• Julien Frère.
• University of Lorraine, Laboratory "Development, Adaption and Disability" (EA 3450), Faculty of Sports Sciences, 30 rue du Jardin Botanique, CS 30156, F-54603 Villers-lès-Nancy, France. Electronic address: julien.frere@univ-lorraine.fr.
• Neuroscience. 2017 Jul 4; 355: 22-35.

AbstractIt is still unclear if muscle synergies reflect neural strategies or mirror the underlying mechanical constraints. Therefore, this study aimed to verify the consistency of muscle groupings between the synergies based on the linear envelope (LE) of muscle activities and those incorporating the time-frequency (TF) features of the electromyographic (EMG) signals. Twelve healthy participants performed six 20-m walking trials at a comfort and fast self-selected speed, while the activity of eleven lower limb muscles was recorded by means of surface EMG. Wavelet-transformed EMG was used to obtain the TF pattern and muscle synergies were extracted by non-negative matrix factorization. When five muscle synergies were extracted, both methods defined similar muscle groupings whatever the walking speed. When accounting the reconstruction level of the initial dataset, a new TF synergy emerged. This new synergy dissociated the activity of the rectus femoris from those of the vastii muscles (synergy #1) and from the one of the tensor fascia latae (synergy #5). Overall, extracting TF muscle synergies supports the neural origin of muscle synergies and provides an opportunity to distinguish between prescriptive and descriptive muscle synergies.Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

5 keywords...

hide…