Intelligent detection exercise rehabilitation system

Abstract

The invention discloses an intelligent detection exercise rehabilitation system, and particularly relates to the technical field of exercise rehabilitation. The system comprises a personalized rehabilitation intelligent planning module for making a personalized rehabilitation plan for each patient by using artificial intelligence and a big data technology, and an intelligent wearable device module for realizing high-precision data acquisition and long-time monitoring through an advanced flexible sensor and an energy collection technology. By integrating personalized rehabilitation intelligent planning, intelligent wearable equipment, intelligent interactive feedback and a data security and privacy protection module, comprehensive rehabilitation support is provided for a patient, artificial intelligence and a big data technology are utilized by the system, comprehensive assessment of the exercise ability and the health state of the patient is achieved, and the rehabilitation effect of the patient is improved. And immersive rehabilitation training experience is provided through the virtual reality technology, the system can dynamically adjust the training scheme through the emotion recognition technology and the adaptive learning algorithm, and individuation and effectiveness of the rehabilitation process are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of sports rehabilitation, and in particular to an intelligent detection sports rehabilitation system. Background Art

[0002] With the acceleration of the aging process of society and the increase in the number of patients with sports injuries and chronic diseases, the demand for rehabilitation treatment is growing rapidly. Traditional rehabilitation treatment often relies on the guidance and supervision of professional medical personnel, and patients need to frequently go to rehabilitation centers for treatment, which not only increases the time and economic costs of patients, but is also constrained by limited medical resources. At the same time, traditional rehabilitation methods lack the ability to be personalized and dynamically adjusted, and it is difficult to meet the different rehabilitation needs of each patient. With the development of artificial intelligence, big data and smart device technology, intelligent detection sports rehabilitation systems have gradually become an important direction in the field of rehabilitation. Improving the efficiency and effectiveness of rehabilitation treatment through intelligent means has become an effective way to solve this problem.

[0003] Existing rehabilitation systems have some shortcomings in practical applications. First, the formulation and adjustment of rehabilitation plans often rely on manual experience, lack of scientific evaluation and dynamic adjustment capabilities, which affects the rehabilitation effect. Secondly, the data acquisition accuracy of traditional rehabilitation equipment is limited, and long-term, high-precision monitoring is impossible, resulting in incomplete data during the rehabilitation process. Furthermore, there is a lack of real-time interactive feedback and guidance during the rehabilitation process, and it is difficult for patients to obtain timely corrections and suggestions, which affects the effectiveness of training. In addition, with the increase in the amount of rehabilitation data, data security and privacy protection have also become an important issue. In order to overcome these shortcomings, we propose an intelligent detection sports rehabilitation system. Summary of the invention

[0004] The purpose of the present invention is to solve the shortcomings in the prior art and to propose an intelligent detection movement rehabilitation system.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] An intelligent detection and sports rehabilitation system, including a personalized rehabilitation intelligent planning module for developing a personalized rehabilitation plan for each patient using artificial intelligence and big data technology, a smart wearable device module for achieving high-precision data collection and long-term monitoring through advanced flexible sensors and energy harvesting technology, a smart interactive feedback module for providing real-time training guidance and feedback based on voice assistants and augmented reality technology, and a data security and privacy protection module for ensuring the security and privacy protection of rehabilitation data using technologies such as blockchain and differential privacy;

[0007] The personalized rehabilitation intelligent planning module includes an intelligent assessment module for comprehensively evaluating the patient's motor ability and health status using artificial intelligence and big data technologies, a virtual reality training module for simulating a rehabilitation training environment through virtual reality technology to provide an immersive training experience, an emotion recognition module for monitoring the patient's psychological state through emotion recognition technologies such as facial expressions and voice intonation to timely adjust the difficulty and method of rehabilitation training, and an adaptive learning algorithm module for dynamically adjusting the training plan and goals according to the patient's rehabilitation progress and feedback using an adaptive learning algorithm;

[0008] The smart wearable device module includes a flexible sensor module for developing flexible sensors that fit the skin using flexible electronic technology to achieve high-precision motion and physiological data acquisition, an energy collection module for providing continuous electrical energy for smart wearable devices through motion energy collection technology, a multimodal sensor fusion module for integrating multiple sensors to achieve multi-dimensional monitoring of patient motion and physiological status, and an intelligent protection module for automatically triggering an early warning or protection mechanism when abnormal motion patterns or physiological indicators are detected.

