborative physiotherapy model are iteratively optimized based on rehabilitation influencing factors including injury symptoms, disease stage, physical characteristics, and physiological indicators. Through iterative optimization, the multimodal collaborative physiotherapy model will dynamically adjust the parameters according to changes in the patient's physiological indicators, including skin temperature elevation and abnormal surface electromyography. Each iteration will calculate the deviation between the actual rehabilitation effect and the expected effect, and use this deviation as the optimization objective function.

[0029] The optimized multimodal collaborative physiotherapy model compares its findings with a database of five-tone music prescriptions, a database of soft tissue injuries, and a database of acupoint prescriptions, outputting a list of personalized recommended physiotherapy plans. Furthermore, based on the patient's specific injury and physical characteristics (e.g., soft tissue strain of the left knee joint, robust constitution), the model matches suitable music prescriptions, physical parameter configurations, and acupoint stimulation schemes from these databases. For example, it might use soothing Gong-tone music at a frequency of 256Hz, transcutaneous electrical stimulation of the music at an intensity of 1mA and a frequency of 10Hz, stimulation of the Zusanli acupoint at a moderate intensity, and a near-infrared photothermal therapy target temperature of 39℃. Through these steps, the multimodal collaborative physiotherapy model provides each patient with a precise physiotherapy plan, significantly improving rehabilitation outcomes.

[0030] Furthermore, the rehabilitation influencing factor determination module 12 is used to perform the following method: The historical physiotherapy data is categorized according to rehabilitation effects. The historical physiotherapy data includes physiotherapy parameter configurations, physiological index change curves, VAS pain scores, and joint range of motion recovery data. Based on the categorized historical physiotherapy data, an association rule algorithm is used to mine the rehabilitation influencing factors corresponding to the mapping relationships.

[0031] In one embodiment, historical physiotherapy data refers to data accumulated during previous physiotherapy sessions, including physiotherapy parameter configurations, physiological index change curves, VAS pain scores, and joint range of motion recovery data. This data reflects the patient's recovery under different physiotherapy programs. Physiotherapy parameter configurations include the musical attributes of five musical pieces, the intensity and frequency of transcutaneous electrical stimulation of the music, the target temperature of near-infrared photothermal therapy, and the combination of acupoint stimulation. Physiological change curves refer to the changes in skin temperature, bioimpedance, surface electromyography, and tissue oxygen saturation over time. VAS pain scores are used to quantify the degree of pain. Joint range of motion recovery data refers to the changes in the range of motion of the joints.

[0032] Classifying data by rehabilitation effect refers to dividing historical physiotherapy data into different categories based on the patient's rehabilitation status. Data can be categorized into three types: good rehabilitation, average rehabilitation, and poor rehabilitation, to facilitate subsequent analysis of the data characteristics and patterns corresponding to different categories. Association rule algorithms are a data mining technique used to discover the relationships between different variables in the data. For example, in cases of good rehabilitation, association rule algorithms can uncover specific relationships between the musical attributes of a musical piece and changes in physiological indicators, or the association between transcutaneous electrical stimulation intensity of music and VAS pain scores. Rehabilitation influencing factors refer to variables or parameter combinations that are significantly associated with rehabilitation effects, discovered through association rule algorithms. These are specific characteristics of physiotherapy parameter configurations, physiological indicator change curves, or key indicators in VAS pain scores and joint mobility recovery data.

[0033] Optionally, historical physiotherapy data can be categorized according to rehabilitation effects. Further analysis of physiotherapy data from 1000 patients with soft tissue injuries reveals three categories based on the reduction in VAS pain scores and the recovery of joint mobility: a VAS score reduction of over 50% and joint mobility recovery of over 80% are considered good rehabilitation; a VAS score reduction of 30%-50% and joint mobility recovery of 50%-80% are considered average rehabilitation; and a VAS score reduction of less than 30% and joint mobility recovery of less than 50% are considered poor rehabilitation. This classification method provides a clear direction for subsequent data analysis.

