AI intelligent system for physical therapy testing, evaluation and auxiliary decision making

Abstract

The invention discloses an AI intelligent system for physical therapy testing, evaluation and auxiliary decision making, which is an innovative system integrating an AI intelligent technology and professional knowledge, and aims to provide comprehensive support for physical therapists, exercise rehabilitation therapists, fitness coaches and vast users. Clinical and non-clinical test and evaluation modules are arranged in the system, and multiple aspects of physical ability, posture, pain, functions, visual diagnosis, palpation, cardiopulmonary functions, muscle nerves and the like are covered. By analyzing a large amount of test data, the system provides deep data insight and comprehensive judgment for professionals, so that body problems are accurately diagnosed, and a personalized rehabilitation scheme is formulated. Along with time and data accumulation, the system is evolved into a user-oriented AI intelligent language model physical treatment evaluation tool, so that the user can easily perform self-test and evaluation and obtain a personalized solution. The innovative scheme can assist the user in knowing the source of the body problem and inject new vitality to the whole health.

Description

Technical Field

[0001] Data collection and processing technology: The system has a data collection interface that can collect patient / user related data, such as body posture, pain perception, functional ability, cardiopulmonary function, and muscle nerve status. At the same time, the system has data cleaning and preprocessing functions to denoise, optimize and extract features from the collected test data to ensure the accuracy and reliability of the data.

[0002] Test and Assessment Module Technology: The system provides multiple test and assessment modules, including posture test and assessment, pain test and assessment, functional test and assessment, visual examination, palpation, cardiopulmonary function test, muscle nerve test and physical fitness test and assessment. Each module involves different technologies, such as image analysis, pain assessment tools, motion measurement, heart rate monitoring, muscle strength test, etc.

[0003] Data model and algorithm application technology: Based on AI technology, the system uses machine learning, data mining and other algorithms and models to analyze and extract features from test data. The system uses these data models and algorithms to generate accurate evaluation results and personalized decision-making plans through analysis and processing of test data. This involves statistics, pattern recognition, classification algorithms, regression analysis and other related technologies.

[0004] Decision support technology: The system's decision support module uses AI technology, combined with assessment results and professional knowledge, to provide personalized decision-making advice to physical therapists, sports rehabilitators, fitness coaches and users. This includes developing rehabilitation plans, training programs and targeted treatment strategies. The system helps decision makers make more accurate and effective decisions in a data-driven way.

[0005] Tool making technology: The system has the tool making function of making test and evaluation tools, and can add test and evaluation tools based on the latest research and development results. This means that the system has flexibility and scalability, and can customize and develop test and evaluation tools according to specific needs to adapt to different professional fields and individual needs.

[0006] Data security and privacy protection technology: The system collects and processes personal health data, so it needs to have advanced data security and privacy protection technology. This includes data encryption, identity authentication, access control, and data anonymization to ensure the confidentiality and security of patient / user data.

[0007] User interface and interaction design technology: The user interface of the system should be simple, intuitive and easy to use. Human-computer interaction technology, such as graphical interface, voice interaction or touch screen, should be used to enable users to easily input data, view evaluation results and decision suggestions, and interact with the system.

[0008] Cloud computing and distributed system technologies: In order to process large amounts of test data and provide real-time evaluation results, the system can use cloud computing and distributed system technologies. These technologies can provide high-performance computing and storage capabilities and support system scalability and parallel processing.

[0009] Mobile applications and remote monitoring technology: Considering that physical therapists, sports rehabilitation therapists and users may need to use the system anytime and anywhere, the system can develop mobile applications to support testing, evaluation and decision-making on mobile devices. In addition, the system can also use remote monitoring technology to monitor patient / user data in real time through sensors or wearable devices to provide remote assistance and monitoring.

[0010] Data sharing and collaboration platform technology: To promote cooperation and knowledge sharing among healthcare professionals, the system can provide data sharing and collaboration platform technology. This can include functions such as sharing anonymized test data, discussing cases, and exchanging treatment strategies to promote academic exchanges and professional cooperation within the industry. Background Art

[0011] Artificial Intelligence (AI) and Machine Learning (ML) technologies: AI and ML technologies are widely used in the healthcare field, capable of processing large-scale data and providing accurate analysis and predictions. These technologies can help the system identify and analyze patient / user test data and generate personalized assessment results and decision recommendations.

