Background
Patients with stroke or lower-limb impairments often suffer from abnormal gait, poor balance, and difficulty walking. Conventional rehabilitation relies heavily on therapists, while existing devices are often limited to fixed environments or single-function training. They are insufficient for simulating real-life walking tasks such as overground walking, turning, and obstacle avoidance. Therefore, this research aims to develop an integrated intelligent gait rehabilitation system to improve training safety, gait naturalness, and clinical applicability.
Research Objectives
Develop a multifunctional follow-up walking rehabilitation system that integrates a lower-limb exoskeleton, variable dynamic body-weight support, motion intention recognition, gait projection guidance, and safety control technologies. The system enables users to perform natural overground gait training while adaptively adjusting assistive forces and training modes according to the user’s condition.
Methods
The research will establish a follow-up mobile platform integrated with a lower-limb exoskeleton and a variable dynamic body-weight support system. IMUs, force sensors, and control algorithms will be used for gait phase detection and bilateral support-force adjustment. A suspension-based motion intention recognition method will identify the user’s movement direction, while gait projection will provide personalized gait training.
Innovation
The innovation of this research lies in integrating variable dynamic body-weight support, non-wearable physiological-sensor-free motion intention recognition, gait projection guidance, and intelligent safety control into a single rehabilitation platform. The system supports more natural overground gait training while reducing dependence on fixed training environments, therapist assistance, and wearable physiological sensors.
Expected Outcomes
The expected outcome is an intelligent rehabilitation system capable of overground follow-up walking, dynamic body-weight support, exoskeleton assistance, gait guidance, and safety control. The system is expected to improve rehabilitation safety, gait naturalness, and personalization, while serving as a technical foundation for future clinical validation, smart assistive device development, and rehabilitation robot commercialization.