Wearable Body Sensors Integrated into a Virtual Reality Environment - A Modality for Automating the Rehabilitation of the Motor Control System

Abstract

Amidst the rising incidences of stroke and spinal cord injuries, this study introduces a Virtual Reality (VR) system integrated with wearable sensor-based motion capture technology to enhance rehabilitation and assessment of upper limb impairments. The proposed motion capture system utilizes Inertial Measurement Units (IMUs) engineered in a modular and portable fashion to best fit different rehabilitation needs of the motor control system. The wearable sensor system consists of 15 modules capable of capturing the entire human body motion, along with a pair of hand gloves including 11 miniature sensors measuring hand motion. The sensor accuracy test demonstrates a Root Mean Square Error below 1.78 degrees compared to measurements collected by a commercial robotic arm. Incorporating detailed data of human joints' motion collected by the array of wearable sensors, the proposed VR system provides additional tools for assessments of the motor control system function, including range of motion, reachable workspace, motor learning, along with rehabilitative intervention games. The developed system provides a foundation for an AI-driven autonomous rehabilitation system, integrating automated clinical assessments with quantitative tools and adaptive difficulty algorithms for personalized interventions, applicable in both clinical-based and home-based settings.