https://doi.org/10.4081/ejtm.2016.6064
0
0
0
0
Smart Citations
0
0
0
0
Citing PublicationsSupportingMentioningContrasting
View Citations

See how this article has been cited at scite.ai

scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.

A hybrid functional electrical stimulation for real-time estimation of joint torque and closed-loop control of muscle activation

Authors

Zhan Li
INRIA-LIRMM, University of Montpellier, Montpellier, France; University of Electronic Science and Technology of China, Chengdu, China.
David Guiraud
INRIA-LIRMM, University of Montpellier, Montpellier, France.
David Andreu
INRIA-LIRMM, University of Montpellier, Montpellier, France.
Charles Fattal
Rehabilitation Center, Montpellier; COS DIVIO, Dijon, France.
Anthony Gelis
PROPARA Rehabilitation Center, Montpellier, France.
Mitsuhiro Hayashibe
hayashibe@lirmm.fr
INRIA-LIRMM, University of Montpellier, Montpellier, France.
As a neuroprosthetic technique, functional electrical stimulation (FES) can restore lost motor performance of impaired patients. Through delivering electrical pulses to target muscles, the joint movement can be eventually elicited. This work presents a real-time FES system which is able to deal with two neuroprosthetic missions: one is estimating FES-induced joint torque with evoked electromyograph (eEMG), and the other is artificially controlling muscle activation with such eEMG feedback. The clinical experiment results on spinal cord injured (SCI) patients and healthy subjects show promising performance of the proposed FES system.

Dimensions

Altmetric

PlumX Metrics

Plum Print visual indicator of research metrics
  • Citations
    • Citation Indexes: 5
  • Captures
    • Readers: 27
see details

Downloads

Citations

Crossref
5
Scopus
0
Google Scholar
Europe PMC
2
Smriti Bala, Venugopalan Y. Vishnu, Deepak Joshi (2023)
Muscle Synergy-Based Functional Electrical Stimulation Reduces Muscular Fatigue in Post-Stroke Patients: A Systematic Comparison. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 31, 2858.
10.1109/TNSRE.2023.3290293
Xiaoling Chen, Yuntao Jiao, Dong Zhang, Ying Wang, Xinyu Wang, Yuqi Zang, Zhenhu Liang, Ping Xie (2023)
An Adaptive Spatial Filtering Method for Multi-Channel EMG Artifact Removal During Functional Electrical Stimulation With Time-Variant Parameters. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 31, 3597.
10.1109/TNSRE.2023.3311819
Layal Chaikho, Elizabeth Clark, Maxime Raison (2022)
Transcutaneous Functional Electrical Stimulation Controlled by a System of Sensors for the Lower Limbs: A Systematic Review. Sensors, 22(24), 9812.
10.3390/s22249812
Jannatul Naeem, Nur Azah Hamzaid, Amelia Wong Azman, Manfred Bijak (2020)
Electrical stimulator with mechanomyography-based real-time monitoring, muscle fatigue detection, and safety shut-off: a pilot study. Biomedical Engineering / Biomedizinische Technik , 65(4), 461.
10.1515/bmt-2019-0191
Claudio Pizzolato, David J. Saxby, Dinesh Palipana, Laura E. Diamond, Rod S. Barrett, Yang D. Teng, David G. Lloyd (2019)
Neuromusculoskeletal Modeling-Based Prostheses for Recovery After Spinal Cord Injury. Frontiers in Neurorobotics, 13,
10.3389/fnbot.2019.00097

How to Cite

Li, Z., Guiraud, D., Andreu, D., Fattal, C., Gelis, A., & Hayashibe, M. (2016). A hybrid functional electrical stimulation for real-time estimation of joint torque and closed-loop control of muscle activation. European Journal of Translational Myology, 26(3). https://doi.org/10.4081/ejtm.2016.6064

PAGEPress has chosen to apply the Creative Commons Attribution NonCommercial 4.0 International License (CC BY-NC 4.0) to all manuscripts to be published.