[0034] Association rule algorithms were used to mine the categorized data to identify factors significantly related to rehabilitation outcomes. Further algorithmic analysis revealed a significant positive correlation between the musical attributes of the five-piece music piece and changes in physiological indicators in cases of good rehabilitation. This indicates that a reasonable configuration of the musical attributes of the five-piece music piece can significantly promote improvements in physiological indicators. Simultaneously, a negative correlation was found between the intensity of transcutaneous electrical stimulation (TES) and VAS pain scores, meaning that appropriate TES intensity can effectively reduce patients' pain. Furthermore, key physiological indicator changes were identified, such as the correlation between increased skin temperature and improved tissue oxygen saturation, which was more pronounced in cases of good rehabilitation. Ideally, systematically mining multidimensional factors related to rehabilitation outcomes from historical data allows for adjusting the parameter configuration of the multimodal collaborative physiotherapy model to better suit the individual patient's needs, thereby improving the adaptability and rehabilitation effectiveness of the physiotherapy plan.

[0035] Furthermore, the iterative optimization module 13 is used to perform the following method: The deviation between the actual rehabilitation effect and the expected effect corresponding to the collaborative physiotherapy parameters output by the multimodal collaborative physiotherapy model is used as the optimization error; the optimization error is used as the objective function for iterative optimization, and the five-tone attribute matching parameters, the intensity and frequency of transcutaneous electrical stimulation of music, the near-infrared target temperature and the acupoint stimulation combination scheme are adjusted in each iteration.

[0036] In one embodiment, synergistic physiotherapy parameters refer to various physiotherapy parameters involved in the multimodal synergistic physiotherapy model, including the five-tone attributes in music therapy with five musical pieces, the intensity and frequency of transcutaneous electrical stimulation of music in physical physiotherapy, the target temperature of near-infrared photothermal therapy, and the acupoint stimulation combination scheme in acupoint therapy. The synergistic physiotherapy parameters work together to determine the specific implementation method of the physiotherapy plan. The actual rehabilitation effect refers to the rehabilitation status obtained by the patient after receiving physiotherapy through physiological indicators, VAS pain scores, joint range of motion, and other indicators. Physiological indicators include skin temperature, bioimpedance, surface electromyography, and tissue blood oxygen saturation.

[0037] The expected effect refers to the pre-set physiotherapy goal based on factors such as the patient's injury symptoms, disease stage, and physical characteristics. The optimization error refers to the difference between the actual rehabilitation effect and the expected effect, usually expressed numerically, reflecting the gap between the current physiotherapy plan and the ideal plan. Iterative optimization refers to the process of minimizing the optimization error by gradually adjusting the physiotherapy parameters. Each iteration adjusts the five-tone attribute matching parameters, the intensity and frequency of transcutaneous electrical stimulation of music, the target temperature of near-infrared photothermal therapy, and the combination of acupoint stimulation according to the optimization error, until the error reaches the minimum or the preset number of iterations is met.

[0038] Optionally, physiotherapy can be implemented using synergistic physiotherapy parameters output by a multimodal synergistic physiotherapy model. The actual rehabilitation effect can be evaluated based on data such as the patient's physiological indicators, VAS pain score, and joint range of motion. For example, after one physiotherapy session, a patient's VAS pain score decreased from 8 to 6, and joint range of motion recovered from 30% to 40%, while the expected effect was a VAS pain score decrease to 4 and joint range of motion recovery to 50%. These optimization errors are used as the objective function for iterative optimization. In each iteration, the physiotherapy parameters are adjusted based on the optimization errors. If the optimization error of the VAS pain score is large, it may be necessary to adjust the pentatonic properties of the music therapy in the pentatonic music to better meet the patient's physiological and psychological needs. If the optimization error of joint range of motion is large, it may be necessary to adjust the intensity and frequency of transcutaneous electrical stimulation of the music to better promote the recovery of soft tissues such as muscles and joints.

