Analysis of surface electromyography of patients with low back pain based on different movement patterns

Fang Zhou, Huihui Li, Gaojun Song, Wenjing Du, Fei Peng, Lei Wang

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

The aim of this study was to analyze Surface Electromyography (sEMG) of low back muscles of low back pain (LBP) patients when they performed different movements. We recruited eighteen female LBP patients and eighteen healthy female subjects. They performed forward and backward trunk bending with the maximum voluntary movement, while sEMG data were collected from the multifidus, external oblique and transverse abdominal muscles. We used root mean square (RMS) of sEMG signals and the coefficient of variation (CV) of RMS sEMG signals as a base for analysis. We found significant differences between the two groups in RMS sEMG signals and the CV feature. For all explored muscles, the mean RMS EMG values of the LBP group were lower than those of the healthy group. The CV feature of the LBP group were higher than those of the healthy group for forward bending and lower for backward bending. The reduced values in LBP patients indicate that the activity levels of all explored muscles in LBP patients were lower than those in the healthy group. The result of this study suggested that RMS sEMG signals captured from the low back muscles, and the corresponding CV feature could serve as a base for quantitative assessment of LBP condition. Also, the CV feature can be used to distinguish LBP group and healthy group.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Information and Automation, IEEE ICIA 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1154-1158
Number of pages5
ISBN (Electronic)9781509041022
DOIs
Publication statusPublished - 24 Jan 2017
Externally publishedYes
Event2016 IEEE International Conference on Information and Automation, IEEE ICIA 2016 - Ningbo, China
Duration: 1 Aug 20163 Aug 2016

Publication series

Name2016 IEEE International Conference on Information and Automation, IEEE ICIA 2016

Conference

Conference2016 IEEE International Conference on Information and Automation, IEEE ICIA 2016
Country/TerritoryChina
CityNingbo
Period1/08/163/08/16

Keywords

  • Coefficient of variation
  • Low back pain
  • Root mean square
  • Surface electromyography

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Computational Mechanics

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