Development of a High-SNR Stochastic sEMG Processor in a Multiple Muscle Elbow Joint
In the robotics and rehabilitation engineering fields, surface electromyography (sEMG) signals have been widely studied to estimate muscle activation and utilized as control inputs for robotic devices because of their advantageous noninvasiveness. However, the stochastic property of sEMG results in...
Main Authors: | Handdeut Chang, Seulki Kyeong, Youngjin Na, Yeongjin Kim, Jung Kim |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2023-01-01
|
Series: | IEEE Transactions on Neural Systems and Rehabilitation Engineering |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10146313/ |
Similar Items
-
Optimal Elbow Angle for Extracting sEMG Signals During Fatiguing Dynamic Contraction
by: Mohamed R. Al-Mulla, et al.
Published: (2015-09-01) -
Research on the motion characteristic of elbow joint angle based on the sEMG of single muscle
by: Wei YuWei, et al.
Published: (2016-12-01) -
Mechanical Simulation of the Extension and Flexion of the Elbow Joint in Rehabilitation
by: Iman Vahdat, et al.
Published: (2013-01-01) -
Prediction of Above-elbow Motions in Amputees, based on Electromyographic(EMG) Signals, Using Nonlinear Autoregressive Exogenous (NARX) Model
by: Ali Akbar Akbari, et al.
Published: (2014-08-01) -
Evaluation of Spasticity Variations at the Elbow Joint of CVA Patients According to the Biomechanical Indices
by: Nima Soleimanzadeh-Ardabili, et al.
Published: (2013-10-01)