Feature-Based Evaluation of a Wearable Surface EMG Sensor against Laboratory Standard EMG during Force-Varying and Fatiguing Contractions

Emer P. Doheny*, Cathy Goulding, Matthew W. Flood, Lara McManus, Madeleine M. Lowery

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

8 Citations (Scopus)

Abstract

Recent advances in wearable sensors enable recording of electromyography (EMG) outside the laboratory for extended periods of time. However, the properties of wearable EMG systems designed for long-term recording may differ from those of laboratory-standard systems, potentially impacting data. This study evaluated EMG features derived from signals recorded using a wearable system (BioStampRC, MC10 Inc.) against a reference laboratory system (Bagnoli, Delsys Inc.). Surface EMG data from the biceps brachii were recorded simultaneously using both systems during isometric elbow flexion, between 10% and 80% of maximum voluntary contraction (MVC), and during sustained submaximal fatiguing contraction, in twelve subjects. Linear and nonlinear EMG temporal and spectral features were then compared across both systems. No effect of recording system was detected on EMG onset/offset times, or on the relationship between force and EMG root mean squared amplitude. However, the relationships between force and median frequency, percentage determinism and multiscale entropy differed between systems. Baseline noise was also greater for the BioStampRC. Lower median frequencies were observed for the wearable system, likely due to the larger interelectrode distance, however, the relative change in EMG amplitude and median frequency during the fatiguing contraction was similar for both. Percentage determinism increased and multiscale entropy decreased during the fatiguing contraction for both systems, with higher and lower values respectively for the wearable system. Results indicate that the BiostampRC is appropriate for EMG onset/offset and amplitude estimation. However, caution is advised when comparing across systems as spectral and nonlinear features may differ due to electrode design differences.

Original languageEnglish
Article number8897580
Pages (from-to)2757-2765
Number of pages9
JournalIEEE Sensors Journal
Volume20
Issue number5
DOIs
Publication statusPublished - 1 Mar 2020
Externally publishedYes

Keywords

  • determinism
  • EMG validation
  • median frequency
  • multiscale entropy
  • wearable sensors

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