[0039] Simultaneously, the near-infrared photothermal therapy target temperature and acupoint stimulation combination are adjusted based on optimization errors to ensure improved overall therapeutic effects. Through these steps, therapeutic parameters can be dynamically adjusted based on real-time patient feedback, achieving personalized and precise therapy that is significantly superior to traditional fixed-parameter therapy programs. This data-driven dynamic optimization method not only improves the adaptability of the therapy program but also significantly enhances rehabilitation efficiency and effectiveness, providing a more scientific and effective solution for the treatment of soft tissue injuries.

[0040] Furthermore, the iterative optimization module 13 is also used to perform the following method: The multimodal synergistic physiotherapy model is used to integrate the synergistic therapeutic effects of five-tone therapy, transcutaneous electrical stimulation of music, near-infrared photothermal therapy, and acupoint targeted stimulation.

[0041] In one embodiment, the multimodal synergistic physiotherapy model refers to a comprehensive physiotherapy model that integrates various types of physiotherapy methods, including five-tone therapy, transcutaneous electrical stimulation of music, near-infrared photothermal therapy, and acupoint targeted stimulation. Furthermore, five-tone therapy refers to using the five tones (Gong, Shang, Jiao, Zhi, and Yu, which have different frequencies and rhythmic characteristics) based on traditional Chinese medicine theory to regulate the patient's psychology and physiology. For example, the Gong tone has a lower frequency and is suitable for relieving anxiety; the Zhi tone has a higher frequency and is suitable for improving mental state. Transcutaneous electrical stimulation of music refers to transmitting currents of specific five-tone attributes with corresponding intensities and frequencies to the human body through electrodes, stimulating soft tissues such as nerves and muscles, promoting local blood circulation, relieving pain, and accelerating tissue repair.

[0042] Near-infrared photothermal therapy utilizes the light and heat effects of near-infrared light to improve local tissue microcirculation, reduce inflammation, and promote wound healing. Near-infrared light can penetrate the skin to a certain depth and act on deep tissues, producing non-thermal biological effects. Near-infrared rays have shorter wavelengths and higher energy than far-infrared rays, and can penetrate the body to a depth of nearly 10mm, which is 10 times that of far-infrared rays. Its photon energy can penetrate into the blood vessels, lymphatic vessels, nerve endings, and subcutaneous tissues deep in the human body and be absorbed by these tissues, producing significant photoelectric and photobiochemical effects. The non-thermal biological effects produced by near-infrared rays can regulate the body's immune function, endocrine function, and autonomic nervous function, and have good clinical efficacy. Acupoint targeted stimulation refers to the precise stimulation of specific acupoints based on the theory of meridians in traditional Chinese medicine, through electrical stimulation, photothermal stimulation or other methods, to regulate the flow of qi and blood in the meridians and promote the body's self-repair ability. Synergistic physiotherapy refers to the cooperation of these different physiotherapy methods in a multimodal synergistic physiotherapy model to exert a comprehensive therapeutic effect. By rationally configuring the parameters of each physiotherapy method, multiple goals such as physiological regulation, psychological relief and meridian unblocking can be achieved.

[0043] Optionally, the multimodal synergistic physiotherapy model integrates five-tone therapy, transcutaneous electrical stimulation with music, near-infrared photothermal therapy, and acupoint targeted stimulation to achieve comprehensive physiotherapy from psychological to physiological perspectives. Specifically, for a patient with acute soft tissue strain, the model first provides soothing music through five-tone therapy to help relieve anxiety and reduce psychological stress. At the same time, transcutaneous electrical stimulation at a frequency of 10Hz and an intensity of 1mA acts on the injured area to promote local blood circulation and relieve muscle tension. Near-infrared photothermal therapy uses a set target temperature to provide photothermal therapy to the injured area, improving local microcirculation and reducing inflammation. In addition, the model also uses acupoint targeted stimulation to provide moderate-intensity transcutaneous electrical stimulation with music and photothermal therapy to the Zusanli acupoint, regulating the flow of Qi and blood in the meridians and promoting the body's self-repair ability.