[0009] The present invention is further configured as follows: the intelligent interactive feedback module includes an intelligent voice assistant module for providing real-time training guidance and feedback through voice recognition and synthesis technology, an augmented reality guidance module for superimposing training guidance information in the patient's field of view using augmented reality technology, a social interaction module for achieving social interaction and experience sharing between patients through an online platform, and a context-aware feedback module for adjusting feedback strategies in combination with the environment and patient context;

[0010] The data security and privacy protection module includes a blockchain data management module for using blockchain technology to achieve decentralized management of sports rehabilitation data, a privacy protection algorithm module for using advanced algorithms such as differential privacy and homomorphic encryption to protect patients' personal privacy data, a dynamic permission control module for flexibly adjusting data access rights according to actual needs, and an anomaly detection and response module for real-time monitoring of abnormal behaviors in data transmission and storage processes and taking timely response measures.

[0011] The present invention is further configured as follows: the multimodal sensor fusion module includes an adaptive sensor configuration module for dynamically adjusting the parameter configuration and perception range of the sensor according to real-time data and environmental changes, an intelligent noise suppression module for automatically identifying and suppressing noise signals in the data using advanced artificial intelligence algorithms, a situational feature extraction module for extracting multimodal data features in combination with the patient's specific situation, a multi-data collaborative processing module for integrating data from multiple sensors for complementary analysis through a multi-source data collaborative processing algorithm, an intelligent motion analysis module for intelligently analyzing the fused multimodal data using a deep learning model to determine complex motion patterns and potential abnormal behaviors, a physiological state intelligent assessment module for intelligently assessing physiological states using a machine learning algorithm based on multimodal data, and a data privacy protection sharing module for using blockchain and differential privacy technology to ensure the security and privacy protection of multimodal data during sharing and transmission;

[0012] The motion analysis module includes a deep learning analysis module for performing feature extraction and pattern recognition on motion data using a deep learning algorithm and an anomaly detection module for detecting anomalies in motion data based on statistical methods and machine learning algorithms;

[0013] The deep learning analysis module branch includes a motion pattern recognition module for detecting and identifying the current motion state of the user, an environment perception module for extracting obstacles and available objects from the user's current environment, and an environment data analysis module for centrally analyzing and processing the data of obstacles and available objects in the environment;

[0014] The abnormality detection module includes an abnormality determination module for analyzing the impact of abnormal situations on users, a fusion decision module for fusing motion data with environmental data to make comprehensive judgments and decisions, a comprehensive judgment module for comprehensive analysis, and an abnormal data collection module for collecting abnormal data determination results.

[0015] The present invention is further configured as follows: the intelligent noise suppression module suppresses noise signals in the data so that the context feature extraction module extracts multimodal data features based on clean data combined with specific contexts; the adaptive sensor configuration module dynamically adjusts the parameter configuration and perception range of the sensor so that the multi-data collaborative processing module integrates the data of multiple sensors through a collaborative processing algorithm to perform complementary analysis; the data after comprehensive processing by the multi-data collaborative processing module is intelligently analyzed by the intelligent motion analysis module using a deep learning model to determine complex motion patterns and potential abnormal behaviors; after determining the motion pattern, the intelligent motion analysis module allows the physiological state intelligent evaluation module to evaluate the physiological state based on these motion data and other multimodal data; the evaluation data generated by the physiological state intelligent evaluation module is shared through a data privacy protection model. The blockchain and differential privacy technology of the block chain ensure the security and privacy protection of the data; the deep learning analysis module extracts and identifies the motion data features, allowing the anomaly detection module to use these features to detect anomalies in the motion data; the motion pattern recognition module detects and identifies the user's motion state, allowing the environmental perception module to extract obstacles and available object data in the current environment; the environmental data collected by the environmental perception module is centrally processed and analyzed by the environmental data analysis module; the abnormal situation determination module analyzes the impact of abnormal situations on the user, allowing the fusion decision module to fuse the motion data with the environmental data to make a comprehensive judgment and decision; the fusion decision module provides a comprehensive judgment basis for the comprehensive judgment module to further analyze and make a final judgment; the analysis results of the comprehensive judgment module are recorded and stored by the abnormal data collection module.

