This technology features a gait assistance robot where the upper and lower leg units are connected by a knee joint unit, and the footplate is connected via an ankle joint unit. It utilizes intent-sensing sensors installed on the lower leg unit to instantly detect the wearer's gait intent based on muscle movement.
Existing gait assistance devices have struggled to accurately and quickly identify a user's gait intent. Furthermore, they often suffer from high noise levels, significant power consumption, and joint stiffness, making them ineffective for supporting patients in the early stages of rehabilitation.
This technology proposes a method that provides immediate assistance by combining intent-sensing sensors, which directly detect muscle movement, with a non-powered propulsion module. It can be applied to the rehabilitation of patients with central nervous system disorders, such as stroke, supporting natural gait tailored to the patient's intent while minimizing noise and power consumption.
This invention was developed with support from the Ministry of Trade, Industry and Energy for the development of a machine learning-based lower limb rehabilitation robot system customized for stroke and Parkinson's patients.
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