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Effect of velocity and acceleration in joint angle estimation for an EMG-Based upper-limb exoskeleton control

Tang, Zhichuan; Yu, Hongnian; Yang, Hongchun; Zhang, Lekai; Zhang, Lufang


Zhichuan Tang

Hongchun Yang

Lekai Zhang

Lufang Zhang


Most studies on estimating user's joint angles to control upper-limb exoskeleton have focused on using surface electromyogram (sEMG) signals. However, the variations in limb velocity and acceleration can affect the sEMG data and decrease the angle estimation performance in the practical use of the exoskeleton. This paper demonstrated that the variations in elbow angular velocity (EAV) and elbow angular acceleration (EAA) associated with normal use led to a large effect on the elbow joint angle estimation. To minimize this effect, we proposed two methods: (1) collecting sEMG data of multiple EAVs and EAAs as training data and (2) measuring the values of EAV and EAA with a gyroscope. A self-developed upper-limb exoskeleton with pneumatic muscles was used in the online control phase to verify our methods' effectiveness. The predicted elbow angle from the sEMG-angle models which were trained in the offline estimation phase was transferred to control signal of the pneumatic muscles to actuate the exoskeleton to move to the same angle. In the offline estimation phase, the average root mean square error (RMSE) between predicted elbow angle and actual elbow angle was reduced from 22.54° to 10.01° (using method one) and to 6.45° (using method two), respectively; in the online control phase, method two achieved a best control performance (average RMSE = 6.87°). The results showed that using multi-sensor fusion (sEMG sensors and gyroscope) achieved a better estimation performance than using only sEMG sensor, which was helpful to eliminate the velocity and acceleration effect in real-time joint angle estimation for upper-limb exoskeleton control.

Journal Article Type Article
Acceptance Date Dec 16, 2021
Online Publication Date Dec 18, 2021
Publication Date 2022-02
Deposit Date Mar 25, 2022
Journal Computers in Biology and Medicine
Print ISSN 0010-4825
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 141
Article Number 105156
Keywords Exoskeleton, Joint angle, sEMG, Velocity, Acceleration
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