[0016] The present invention is further configured as follows: the intelligent assessment module comprehensively assesses the patient's motor ability and health status by utilizing artificial intelligence and big data technologies, allowing the virtual reality training module to simulate a rehabilitation training environment and provide an immersive training experience; the training experience data provided by the virtual reality training module is monitored by an emotion recognition module using facial expressions, voice intonation and other emotion recognition technologies to monitor the patient's psychological state; the psychological state data monitored by the emotion recognition module allows the adaptive learning algorithm module to dynamically adjust the training plan and goals according to the patient's rehabilitation progress and feedback.

[0017] The present invention is further configured as follows: the flexible sensor module utilizes flexible electronic technology to develop a flexible sensor that fits the skin to achieve high-precision motion and physiological data acquisition, allowing the energy collection module to provide continuous electrical energy for the smart wearable device through motion energy collection technology; the electrical energy provided by the energy collection module supports the multimodal sensor fusion module to integrate multiple sensors to achieve multi-dimensional monitoring of the patient's motion and physiological state; the motion and physiological data monitored by the multimodal sensor fusion module are used by the intelligent protection module to automatically trigger an early warning or protection mechanism when abnormal motion patterns or physiological indicators are detected.

[0018] The present invention is further configured as follows: the intelligent voice assistant module provides real-time training guidance and feedback through voice recognition and synthesis technology, and the information is superimposed by the augmented reality guidance module in the patient's field of view using augmented reality technology; the information and feedback strategy superimposed by the augmented reality guidance module is combined with the social interaction module to realize social interaction and experience sharing between patients through an online platform; the social feedback and environmental data obtained by the social interaction module are used by the contextual perception feedback module to adjust the feedback strategy.

[0019] The present invention is further configured as follows: the blockchain data management module adopts blockchain technology to realize the decentralized management of sports rehabilitation data, and the privacy protection algorithm module uses differential privacy and homomorphic encryption algorithms to protect the patient's personal privacy data; the data protected by the privacy protection algorithm module is flexibly adjusted by the dynamic permission control module for data access rights according to actual needs; the permissions and monitoring results set by the dynamic permission control module allow the anomaly detection and response module to monitor abnormal behaviors in the data transmission and storage process in real time and take timely response measures.

[0020] The beneficial effects of the present invention are:

[0021] 1. The present invention provides patients with comprehensive rehabilitation support by integrating personalized rehabilitation intelligent planning, smart wearable devices, intelligent interactive feedback and data security and privacy protection modules. The system uses artificial intelligence and big data technologies to achieve a comprehensive assessment of the patient's motor ability and health status, and provides an immersive rehabilitation training experience through virtual reality technology. Through emotion recognition technology and adaptive learning algorithms, the system can dynamically adjust the training plan to ensure the personalization and effectiveness of the rehabilitation process. In addition, the system achieves high-precision data collection and long-term monitoring through smart wearable devices, and automatically triggers early warning or protection mechanisms when abnormalities are detected. The intelligent interactive feedback module provides real-time training guidance and feedback, and promotes social interaction and experience sharing among patients through an online platform. The data security and privacy protection module uses blockchain and differential privacy technology to ensure the security and privacy protection of rehabilitation data, thereby improving the efficiency and safety of rehabilitation services as a whole.

[0022] 2. The present invention realizes multi-dimensional monitoring and intelligent analysis of patient movement and physiological state by integrating and processing data from multiple sensors. The adaptive sensor configuration module dynamically adjusts the parameter configuration and perception range of the sensor according to real-time data and environmental changes to ensure the accuracy of data acquisition. The intelligent noise suppression module uses advanced artificial intelligence algorithms to automatically identify and suppress noise signals in the data, provide clean data for the context feature extraction module, and extract multimodal data features in combination with the patient's specific context. The multi-data collaborative processing module uses a collaborative processing algorithm to integrate the data of multiple sensors for complementary analysis. The intelligent motion analysis module uses a deep learning model to determine complex motion patterns and potential abnormal behaviors. The physiological state intelligent assessment module evaluates the physiological state based on multimodal data. The assessment results ensure data security and privacy protection through the blockchain and differential privacy technology of the data privacy protection sharing module. Through the collaborative work of these sub-modules, the multimodal sensor fusion module realizes efficient and accurate monitoring and analysis, which helps to improve the effect of rehabilitation training and the safety of patients. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a schematic diagram of the check-in system flow in the present invention.