[0012] Data analysis and mining technology: Data analysis and mining technology can be used to process and analyze test data to discover patterns, correlations and trends in the data. By applying these technologies, the system can extract useful information and features from large amounts of test data, providing a reliable basis for evaluation and decision-making.

[0013] Sensor technology: Intelligent systems for physical therapy testing, assessment, and decision support may utilize various sensors to collect relevant data from patients / users. For example, motion sensors, heart rate monitors, and electromyographic sensors can be used to measure and monitor key indicators such as patient / user movement, cardiopulmonary function, and muscle nerve status.

[0014] Image and video processing technology: Image and video processing technology can be applied to posture test assessment, visual examination and palpation. Through the analysis and processing of image and video data, the system can identify and evaluate the patient / user's posture, posture, body structure and other information, and assist decision makers in making accurate assessments and decisions.

[0015] Data security and privacy protection technologies: Considering that the system involves sensitive personal health data, data security and privacy protection technologies are indispensable. These technologies include measures such as data encryption, authentication, access control, and anonymization to ensure the confidentiality and security of patient / user data.

[0016] Mobile applications and remote monitoring technology: With the development of mobile technology, mobile applications and remote monitoring technology are widely used in the field of healthcare. Intelligent systems for physical therapy testing, evaluation and decision support can use mobile applications and remote monitoring technology to enable patients / users to conveniently conduct tests, evaluations and receive decision-making advice, while achieving remote assistance and monitoring.

[0017] Cloud computing and distributed system technologies: In order to process large-scale test data and provide real-time evaluation results, the system can utilize cloud computing and distributed system technologies. These technologies can provide high-performance computing and storage capabilities and support system scalability and parallel processing. Summary of the invention

[0018] Input interface: The system has input interfaces for collecting patient / user related data. Through these interfaces, patients / users can easily input relevant information and data, including body posture, pain perception, functional ability, etc.

[0019] Test module: The system provides multiple test evaluation modules for posture test evaluation, pain test evaluation, functional test evaluation, visual examination, palpation, cardiopulmonary function test, muscle nerve test and physical fitness test evaluation, etc. Each module has corresponding tools and algorithms to accurately measure and evaluate the relevant indicators of patients / users.

[0020] Tool creation function: The system has the tool creation function for creating test evaluation tools, which can be added based on the latest research and development results. This makes the system flexible and scalable, and can customize and develop test evaluation tools according to specific needs to adapt to different professional fields and individual needs.

[0021] Data processing module: The system is equipped with a data processing module for cleaning, preprocessing and feature extraction of the collected test data. This ensures the accuracy and reliability of the data and provides a reliable basis for subsequent data analysis and decision-making.

[0022] AI decision support module: Based on AI technology, the system uses algorithms and models such as machine learning and data mining to analyze and process test data. The AI ​​decision support module generates accurate evaluation results and personalized decision plans based on evaluation results and professional knowledge. This helps physical therapists, sports rehabilitators, fitness coaches and users make accurate and effective decisions.

[0023] Output interface: The system provides output interfaces to provide assessment results and decision suggestions to physical therapists, sports rehabilitation therapists, fitness coaches and users. These interfaces can be in the form of graphical interfaces, report generation, voice prompts or mobile applications, so that users can easily view and understand the assessment results. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 :System flow chart Figure 2 : Example of physical fitness test evaluation Figure 3 : Example of ankle physical examination pain test assessment Figure 4 :Test content example - International Classification of Functioning, Disability and Health Rehabilitation Battery (ICF-RS) assessment standards Figure 5 : Make a test evaluation tool example Figure 1 Figure 6 : Make a test evaluation tool example Figure 2 Figure 7 :Test evaluation tool display diagram DETAILED DESCRIPTION

[0025] Data collection: a. Design and develop input interfaces to support patients / users to input relevant information and data through the system. This can be done through a graphical interface, form filling, or voice input. b. Optionally, the system can be integrated with sensor devices to collect more objective data, such as motion sensors, heart rate monitors, muscle tension sensors, etc. Sensor data can interact with the system in real time through the interface.

