학술논문
A Novel Torque-Controlled Hand Exoskeleton to Decode Hand Movements Combining Semg and Fingers Kinematics: A Feasibility Study
Document Type
Periodical
Author
Source
IEEE Robotics and Automation Letters IEEE Robot. Autom. Lett. Robotics and Automation Letters, IEEE. 7(1):239-246 Jan, 2022
Subject
Language
ISSN
2377-3766
2377-3774
2377-3774
Abstract
This study presents a novel torque-controlled hand exoskeleton, named HandeXos-gamma, which uses a series-elastic actuator (SEA)-based architecture to allow a compliant actuation of the hand joints, and an intention decoding algorithm that combines surface electromyography (sEMG) signals with kinematic information from the exoskeleton's encoders. The algorithm was developed offline using data acquired from healthy subjects who performed two grasping movements (lateral and power grasp) under different operating conditions while wearing the exoskeleton. Performance was evaluated for three variants of the algorithm: one using sEMG signals only, another using kinematic data only, and the last combining sEMG and kinematic data. Results indicated that the combination of the two modalities conferred greater algorithm performance than sEMG alone, thus supporting a new paradigm for adaptive robotic hand rehabilitation.