Rectification of EMG in low force contractions improves detection of motor unit coherence in the beta-frequency band

Ward, Nicholas J, Farmer, Simon F, Berthouze, Luc and Halliday, David M (2013) Rectification of EMG in low force contractions improves detection of motor unit coherence in the beta-frequency band. Journal of Neurophysiology, 110 (8). pp. 1744-1750. ISSN 0022-3077

[img] PDF - Published Version
Restricted to SRO admin only

Download (148kB)

Abstract

Rectification of surface EMG before spectral analysis is a well-established preprocessing method used in the detection of motor unit firing patterns. A number of recent studies have called into question the need for rectification before spectral analysis, pointing out that there is no supporting experimental evidence to justify rectification. We present an analysis of 190 records from 13 subjects consisting of simultaneous recordings of paired single motor units and surface EMG from the extensor digitorum longus muscle during middle finger extension against gravity (unloaded condition) and against gravity plus inertial loading (loaded condition). We directly examine the hypothesis that rectified surface EMG is a better predictor of the frequency components of motor unit synchronization than the unrectified (or raw) EMG in the beta-frequency band (15-32 Hz). We use multivariate analysis and estimate the partial coherence between the paired single units using both rectified and unrectified surface EMG as a predictor. We use a residual partial correlation measure to quantify the difference between raw and rectified EMG as predictor and analyze unloaded and loaded conditions separately. The residual correlation for the unloaded condition is 22% with raw EMG and 3.5% with rectified EMG and for the loaded condition it is 5.2% with raw EMG and 1.4% with rectified EMG. We interpret these results as strong supporting experimental evidence in favor of using the preprocessing step of surface EMG rectification before spectral analysis.

Item Type: Article
Schools and Departments: School of Engineering and Informatics > Informatics
Subjects: Q Science > QP Physiology > QP0351 Neurophysiology and neuropsychology
Depositing User: Luc Berthouze
Date Deposited: 06 Nov 2013 08:25
Last Modified: 13 Mar 2017 10:56
URI: http://sro.sussex.ac.uk/id/eprint/46713

View download statistics for this item

📧 Request an update