[0026] Test modules: a. Develop a posture test assessment module to provide image or video analysis tools to assess the patient / user's posture and position. This can include assessments of standing, walking, sitting, etc. b. Develop a pain test assessment module to provide pain assessment tools and questionnaires to help patients / users describe the type, location and degree of pain. c. Develop a functional test assessment module to provide a series of functional test items, such as balance, coordination, flexibility, strength, etc. This can include standard test items and personalized test items. d. Develop an inspection and palpation module to provide visual and tactile tools to help physical therapists or professionals observe and detect the patient / user's condition. e. Develop a cardiopulmonary function test module to provide tools such as heart rate monitoring and spirometry to assess the patient / user's cardiopulmonary function and endurance. f. Develop a muscle and nerve test module to provide muscle strength tests and nerve function assessment tools to assess the patient / user's muscle and nervous system conditions. g. Develop a physical fitness test assessment module that provides tools such as strength test, flexibility test, endurance test, balance test and agility test to assess the patient / user's overall physical fitness level and sports performance.

[0027] Data processing: a. Design and implement data cleaning and preprocessing functions, denoise and optimize the collected test data to ensure the accuracy and reliability of the data. b. Develop data analysis and feature extraction functions, and use data analysis and mining techniques to extract useful features and indicators from test data. c. Design and implement data model and algorithm application functions, and use machine learning, data mining and other technologies to analyze data and generate evaluation results. The system can use pre-trained models and algorithms, and adjust and optimize them according to actual needs.

[0028] AI decision support module: a. Design and develop AI decision support modules to generate accurate assessment results and personalized decision recommendations based on the results of data analysis. This includes functions such as visualization of assessment results, generation of decision recommendations, and formulation of rehabilitation plans. b. Optionally, the system can be integrated with the knowledge and experience of professionals to provide more personalized and professional assessment and decision support.

[0029] Test the evaluation tool production function: a. Determine the goal and purpose of the evaluation tool. According to the needs of physical therapy, sports rehabilitation or fitness training, determine the type and function of the evaluation tool to be produced. b. Collect relevant data and indicators. According to the goal of the evaluation tool, collect and organize data and indicators related to the tool, such as body posture, pain level, functional ability, etc. c. Design the interface and interaction method of the evaluation tool. According to the goals and data, design the user interface of the evaluation tool to ensure that users can easily and accurately enter relevant data and information. d. Develop algorithms and computational models for the evaluation tool. According to the collected data and indicators, develop algorithms and computational models that adapt to the goals to achieve data processing and evaluation. e. Test and verify the accuracy and reliability of the evaluation tool. During the system development process, test and verify the evaluation tool to ensure that it can accurately evaluate the user's physical condition and functional ability. f. Integrate the evaluation tool into the system. Integrate the produced evaluation tool into the test module of the system so that it can work with other evaluation tools to achieve comprehensive physical therapy testing and evaluation.

[0030] Output interface: a. Design and implement output interfaces to provide assessment results and decision-making recommendations to physical therapists, sports rehabilitators, fitness coaches, and users. This can be in the form of graphical interface reports, voice prompts, mobile applications, etc. b. Optionally, the system can support the generation of detailed assessment reports and personalized rehabilitation plans to meet the needs of professionals and users.

Claims

1. An AI intelligent system for physical therapy testing, evaluation and decision-making assistance, comprising: a. Input interface for collecting patient / user related data. b. Test modules for posture test assessment, pain test assessment, functional test assessment, visual examination, palpation, cardiopulmonary function test, muscle nerve test, physical fitness test, etc. c. Tool creation function for creating test evaluation tools, which can be added based on the latest research and development results. d. Data processing module for analyzing and processing test data. e. Decision support module based on AI technology for generating accurate evaluation results and personalized decision plans. f. Output interface for providing evaluation results and decision suggestions to physical therapists, sports rehabilitation therapists, fitness coaches and users.

