Intelligent exoskeletons controlled via wearable bioelectronics

This project sought to introduce an intelligent upper-limb exoskeleton combined with wearable electronics that utilizes deep learning to predict human intention for strength augmentation. The embedded soft wearable sensors provide sensory feedback by collecting real-time muscle activities, which are simultaneously computed to determine the user’s intended movement.

Cloud-based deep learning predicts joint motions with an average accuracy of 96.2% at a 500–550 ms response rate. An array of soft pneumatics assists the intended movements. The intent-driven exoskeleton can reduce human muscle activities by 3.7 times on average compared to the unassisted exoskeleton.

Relevant Papers

Intelligent upper-limb exoskeleton integrated with soft bioelectronics and deep learning for intention-driven augmentation

npj Flexible Electronics (2024)

(pdf)

Soft wearable flexible bioelectronics integrated with an ankle-foot exoskeleton for estimation of metabolic costs and physical effort

npj Flexible Electronics (2023)

(pdf)