[0044] Preferably, the multimodal collaborative physiotherapy model, by integrating multiple physiotherapy methods, can more comprehensively meet the rehabilitation needs of patients and significantly improve the physiotherapy effect. In addition, the multimodal collaborative physiotherapy model can also dynamically adjust the parameters of each physiotherapy method according to the patient's real-time feedback. Furthermore, if the patient reports that the pain is not significantly relieved during the physiotherapy process, the multimodal collaborative physiotherapy model can appropriately increase the intensity of transcutaneous electrical stimulation of music or adjust the target temperature of near-infrared photothermal therapy. This dynamic adjustment mechanism further improves the personalization and precision of the physiotherapy plan, providing a more scientific and effective solution for the physiotherapy of soft tissue injuries.

[0045] Furthermore, the iterative optimization module 13 is also used to perform the following method: A reinforcement learning mechanism is introduced, which uses the reduction of optimization error and the improvement of rehabilitation indicators as reward signals, and the increase of optimization error and abnormal physiological indicators as punishment signals, to dynamically adjust the weight coefficients of the music therapy channel, physical therapy channel and acupoint therapy channel of the five musical pieces.

[0046] In one embodiment, reinforcement learning is a machine learning method that learns optimal behavioral strategies through the interaction between an agent and its environment. This mechanism dynamically adjusts parameters in the multimodal collaborative physiotherapy model to optimize therapeutic effects. A reward signal is the positive feedback given when the behavior of the multimodal collaborative physiotherapy model leads to a reduction in optimization error or an improvement in physiological indicators. Specifically, a decrease in the patient's VAS pain score or an improvement in joint mobility is considered a reward signal. A penalty signal is the negative feedback given when the model's behavior leads to an increase in optimization error or abnormal physiological indicators. Specifically, an abnormal increase in the patient's skin temperature or an abnormal change in bioimpedance is considered a penalty signal. Weighting coefficients are the relative importance parameters assigned to the music therapy channel, physical therapy channel, and acupoint therapy channel of the five musical pieces in the multimodal collaborative physiotherapy model. The weighting coefficients of these channels determine their contribution ratio in the overall physiotherapy plan.

[0047] Optionally, treatment can be implemented based on current physiotherapy parameters, and the patient's physiological indicators, VAS pain score, and joint mobility recovery can be monitored in real time. For example, after one physiotherapy session, if the VAS pain score decreases from 8 to 6 and joint mobility recovers from 30% to 40%, but skin temperature slightly increases, the physiotherapy effect can be judged based on the changes in these indicators. If the optimization error decreases or physiological indicators improve, such as a decrease in VAS pain score or recovery in joint mobility, these changes are considered reward signals, thereby increasing the weight coefficient of the corresponding physiotherapy channel. Furthermore, if transcutaneous electrical stimulation of music significantly reduces the patient's VAS pain score, the system will increase the weight coefficient of the physical physiotherapy channel to further enhance this effect.

[0048] Conversely, if the optimization error increases or physiological indicators become abnormal—for example, if the VAS pain score does not decrease or even increases, or if skin temperature rises abnormally—these changes are treated as penalty signals, thereby reducing the weight coefficient of the corresponding physiotherapy channel. Furthermore, if the abnormally high skin temperature may be due to excessively high near-infrared photothermal therapy temperature, the system will reduce the weight coefficient of the near-infrared photothermal therapy channel to avoid adverse effects on the patient. In the above steps, the reinforcement learning mechanism can dynamically adjust the weight coefficients of each physiotherapy channel, enabling the model to continuously optimize the physiotherapy plan based on the patient's real-time feedback, significantly improving the adaptability and rehabilitation effect of the physiotherapy plan.