[0024] Figure 2 It is a partial flow chart of the multimodal sensor fusion module in the present invention. DETAILED DESCRIPTION

[0025] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0026] Example 1

[0027] like Figure 1 As shown, an intelligent detection and exercise rehabilitation system includes a personalized rehabilitation intelligent planning module for formulating a personalized rehabilitation plan for each patient using artificial intelligence and big data technology, a smart wearable device module for realizing high-precision data collection and long-term monitoring through advanced flexible sensors and energy harvesting technology, an intelligent interactive feedback module for providing real-time training guidance and feedback based on voice assistants and augmented reality technology, and a data security and privacy protection module for ensuring the security and privacy protection of rehabilitation data using technologies such as blockchain and differential privacy;

[0028] The personalized rehabilitation intelligent planning module includes an intelligent assessment module for comprehensively evaluating the patient's motor ability and health status using artificial intelligence and big data technologies, a virtual reality training module for simulating a rehabilitation training environment through virtual reality technology to provide an immersive training experience, an emotion recognition module for monitoring the patient's psychological state through emotion recognition technologies such as facial expressions and voice intonation to timely adjust the difficulty and method of rehabilitation training, and an adaptive learning algorithm module for dynamically adjusting the training plan and goals according to the patient's rehabilitation progress and feedback using an adaptive learning algorithm;

[0029] The smart wearable device module includes a flexible sensor module for developing a flexible sensor that fits the skin using flexible electronic technology to achieve high-precision motion and physiological data acquisition, an energy collection module for providing continuous electrical energy for the smart wearable device through motion energy collection technology, a multimodal sensor fusion module for integrating multiple sensors to achieve multi-dimensional monitoring of patient motion and physiological status, and an intelligent protection module for automatically triggering an early warning or protection mechanism when an abnormal motion pattern or physiological indicator is detected;

[0030] The intelligent interactive feedback module includes an intelligent voice assistant module for providing real-time training guidance and feedback through voice recognition and synthesis technology, an augmented reality guidance module for superimposing training guidance information in the patient's field of view using augmented reality technology, a social interaction module for achieving social interaction and experience sharing between patients through an online platform, and a context-aware feedback module for adjusting feedback strategies in combination with the environment and patient context;

[0031] The data security and privacy protection module includes a blockchain data management module for implementing decentralized management of sports rehabilitation data using blockchain technology, a privacy protection algorithm module for protecting the patient's personal privacy data using advanced algorithms such as differential privacy and homomorphic encryption, a dynamic permission control module for flexibly adjusting data access rights according to actual needs, and an anomaly detection and response module for real-time monitoring of abnormal behaviors in the data transmission and storage process and taking timely response measures;

[0032] The intelligent assessment module comprehensively evaluates the patient's motor ability and health status by using artificial intelligence and big data technology, allowing the virtual reality training module to simulate the rehabilitation training environment to provide an immersive training experience; the training experience data provided by the virtual reality training module is monitored by the emotion recognition module using facial expressions, voice intonation and other emotion recognition technologies to monitor the patient's psychological state; the psychological state data monitored by the emotion recognition module allows the adaptive learning algorithm module to dynamically adjust the training plan and goals according to the patient's rehabilitation progress and feedback;

[0033] The flexible sensor module uses flexible electronic technology to develop flexible sensors that fit the skin to achieve high-precision motion and physiological data collection, allowing the energy collection module to provide continuous power for the smart wearable device through motion energy collection technology; the power provided by the energy collection module supports the multi-modal sensor fusion module to integrate multiple sensors to achieve multi-dimensional monitoring of the patient's motion and physiological state; the motion and physiological data monitored by the multi-modal sensor fusion module are used by the intelligent protection module to automatically trigger an early warning or protection mechanism when abnormal motion patterns or physiological indicators are detected;

