Back to Search Start Over

Muscle Synergy during Wrist Movements Based on Non-Negative Tucker Decomposition.

Authors :
Chen, Xiaoling
Feng, Yange
Chang, Qingya
Yu, Jinxu
Chen, Jie
Xie, Ping
Source :
Sensors (14248220). May2024, Vol. 24 Issue 10, p3225. 15p.
Publication Year :
2024

Abstract

Modular control of the muscle, which is called muscle synergy, simplifies control of the movement by the central nervous system. The purpose of this study was to explore the synergy in both the frequency and movement domains based on the non-negative Tucker decomposition (NTD) method. Surface electromyography (sEMG) data of 8 upper limb muscles in 10 healthy subjects under wrist flexion (WF) and wrist extension (WE) were recorded. NTD was selected for exploring the multi-domain muscle synergy from the sEMG data. The results showed two synergistic flexor pairs, Palmaris longus–Flexor Digitorum Superficialis (PL-FDS) and Extensor Carpi Radialis–Flexor Carpi Radialis (ECR-FCR), in the WF stage. Their spectral components are mainly in the respective bands 0–20 Hz and 25–50 Hz. And the spectral components of two extensor pairs, Extensor Digitorum–Extensor Carpi Ulnar (ED-ECU) and Extensor Carpi Radialis–Brachioradialis (ECR-B), are mainly in the respective bands 0–20 Hz and 7–45 Hz in the WE stage. Additionally, further analysis showed that the Biceps Brachii (BB) muscle was a shared muscle synergy module of the WE and WF stage, while the flexor muscles FCR, PL and FDS were the specific synergy modules of the WF stage, and the extensor muscles ED, ECU, ECR and B were the specific synergy modules of the WE stage. This study showed that NTD is a meaningful method to explore the multi-domain synergistic characteristics of multi-channel sEMG signals. The results can help us to better understand the frequency features of muscle synergy and shared and specific synergies, and expand the study perspective related to motor control in the nervous system. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14248220
Volume :
24
Issue :
10
Database :
Academic Search Index
Journal :
Sensors (14248220)
Publication Type :
Academic Journal
Accession number :
177490393
Full Text :
https://doi.org/10.3390/s24103225