Movement assistance at home needs to respond to changing activities and individual needs. RevalExo co-designs a home-based lower-limb exoskeleton with users and clinicians. Our research focuses on AI-based assessment and intelligent adaptive control, combining movement, physiological demand and environmental context to anticipate walking activities and tailor assistance.
The RevalExo benchmark supports locomotion-mode learning across older adults and clinical cohorts. HERMES connects synchronized multimodal sensing with real-time inference and closed-loop assistance. A healthy-participant feasibility pilot explored assistance informed by locomotion intent and fatigue, with wearer and researcher adjustment or override.