[0049] Furthermore, the iterative optimization module 13 is also used to perform the following method: The rehabilitation difficulty index is assessed based on the severity and stage of soft tissue injury; the maximum number of iterations is dynamically configured according to the rehabilitation difficulty index.

[0050] In one embodiment, the severity of soft tissue injury refers to the degree of injury, which is usually assessed through clinical examination and relevant test indicators including the degree of tissue inflammation, pain score, and joint range of motion. For example, a mild injury may only manifest as mild local pain and swelling, while a severe injury may be accompanied by significant functional impairment and tissue tearing. The course of the disease refers to the time stage after the injury, which is usually divided into the acute phase, the subacute phase, and the recovery phase. Specifically, the acute phase is less than 7 days, the subacute phase is 7 to 30 days, and the recovery phase is more than 30 days. The treatment focus and physical therapy parameters are different in different stages.

[0051] The rehabilitation difficulty index is a comprehensive assessment indicator used to quantify the difficulty of rehabilitation. It is calculated based on the severity of the injury and the stage of the disease, reflecting the challenges that patients may face during rehabilitation. For example, the rehabilitation difficulty index may be higher for severe injuries in the acute phase. The maximum number of iterations refers to the maximum number of iterations allowed during parameter optimization. The more iterations, the longer the model optimization time, but the better the optimization effect may be. The maximum number of iterations is dynamically configured through the rehabilitation difficulty index to ensure that the optimization process is both efficient and accurate.

[0052] Optionally, the rehabilitation difficulty index can be assessed based on the severity and stage of the soft tissue injury.

[0053] Furthermore, the recommended physiotherapy plan list output module 14 is used to perform the following method: Connect to a multimodal detection terminal to mark soft tissue injury areas; based on the soft tissue injury areas, match the corresponding five-music music prescriptions, physical parameter configuration schemes and acupoint stimulation prescriptions in the five-music music prescription database, soft tissue injury database and acupoint prescription database to construct a differential physiotherapy basic framework.

[0054] In one embodiment, a multimodal detection terminal refers to a device that integrates multiple detection methods for real-time monitoring and recording of information related to soft tissue injuries. The detection methods may include ultrasound imaging, infrared thermography, bioelectric detection, etc., which can provide detailed physiological information of the injured area. Marking the soft tissue injury area refers to determining the specific location, extent, and degree of injury through data obtained by the multimodal detection terminal. For example, ultrasound imaging can clearly show the tear site of muscles or ligaments, and infrared thermography can detect local blood flow and inflammation.

[0055] The Five-Music Prescription Database stores musical pieces and combinations thereof with different musical attributes (including the five notes of the pentatonic scale, such as Gong, Shang, Jiao, Zhi, and Yu, which have different frequencies and rhythmic characteristics). These musical prescriptions for the Five-Music scale are designed for specific injuries and rehabilitation stages, and can regulate the patient's psychological state and physiological response. The Soft Tissue Injury Database stores the characteristics of different injuries such as contusions, strains, tears, and inflammation, along with corresponding physiotherapy parameter configurations, providing reference data for the model. The Acupoint Prescription Database stores acupoint stimulation programs for different injury sites and rehabilitation stages, including information such as single acupoints or combinations of several acupoints, acupoint locations, the intensity and frequency of transcutaneous electrical stimulation, and the target temperature for near-infrared photothermal therapy. The Differential Physiotherapy Framework is a personalized physiotherapy plan framework constructed based on individual patient differences. This framework integrates the specific parameter configurations of the music, physical therapy, and acupoint physiotherapy of the Five-Music scale, providing a foundation for subsequent dynamic optimization.

