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Lower Limb Exoskeleton With Multimodal Physiological Signal Sensing and Hybrid Drive Mechanism

CSEF · 2026 Applied Mechanics (Senior Division)

Chris Zheng

Overview

This project addresses the high incidence of lower back and lower limb injuries among firefighters and workers during heavy-load rescue operations. In this paper, a novel lower-limb exoskeleton system is designed and developed that integrates multimodal physiological signal sensing (EEG for fatigue detection, EMG for motion intention recognition) with a hybrid drive mechanism (motor + spring for energy recovery). A functional prototype was built and tested. Key results demonstrate a motion intention recognition accuracy of 92%, and a 42% increase in battery life achieved through the implementation of fatigue-adaptive control, compared to a fixed-output mode. The system shows significant potential to enhance operator endurance and safety in demanding rescue scenarios.

Competition history

  • CSEF 2026 Applied Mechanics (Senior Division) · Entry S-02-24

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