[0034] The intelligent voice assistant module provides real-time training guidance and feedback through voice recognition and synthesis technology, and the information is superimposed by the augmented reality guidance module in the patient's field of vision using augmented reality technology; the information and feedback strategy superimposed by the augmented reality guidance module are combined with the social interaction module to achieve social interaction and experience sharing between patients through an online platform; the social feedback and environmental data obtained by the social interaction module are used by the context perception feedback module to adjust the feedback strategy;

[0035] The blockchain data management module adopts blockchain technology to realize the decentralized management of sports rehabilitation data. The privacy protection algorithm module uses differential privacy and homomorphic encryption algorithms to protect the patient's personal privacy data; the data protected by the privacy protection algorithm module is flexibly adjusted by the dynamic permission control module according to actual needs. The permissions and monitoring results set by the dynamic permission control module allow the anomaly detection and response module to monitor abnormal behaviors in the data transmission and storage process in real time and take timely response measures.

[0036] In the above embodiment, the personalized rehabilitation intelligent planning module uses virtual reality technology to simulate the rehabilitation training environment to provide an immersive training experience by intelligently evaluating the patient's motor ability and health status, monitors the patient's psychological state through emotion recognition technology, and dynamically adjusts the training plan using an adaptive learning algorithm. The intelligent wearable device module uses flexible sensors to achieve high-precision data acquisition, provides continuous power through an energy collection module, integrates multiple sensors for multi-dimensional monitoring, and automatically triggers an early warning or protection mechanism when an abnormality is detected. The intelligent interactive feedback module relies on a voice assistant to provide real-time training guidance, uses augmented reality technology to overlay training information in the patient's field of view, realizes social interaction and experience sharing between patients through an online platform, and adjusts the feedback strategy in combination with the environment and patient context. The data security and privacy protection module uses blockchain technology to decentralize data management, uses differential privacy and homomorphic encryption to protect patient privacy, dynamically adjusts data access rights, and monitors and responds to abnormal behaviors in data transmission and storage in real time. The system provides comprehensive, efficient and safe sports rehabilitation services through the collaborative work of various modules.

[0037] Example 2

[0038] like Figure 1-2 As shown, an intelligent detection and movement rehabilitation system, the multimodal sensor fusion module includes an adaptive sensor configuration module for dynamically adjusting the parameter configuration and perception range of the sensor according to real-time data and environmental changes, an intelligent noise suppression module for automatically identifying and suppressing noise signals in the data using advanced artificial intelligence algorithms, a situational feature extraction module for extracting multimodal data features in combination with the patient's specific situation, a multi-data collaborative processing module for integrating data from multiple sensors for complementary analysis through a multi-source data collaborative processing algorithm, an intelligent motion analysis module for intelligently analyzing the fused multimodal data using a deep learning model to determine complex movement patterns and potential abnormal behaviors, a physiological state intelligent assessment module for intelligently assessing the physiological state using a machine learning algorithm based on multimodal data, and a data privacy protection sharing module for using blockchain and differential privacy technology to ensure the security and privacy protection of multimodal data during sharing and transmission;

[0039] The motion analysis module includes a deep learning analysis module for performing feature extraction and pattern recognition on motion data using a deep learning algorithm and an anomaly detection module for detecting anomalies in motion data based on statistical methods and machine learning algorithms;

[0040] The deep learning analysis module branch includes a motion pattern recognition module for detecting and identifying the current motion state of the user, an environment perception module for extracting obstacles and available objects from the user's current environment, and an environment data analysis module for centrally analyzing and processing the data of obstacles and available objects in the environment;

[0041] The abnormality detection module includes an abnormality determination module for analyzing the impact of abnormal situations on users, a fusion decision module for fusing motion data with environmental data to make comprehensive judgments and decisions, a comprehensive judgment module for comprehensive analysis, and an abnormal data collection module for collecting abnormal data determination results;

