Developing a Balance Rehabilitation System for Older Adults, Based on IMU and AI: Personalized Training and Preventive Strategies

The development of a balance rehabilitation system for older adults, integrating Inertial Measurement Unit (IMU) sensing and Artificial Intelligence (AI). The key technical components and methodology are as follows: Technological Foundation: IMU sensors will be used to monitor and assess human movement and posture. These sensors detect motion through accelerometers, gyroscopes, and magnetometers, allowing for precise gait analysis. AI and Generative Adversarial Networks (GAN) will process the data to customize training regimens based on the individual's physiological and movement characteristics. A Vicon 3D motion capture system will be used in conjunction with IMUs for validating and collecting data during the development phase. Research Phases: Year 1: Developing an AI-based gait training system using IMUs. This involves creating a gait database and balance training protocols using bilateral and unilateral movements. Year 2: Optimizing the training system using AI and GAN to diversify the data and improve training efficacy. Year 3: Clinical validation of the system by comparing results between participants undergoing IMU-based training versus standard physical exercises. Training Protocols: Exergame Environment: Participants engage in exercises within a virtual environment, which mimics real-world conditions but includes artificial elements to challenge balance and coordination. Balance Training: Skateboard-based training focuses on unilateral leg movements, monitored by IMUs to provide feedback and adjust difficulty based on performance. Data Analysis: Gait Data: AI and GAN are used to generate personalized gait profiles, which will feed into the training system. Statistical Analysis: Various statistical tests (e.g., ANOVA) will assess the effectiveness of the system compared to conventional rehabilitation methods. This system aims to provide older adults with personalized rehabilitation, reducing fall risk and enhancing their quality of life.