[0056] Optionally, by connecting to a multimodal detection terminal, detailed information on the patient's soft tissue injury can be obtained in real time, and the injured area can be marked. For example, ultrasound imaging technology can be used to accurately mark the extent of muscle strain, and infrared thermography can detect the severity of local inflammation and the local blood flow status, providing precise targets for subsequent personalized physiotherapy plans. Based on the marked soft tissue injury area, corresponding physiotherapy parameters are matched from the Five Music Prescription Database, the Soft Tissue Injury Database, and the Acupoint Prescription Database. Furthermore, for the injured area marked as a mild strain of the left knee joint, a soothing Gong-tone music with a frequency of 256Hz is selected from the Five Music Prescription Database, and physical parameter configurations suitable for mild strains are selected from the Soft Tissue Injury Database, such as a transcutaneous electrical stimulation intensity of 0.8mA and a frequency of 10Hz. A stimulation scheme for the Zusanli acupoint is selected from the Acupoint Prescription Database, such as a medium intensity, a frequency of 2Hz, and a near-infrared photothermal therapy target temperature of 39℃. Through the above steps, a differentiated physiotherapy framework is constructed, providing each patient with a personalized initial physiotherapy plan. This differentiated physiotherapy framework improves the precision of physiotherapy, ensuring that the entire physiotherapy process can better adapt to the individual physiotherapy needs of patients and enhance rehabilitation outcomes.

[0057] In summary, the beneficial effects of the embodiments of this application are: The system employs a multimodal collaborative physiotherapy model building module, which establishes a multimodal collaborative physiotherapy model corresponding to soft tissue injury conditions based on the music therapy channel, physical therapy channel, and acupoint therapy channel of the Five Musical Pieces. Soft tissue injury conditions include tissue contusion, tissue strain, tissue tear, and tissue inflammation. A rehabilitation influencing factor determination module is used to determine rehabilitation influencing factors based on historical physiotherapy data, including injury condition, disease stage, physical characteristics, and physiological indicators. Physiological indicators include skin temperature, bioimpedance, surface electromyography, and tissue oxygen saturation. An iterative optimization module is used to iteratively optimize the parameters of the multimodal collaborative physiotherapy model based on rehabilitation influencing factors until the maximum number of iterations is reached. A recommended physiotherapy plan output module is used to output a list of recommended physiotherapy plans based on the iteratively optimized multimodal collaborative physiotherapy model and the Five Musical Pieces prescription database, soft tissue injury database, and acupoint prescription database. This application provides a comprehensive multimodal physiotherapy device and method for soft tissue injuries. It integrates music, physical therapy, and acupoint therapy channels of five musical pieces to construct a multimodal collaborative physiotherapy model. Based on historical physiotherapy data, it identifies rehabilitation influencing factors and iteratively optimizes the parameters of the multimodal collaborative physiotherapy model. This allows the physiotherapy parameters to be dynamically adjusted according to the patient's physiological indicators during the rehabilitation process, adapting to the personalized physiotherapy needs at different stages of the disease and improving the technical effect of matching the physiotherapy plan with the individual patient's physiotherapy needs.

[0058] Example 2, based on the same inventive concept as the comprehensive multimodal physiotherapy device for soft tissue injuries described in the foregoing examples, such as... Figure 2 As shown, this application provides a comprehensive multimodal physical therapy method for soft tissue injuries, the method comprising: Based on the music therapy channel, physical therapy channel, and acupoint therapy channel of five musical pieces, a multimodal collaborative therapy model corresponding to soft tissue injury symptoms is established, including tissue contusion, tissue strain, tissue tear, and tissue inflammation.

[0059] Based on historical physiotherapy data, rehabilitation influencing factors were identified, including injury symptoms, disease stage, physical characteristics, and physiological indicators, such as skin temperature, bioimpedance, surface electromyography, and tissue oxygen saturation.

[0060] Based on the aforementioned rehabilitation influencing factors, the parameters of the multimodal collaborative physiotherapy model are iteratively optimized until the maximum number of iterations is reached.

[0061] Using the iteratively optimized multimodal collaborative physiotherapy model, and comparing it with the five-music prescription database, soft tissue injury database, and acupoint prescription database, a list of recommended physiotherapy plans is output.