[0042] The intelligent noise suppression module suppresses the noise signal in the data, allowing the situational feature extraction module to extract multimodal data features based on clean data combined with specific situations; the adaptive sensor configuration module dynamically adjusts the parameter configuration and perception range of the sensor, allowing the multi-data collaborative processing module to integrate the data of multiple sensors through a collaborative processing algorithm for complementary analysis; the data processed by the multi-data collaborative processing module is intelligently analyzed by the intelligent motion analysis module using a deep learning model to determine complex motion patterns and potential abnormal behaviors; after determining the motion pattern, the intelligent motion analysis module allows the physiological state intelligent assessment module to assess the physiological state based on these motion data and other multimodal data; the assessment data generated by the physiological state intelligent assessment module is shared through the blockchain of the data privacy protection module and differential privacy technology to ensure data security and privacy protection; the deep learning analysis module extracts and identifies motion data features, allowing the anomaly detection module to use these features to detect anomalies in the motion data; the motion pattern recognition module detects and identifies the user's motion state, allowing the environmental perception module to extract obstacle and suspicious object data in the current environment; the environmental data collected by the environmental perception module is centrally processed and analyzed by the environmental data analysis module; the abnormal situation determination module analyzes the impact of abnormal situations on the user, allowing the fusion decision module to fuse the motion data with the environmental data to make a comprehensive judgment and decision; the fusion decision module provides a comprehensive judgment basis for the comprehensive judgment module to further analyze and make a final judgment; the analysis results of the comprehensive judgment module are recorded and stored by the abnormal data collection module.

[0043] In the above embodiment, the adaptive sensing configuration module dynamically adjusts the sensor parameter configuration and perception range according to real-time data and environmental changes to ensure the accuracy of data collection. The intelligent noise suppression module uses artificial intelligence algorithms to automatically identify and suppress noise signals in the data, and provides clean data for the context feature extraction module, which extracts multimodal data features in combination with specific contexts. The multi-data collaborative processing module uses a collaborative processing algorithm to integrate the data of multiple sensors for complementary analysis, and passes the integrated processed data to the intelligent motion analysis module, which uses a deep learning model for intelligent analysis to determine complex motion patterns and potential abnormal behaviors. After determining the motion pattern, the intelligent motion analysis module passes the data to the physiological state intelligent assessment module, which assesses the physiological state based on multimodal data. The assessment results ensure the security and privacy protection of data during sharing and transmission through the blockchain and differential privacy technology of the data privacy protection sharing module. The deep learning analysis module supports the anomaly detection module to detect anomalies in the motion data by extracting and identifying motion data features. The motion pattern recognition module identifies the user's motion state, and the environmental perception module extracts obstacles and available object data in the current environment, which are centrally processed and differentiated by the environmental data analysis module. The abnormal situation determination module analyzes the impact of abnormal situations on users, the fusion decision module fuses motion and environmental data to make comprehensive judgments and decisions, and finally the comprehensive judgment module conducts detailed analysis and records it in the abnormal data collection module.

[0044] Working principle: When the present invention is used, the intelligent evaluation module uses artificial intelligence and big data technology to comprehensively evaluate the patient's motor ability and health status. Then, the virtual reality training module simulates the rehabilitation training environment to provide an immersive training experience, and the data is monitored by the emotion recognition module to monitor the patient's psychological state. The adaptive learning algorithm module dynamically adjusts the training plan according to the patient's rehabilitation progress and feedback to ensure the personalization and adaptability of the rehabilitation plan. This process achieves accurate management and optimization of the patient's rehabilitation process through intelligent evaluation and real-time adjustment.

[0045] In the smart wearable device module, the flexible sensor module uses flexible electronic technology to develop skin-fitting sensors to achieve high-precision motion and physiological data collection. The energy harvesting module provides continuous power for smart wearable devices through motion energy harvesting technology, supporting multi-dimensional monitoring of the multimodal sensor fusion module. The multimodal sensor fusion module comprehensively processes the collected data, and when abnormal motion patterns or physiological indicators are detected, the intelligent protection module automatically triggers an early warning or protection mechanism. The entire process ensures comprehensive monitoring of the patient's motion and physiological status, and protects patient safety through an early warning mechanism.

[0046] In the intelligent interactive feedback module and the data security and privacy protection module, the intelligent voice assistant module provides real-time training guidance through voice recognition and synthesis technology, the augmented reality guidance module superimposes training information in the patient's field of view, the social interaction module realizes interaction and experience sharing between patients through an online platform, and the context-aware feedback module adjusts the feedback strategy according to the environment and patient context. The blockchain data management module uses blockchain technology to achieve decentralized data management, the privacy protection algorithm module uses differential privacy and homomorphic encryption to protect patient privacy, the dynamic permission control module flexibly adjusts data access rights, and the anomaly detection and response module monitors and responds to abnormal behaviors in data transmission and storage in real time to ensure data security and privacy protection. The system achieves efficient and safe sports rehabilitation management through intelligent interaction and strict data security measures.

