Spike shape analysis for the surface and needle electromyographic interference pattern. (July 2017)

• Record Type: Journal Article
• Authors: Green, Lara A.; Christie, Anita; Gabriel, David A.
• Is Part Of: Biomedical signal processing and control. Volume 36(2017)
• Page Start: 1
• Page End: 10
• Publication Date: 2017-07
• Subjects: ANOVA analysis of variance -- EMG electromyography -- MDF median power frequency -- MNPPS mean number of peaks per spike -- MPF mean power frequency -- MSA mean spike amplitude -- MSD mean spike duration -- MSF mean spike frequency -- MSS mean spike slope -- MVC maximal voluntary contraction -- RMS root mean square -- sEMG surface electromyography; Biceps brachii -- Isometric force -- Motor unit -- Elbow flexion -- Muscle activity -- Electromyography; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2017.03.006
• Languages: English
• ISSNs: 1746-8094

Abstract

Graphical abstract: Highlights: Surface and indwelling EMG spike shape measures of the biceps brachii change in parallel up to 50% of maximal force. Electrode-source distance and spike threshold affect the pattern of change in EMG for frequency but not amplitude measures. Surface EMG spike shape analysis can track changes by recruitment and rate-coding up to 50% of maximal force. Abstract: Introduction: The ability of surface and needle electromyographic (EMG) spike shape measures to match changes in motor unit recruitment, firing rate, and synchronization during force gradation, were compared. The purpose of the study was to determine the force level at which the surface EMG spike shape measures no longer parallel their indwelling analogues. Secondarily, the impact of the noise rejection criterion on the sensitivity of the spike shape measures was examined. Methods: Maximal isometric elbow flexion ramp contractions were performed while recording surface and needle EMG from the biceps brachii. Spike shape measures were calculated in 500 ms epochs over the duration of the ramp contraction. The spike threshold for needle EMG spike detection was varied to examine the effect of the algorithm's selectivity. The pattern of change across force levels between surface and needle EMG measures was compared. Results: Spike detection resulted in the same pattern of change for both surface and needle amplitude measures over the gradation of force. Frequency measures and mean number of peaks per spike (MNPPS) were affected by electrode-source distance and spike threshold. Surface and needle frequency measures changed in parallel to 50% MVC while the MNPPS plateaued at 50–55% MVC. Discussion: Spike shape analysis of surface EMG can track changes in the interference pattern produced by recruitment and rate-coding up to 50% MVC.