Decomposition of multi-channel intramuscular EMG signals by cyclostationary-based blind source separation
File(s)
Accepted version
Author(s)
Roussel, J
Ravier, P
Haritopoulos, M
Farina, D
Buttelli, O
Type
Journal Article
Abstract
We propose a novel decomposition method for electromyographic (EMG) signals based on blind source separation. Using the cyclostationary properties of motor unit action potential trains (MUAPt), it is shown that MUAPt can be decomposed by joint diagonalization of the cyclic spatial correlation matrix of the observations. After modeling of the source signals, we provide the proof of orthogonality of the sources and of their delayed versions in a cyclostationary context. We tested the proposed method on simulated signals and showed that it can decompose up to 6 sources with a probability of correct detection and classification >95%, using only 8 recording sites. Moreover, we tested the method on experimental multi-channel signals recorded with thin-film intramuscular electrodes, with a total of 32 recording sites. The rate of agreement of the decomposed MUAPt with those obtained by an expert using a validated tool for decomposition was >93%.
Date Issued
2017-05-03
Date Acceptance
2017-04-30
Citation
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2017, 25 (11), pp.2035-2045
ISSN
1558-0210
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Start Page
2035
End Page
2045
Journal / Book Title
IEEE Transactions on Neural Systems and Rehabilitation Engineering
Volume
25
Issue
11
Copyright Statement
© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
Subjects
0903 Biomedical Engineering
0906 Electrical And Electronic Engineering
Biomedical Engineering
Publication Status
Published