[0047] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. An intelligent detection and exercise rehabilitation system, characterized in that: It includes a personalized rehabilitation intelligent planning module for developing personalized rehabilitation plans for each patient using artificial intelligence and big data technologies, a smart wearable device module for achieving high-precision data collection and long-term monitoring through advanced flexible sensors and energy harvesting technologies, a smart interactive feedback module for providing real-time training guidance and feedback based on voice assistants and augmented reality technologies, and a data security and privacy protection module for ensuring the security and privacy of rehabilitation data using technologies such as blockchain and differential privacy; The personalized rehabilitation intelligent planning module includes an intelligent assessment module for comprehensively evaluating the patient's motor ability and health status using artificial intelligence and big data technologies, a virtual reality training module for simulating a rehabilitation training environment through virtual reality technology to provide an immersive training experience, an emotion recognition module for monitoring the patient's psychological state through emotion recognition technologies such as facial expressions and voice intonation to timely adjust the difficulty and method of rehabilitation training, and an adaptive learning algorithm module for dynamically adjusting the training plan and goals according to the patient's rehabilitation progress and feedback using an adaptive learning algorithm; The smart wearable device module includes a flexible sensor module for developing flexible sensors that fit the skin using flexible electronic technology to achieve high-precision motion and physiological data acquisition, an energy collection module for providing continuous electrical energy for smart wearable devices through motion energy collection technology, a multimodal sensor fusion module for integrating multiple sensors to achieve multi-dimensional monitoring of patient motion and physiological status, and an intelligent protection module for automatically triggering an early warning or protection mechanism when abnormal motion patterns or physiological indicators are detected.

2. The intelligent detection and exercise rehabilitation system according to claim 1, characterized in that: The intelligent interactive feedback module includes an intelligent voice assistant module for providing real-time training guidance and feedback through voice recognition and synthesis technology, an augmented reality guidance module for superimposing training guidance information in the patient's field of view using augmented reality technology, a social interaction module for achieving social interaction and experience sharing between patients through an online platform, and a context-aware feedback module for adjusting feedback strategies in combination with the environment and patient context; The data security and privacy protection module includes a blockchain data management module for using blockchain technology to achieve decentralized management of sports rehabilitation data, a privacy protection algorithm module for using advanced algorithms such as differential privacy and homomorphic encryption to protect patients' personal privacy data, a dynamic permission control module for flexibly adjusting data access rights according to actual needs, and an anomaly detection and response module for real-time monitoring of abnormal behaviors in data transmission and storage processes and taking timely response measures.

3. The intelligent detection and exercise rehabilitation system according to claim 1, characterized in that: The multimodal sensing fusion module includes an adaptive sensing configuration module for dynamically adjusting the parameter configuration and sensing range of the sensor according to real-time data and environmental changes, an intelligent noise suppression module for automatically identifying and suppressing noise signals in the data using advanced artificial intelligence algorithms, a situational feature extraction module for extracting multimodal data features in combination with the patient's specific situation, a multi-data collaborative processing module for integrating data from multiple sensors for complementary analysis through a multi-source data collaborative processing algorithm, an intelligent motion analysis module for intelligently analyzing the fused multimodal data using a deep learning model to determine complex motion patterns and potential abnormal behaviors, a physiological state intelligent assessment module for intelligently assessing physiological states using a machine learning algorithm based on multimodal data, and a data privacy protection sharing module for using blockchain and differential privacy technology to ensure the security and privacy protection of multimodal data during sharing and transmission; The motion analysis module includes a deep learning analysis module for performing feature extraction and pattern recognition on motion data using a deep learning algorithm and an anomaly detection module for detecting anomalies in motion data based on statistical methods and machine learning algorithms; The deep learning analysis module branch includes a motion pattern recognition module for detecting and identifying the current motion state of the user, an environment perception module for extracting obstacles and available objects from the user's current environment, and an environment data analysis module for centrally analyzing and processing the data of obstacles and available objects in the environment; The abnormality detection module includes an abnormality determination module for analyzing the impact of abnormal situations on users, a fusion decision module for fusing motion data with environmental data to make comprehensive judgments and decisions, a comprehensive judgment module for comprehensive analysis, and an abnormal data collection module for collecting abnormal data determination results.

