Less is more: uncompensated gravity torques for intuitive EMG-based assistance with a robotic exoskeleton
Despite extensive investigation on the use of electromyographic (EMG) activity to control active exoskeletons over the past decade, designing intuitive assistive controllers that seamlessly integrate with natural human motor control have yet to be realized. While existing EMG-based controllers often achieve substantial reduction in muscle effort, they frequently incur increased cognitive and attentional load for the user, thereby compromising the overall efficacy of the assistance. Here we introduce a novel EMG-based assistive controller founded upon neuroscience principles, specifically the observation that humans naturally exploit gravity torque to facilitate movement control. Therefore, deviating from conventional compensation strategies, our approach purposely leaves a fraction of the predicted human gravity torque uncompensated so that users can still take advantage of gravity as they would without assistance. Through a load-carrying arm movement task, we show that enabling gravity exploitation improves traditional EMGbased assistance by achieving a significant reduction in muscle effort, while concurrently yielding superior kinematic performance (i.e., faster, smoother movements) and enhanced subjective user experience. These findings demonstrate that integrating principles from neural motor control into assistive controllers allows to implement a favorable tradeoff between muscle effort reduction and functional usability.