[0062] Furthermore, this application provides a method for identifying rehabilitation influencing factors based on historical physiotherapy data, including injury symptoms, disease stage, physical characteristics indicators, and physiological indicators. The method includes: The historical physiotherapy data is categorized according to rehabilitation effects. The historical physiotherapy data includes physiotherapy parameter configurations, physiological index change curves, VAS pain scores, and joint range of motion recovery data. Based on the categorized historical physiotherapy data, an association rule algorithm is used to mine the rehabilitation influencing factors corresponding to the mapping relationships.

[0063] Furthermore, this application provides a method for iteratively optimizing the parameters of the multimodal collaborative physiotherapy model, the method comprising: The deviation between the actual rehabilitation effect and the expected effect corresponding to the collaborative physiotherapy parameters output by the multimodal collaborative physiotherapy model is used as the optimization error; the optimization error is used as the objective function for iterative optimization, and the five-tone attribute matching parameters, the intensity and frequency of transcutaneous electrical stimulation of music, the target temperature of near-infrared photothermal therapy, and the acupoint stimulation combination scheme are adjusted in each iteration.

[0064] Furthermore, the method of this application also includes: The multimodal synergistic physiotherapy model is used to integrate the synergistic therapeutic effects of five-tone therapy, transcutaneous electrical stimulation of music, near-infrared photothermal therapy, and acupoint targeted stimulation.

[0065] Furthermore, the method of this application also includes: A reinforcement learning mechanism is introduced, which uses the reduction of optimization error and the improvement of rehabilitation indicators as reward signals, and the increase of optimization error and abnormal physiological indicators as punishment signals, to dynamically adjust the weight coefficients of the music therapy channel, physical therapy channel and acupoint therapy channel of the five musical pieces.

[0066] Furthermore, the method of this application also includes: The rehabilitation difficulty index is assessed based on the severity and stage of soft tissue injury; the maximum number of iterations is dynamically configured according to the rehabilitation difficulty index.

[0067] Furthermore, this application provides a database of prescriptions for five musical pieces, a database of soft tissue injuries, and a database of prescriptions for acupoints, and outputs a list of recommended physiotherapy plans. The method includes: Connect to a multimodal detection terminal to mark soft tissue injury areas; based on the soft tissue injury areas, match the corresponding five-music music prescriptions, physical parameter configuration schemes and acupoint stimulation prescriptions in the five-music music prescription database, soft tissue injury database and acupoint prescription database to construct a differential physiotherapy basic framework.

[0068] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, the above description focuses on specific embodiments of this specification. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0069] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0070] This specification and accompanying drawings are merely illustrative examples of this application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Therefore, if such modifications and modifications fall within the scope of this application and its equivalents, this application intends to include such modifications and modifications.

Claims

1. A comprehensive multimodal physiotherapy device for soft tissue injuries, characterized in that, The device includes: The multimodal collaborative physiotherapy model establishment module is used to establish a multimodal collaborative physiotherapy model corresponding to soft tissue injury symptoms based on the music physiotherapy channel, physical physiotherapy channel, and acupoint physiotherapy channel of five musical pieces. The soft tissue injury symptoms include tissue contusion, tissue strain, tissue tear, and tissue inflammation. The rehabilitation influencing factor determination module is used to determine rehabilitation influencing factors based on historical physiotherapy data, including injury symptoms, disease stage, physical characteristics indicators, and physiological indicators, including skin temperature, bioimpedance, surface electromyography, and tissue blood oxygen saturation. The iterative optimization module is used to perform iterative optimization of the parameters of the multimodal collaborative physiotherapy model based on the rehabilitation influencing factors until the maximum number of iterations is reached; The recommended physiotherapy plan list output module is used to output a list of recommended physiotherapy plans by comparing the iteratively optimized multimodal collaborative physiotherapy model with the five-music prescription database, soft tissue injury database and acupoint prescription database.