4. The intelligent detection and exercise rehabilitation system according to claim 3, characterized in that: The intelligent noise suppression module suppresses the noise signal in the data, allowing the situational feature extraction module to extract multimodal data features based on the clean data combined with the specific situation; the adaptive sensor configuration module dynamically adjusts the parameter configuration and perception range of the sensor, allowing the multi-data collaborative processing module to integrate the data of multiple sensors through the collaborative processing algorithm for complementary analysis; the data processed by the multi-data collaborative processing module is intelligently analyzed by the intelligent motion analysis module using a deep learning model to determine complex motion patterns and potential abnormal behaviors; after determining the motion pattern, the intelligent motion analysis module allows the physiological state intelligent assessment module to assess the physiological state based on these motion data and other multimodal data; The assessment data generated by the physiological state intelligent assessment module ensures data security and privacy protection through the blockchain and differential privacy technology of the data privacy protection sharing module; the deep learning analysis module extracts and identifies motion data features, allowing the anomaly detection module to use these features to detect anomalies in the motion data; the motion pattern recognition module detects and identifies the user's motion state, allowing the environmental perception module to extract obstacles and available object data in the current environment; the environmental data collected by the environmental perception module is centrally processed and analyzed by the environmental data analysis module; the abnormal situation determination module analyzes the impact of abnormal situations on the user, allowing the fusion decision module to fuse the motion data with the environmental data to make a comprehensive judgment and decision; the fusion decision module provides a comprehensive judgment basis for the comprehensive judgment module to further analyze and make a final judgment; the analysis results of the comprehensive judgment module are recorded and stored by the abnormal data collection module.

5. The intelligent detection and exercise rehabilitation system according to claim 2, characterized in that: The intelligent assessment module comprehensively evaluates the patient's motor ability and health status by using artificial intelligence and big data technology, allowing the virtual reality training module to simulate the rehabilitation training environment to provide an immersive training experience; the training experience data provided by the virtual reality training module is monitored by the emotion recognition module using facial expressions, voice intonation and other emotion recognition technologies to monitor the patient's psychological state; the psychological state data monitored by the emotion recognition module allows the adaptive learning algorithm module to dynamically adjust the training plan and goals according to the patient's rehabilitation progress and feedback.

6. The intelligent detection and exercise rehabilitation system according to claim 2, characterized in that: The flexible sensor module uses flexible electronic technology to develop a flexible sensor that fits the skin to achieve high-precision motion and physiological data collection, allowing the energy harvesting module to provide continuous power for the smart wearable device through motion energy harvesting technology; The electric energy provided by the energy collection module supports the multimodal sensor fusion module to integrate multiple sensors to realize multi-dimensional monitoring of the patient's movement and physiological state; the movement and physiological data monitored by the multimodal sensor fusion module are used by the intelligent protection module to automatically trigger an early warning or protection mechanism when abnormal movement patterns or physiological indicators are detected.

7. The intelligent detection and exercise rehabilitation system according to claim 2, characterized in that: The intelligent voice assistant module provides real-time training guidance and feedback through voice recognition and synthesis technology, and the information is superimposed by the augmented reality guidance module in the patient's field of view using augmented reality technology; the information and feedback strategy superimposed by the augmented reality guidance module are combined with the social interaction module to realize social interaction and experience sharing between patients through an online platform; the social feedback and environmental data obtained by the social interaction module are used by the contextual perception feedback module to adjust the feedback strategy.

8. The intelligent detection and exercise rehabilitation system according to claim 2, characterized in that: The blockchain data management module adopts blockchain technology to realize the decentralized management of sports rehabilitation data. The privacy protection algorithm module uses differential privacy and homomorphic encryption algorithms to protect the patient's personal privacy data; the data protected by the privacy protection algorithm module is flexibly adjusted by the dynamic permission control module according to actual needs. The permissions and monitoring results set by the dynamic permission control module allow the anomaly detection and response module to monitor abnormal behaviors in the data transmission and storage process in real time and take timely response measures.

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