2. The system according to claim 1, wherein the test module comprises: a. Posture test and evaluation module, used to evaluate the posture and position of patients / users: Detect and evaluate the posture and position of patients / users, including standing, walking, sitting, etc. through image or video analysis. Provide quantitative and qualitative posture evaluation results, such as body symmetry, posture deviation, etc. Generate posture improvement suggestions and training guidance based on measurement results and preset standards. b. Pain test and evaluation module, used to evaluate the pain condition and degree of patients / users: Provide pain assessment tools and questionnaires to help patients / users describe the type, location and degree of pain. Evaluate and classify pain through quantitative and qualitative analysis, such as pain intensity, duration, etc. Based on the evaluation results, pain management recommendations and personalized treatment plans are provided. c. Functional test assessment module, used to evaluate the patient / user's physical function and motor ability: a series of functional tests are provided, such as test items in balance, coordination, flexibility, strength, etc. The patient / user's physical function level and motor ability are evaluated through objective measurement and quantitative analysis. Based on the evaluation results, personalized rehabilitation plans and training programs are formulated to improve the functional level. d. Visual and palpation module, used to evaluate the condition through observation and touch: visual and tactile tools are provided to help physical therapists or professionals observe and detect the patient / user's condition. The condition is evaluated by visual observation of body structure and abnormal signs, and tactile detection of lesions, muscle tension, etc. e. Cardiopulmonary function test module, used to evaluate the patient / user's cardiopulmonary function and endurance: cardiopulmonary function test tools such as heart rate monitoring, vital capacity measurement, etc. are provided to evaluate the functional status of the cardiopulmonary system. The patient / user's cardiopulmonary endurance level and rehabilitation needs are determined through exercise testing and endurance evaluation. Based on the evaluation results, a cardiopulmonary function improvement plan and aerobic training plan are formulated. f. Muscle and nerve testing module for assessing the patient / user's muscle and nervous system condition: Provides muscle strength testing tools and test items to assess the patient / user's muscle strength level and function. For example, muscle strength can be assessed by measuring the maximum contraction force of a specific muscle or muscle group. Provide neurological function assessment tools and test items to assess the patient / user's nervous system function. For example, assess the neurological function status by measuring nerve conduction velocity, muscle reaction time or neuromuscular coordination. g. Physical fitness test assessment module, used to assess the patient / user's overall physical fitness level and sports performance, including strength test, flexibility test, endurance test, balance test and agility test: Provide strength test tools and test items to assess the patient / user's muscle strength and explosive power. For example, measure the maximum weight of bench press, squat or weightlifting. Provide flexibility test tools and test items to assess the patient / user's joint flexibility and muscle extension ability. For example, assess by measuring the range of motion of each joint of the body. Provide endurance test tools and test items to assess the patient / user's cardiorespiratory endurance and muscle endurance. For example, test the endurance level through activities such as long-term running, skipping rope or rowing. Provide balance test tools and test items to assess the patient / user's balance ability and body control ability. For example, assess the balance level through single-leg standing, closed-eye balance or balance board test. Agility testing tools and tests are available to assess the patient / user's reaction speed and physical mobility. For example, agility levels can be assessed through tests such as flexible obstacle traversal, lateral movement or rapid changes of direction.

3. The system according to claim 1 or claim 2, wherein the data processing module comprises: a. Data cleaning and preprocessing functions are used to denoise and optimize the collected test data. Data cleaning tools and algorithms are provided to detect and remove outliers, noise, and erroneous data in the test data. Data preprocessing techniques such as interpolation, smoothing, and standardization are implemented to optimize the quality and usability of the data. Through data cleaning and preprocessing, the accuracy and reliability of the test data are ensured, providing a reliable foundation for subsequent data analysis and model application. b. Data analysis and feature extraction functions, used to extract useful features and indicators from test data. Use statistical and data analysis methods to perform exploratory analysis and descriptive statistics on test data to understand the distribution and correlation of data. Use machine learning and data mining techniques to extract relevant features and indicators from test data, such as range of motion, muscle strength, pain score, etc. Through feature selection and dimensionality reduction techniques, extract the most informative and relevant features from a large amount of test data to reduce data dimensions and improve model performance. c. Data model and algorithm application functions, used to apply machine learning, data mining and other technologies to analyze data and generate evaluation results. Based on machine learning algorithms, build data models to analyze test data and generate evaluation results. Algorithms include support vector machines, decision trees, neural networks, etc. Train and optimize data models, and use test data sets for model training and verification to improve the model's prediction accuracy and generalization ability. Apply the trained data model to new test data, and generate accurate evaluation results by inputting test data and using the model for prediction and evaluation.

4. The system according to claim 1, wherein the AI ​​decision support module comprises: a. Models and algorithms based on machine learning and artificial intelligence technologies are used to analyze test data, identify patterns and associations, and generate accurate evaluation results. b. Personalized decision plan generation function provides personalized treatment and training plans for physical therapists, sports rehabilitation therapists, and fitness coaches based on the individual characteristics of patients / users and test results.

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