2. The comprehensive multimodal physiotherapy device for soft tissue injuries as described in claim 1, characterized in that, Based on historical physiotherapy data, rehabilitation influencing factors were identified, including injury symptoms, disease stage, physical characteristics, and physiological indicators, including: The historical physiotherapy data is categorized according to rehabilitation effects, including physiotherapy parameter configurations, physiological index change curves, VAS pain scores, and joint range of motion recovery data. Based on the classified historical physiotherapy data, the association rule algorithm was used to mine the rehabilitation influencing factors corresponding to the mapping relationship.

3. The comprehensive multimodal physiotherapy device for soft tissue injuries as described in claim 2, characterized in that, The multimodal collaborative physiotherapy model is subjected to parameter iterative optimization, including: The deviation between the actual rehabilitation effect and the expected effect corresponding to the collaborative physiotherapy parameters output by the multimodal collaborative physiotherapy model is used as the optimization error; Using the optimization error as the objective function for iterative optimization, each iteration adjusts the five-tone attribute matching parameters, the intensity and frequency of transcutaneous electrical stimulation of music, the near-infrared target temperature, and the acupoint stimulation combination scheme.

4. The comprehensive multimodal physiotherapy device for soft tissue injuries as described in claim 3, characterized in that, include: The multimodal synergistic physiotherapy model is used to integrate the synergistic therapeutic effects of five-tone therapy, transcutaneous electrical stimulation of music, near-infrared photothermal therapy, and acupoint targeted stimulation.

5. The comprehensive multimodal physiotherapy device for soft tissue injuries as described in claim 4, characterized in that, include: A reinforcement learning mechanism is introduced, which uses the reduction of optimization error and the improvement of rehabilitation indicators as reward signals, and the increase of optimization error and abnormal physiological indicators as punishment signals, to dynamically adjust the weight coefficients of the music therapy channel, physical therapy channel and acupoint therapy channel of the five musical pieces.

6. The comprehensive multimodal physiotherapy device for soft tissue injuries as described in claim 5, characterized in that, include: The rehabilitation difficulty index is assessed based on the severity and stage of soft tissue injury. The maximum number of iterations is dynamically configured proportionally based on the rehabilitation difficulty index.

7. The comprehensive multimodal physiotherapy device for soft tissue injuries as described in claim 1, characterized in that, Based on the Five Music Prescription Database, Soft Tissue Injury Database, and Acupoint Prescription Database, a list of recommended physiotherapy plans is generated, including: Connect to a multimodal detection terminal to mark soft tissue injury areas; Based on the soft tissue injury area, the corresponding five-music music prescriptions, physical parameter configuration schemes, and acupoint stimulation prescriptions are matched with the five-music music prescription database, soft tissue injury database, and acupoint prescription database to construct a differential physiotherapy framework.

8. A comprehensive multimodal physical therapy method for soft tissue injuries, characterized in that, For implementing the comprehensive multimodal physiotherapy device for soft tissue injuries according to any one of claims 1-7, the method comprises: Based on the music therapy channel, physical therapy channel, and acupoint therapy channel of five musical pieces, a multimodal collaborative therapy model corresponding to soft tissue injury symptoms is established, including tissue contusion, tissue strain, tissue tear, and tissue inflammation. Based on historical physiotherapy data, rehabilitation influencing factors were identified, including injury symptoms, disease stage, physical characteristics, and physiological indicators, such as skin temperature, bioimpedance, surface electromyography, and tissue oxygen saturation. Based on the aforementioned rehabilitation influencing factors, the parameters of the multimodal collaborative physiotherapy model are iteratively optimized until the maximum number of iterations is reached; Using the iteratively optimized multimodal collaborative physiotherapy model, and comparing it with the five-music prescription database, soft tissue injury database, and acupoint prescription database, a list of recommended physiotherapy plans is output.

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