Clinical applications of high-density surface EMG: A systematic review

G Drost, D.F. Stegeman, B.G.M. van Engelen, J.A.M. Smeitink, J.A. Rodenburg, F.A. Hol

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

High density-surface EMG (HD-sEMG) is a non-invasive technique to measure electrical muscle activity with multiple (more than two) closely spaced electrodes overlying a restricted area of the skin. Besides temporal activity HD-sEMG also allows spatial EMG activity to be recorded, thus expanding the possibilities to detect new muscle characteristics. Especially muscle fiber conduction velocity (MFCV) measurements and the evaluation of single motor unit (MU) characteristics come into view. This systematic review of the literature evaluates the clinical applications of HD-sEMG. Although beyond the scope of the present review, the search yielded a large number of "non-clinical" papers demonstrating that a considarable amount of work has been done and that significant technical progress has been made concerning the feasibility and optimization of HD-sEMG techniques. Twenty-nine clinical studies and four reviews of clinical applications of HD-sEMG were considered. The clinical studies concerned muscle fatigue, motor neuron diseases (MND), neuropathies, myopathies (mainly in patients with channelopathies), spontaneous muscle activity and MU firing rates. In principle, HD-sEMG allows pathological changes at the MU level to be detected, especially changes in neurogenic disorders and channelopathies. We additionally discuss several bioengineering aspects and future clinical applications of the technique and provide recommendations for further development and implementation of HD-sEMG as a clinical diagnostic tool. © 2006 Elsevier Ltd. All rights reserved.
Original languageEnglish
Pages (from-to)568-602
JournalJournal of Electromyography and Kinesiology
Volume16
DOIs
Publication statusPublished - 2006

Fingerprint

Dive into the research topics of 'Clinical applications of high-density surface EMG: A systematic review'. Together they form a unique fingerprint.

Cite this