Literature DB >> 26188951

Determining minimal stimulus intensity for mechanomyographic analysis.

Danijel Tosovic1, Laura Seidl2, Estifanos Ghebremedhin2, Mark J Brown2.   

Abstract

INTRODUCTION: Mechanomyography (MMG) has recently shown promise in monitoring recovery of injured muscles. However, delivering a maximal percutaneous neuromuscular stimulus (PNS) could potentially be painful on severely damaged muscles. The aim of this paper was to determine whether delivering a sub-maximal PNS could still obtain accurate MMG recordings of muscle contraction time (Tc). The effect of muscle architecture on determining the minimal level of current was also investigated.
METHODS: Six muscles were investigated; 5 lower limb and the 1st dorsal interosseous. A 'current ramp' procedure was performed to determine minimal stimulus intensity required for accurate Tc recordings. A current ramp entails beginning at a low current (30mA) and increasing in increments of 10mA until a maximal muscle contraction is observed.
RESULTS: For lower limb muscles, 130mA was the largest current required to obtain accurate Tc recordings in at least 95% of the population. This was up to a 50% reduction in the amount of current delivered for some muscles. Fibre type distribution showed the greatest relationship with mean minimum current. DISCUSSION: Future studies investigating injured or uninjured muscles via MMG, could use these submaximal currents to obtain accurate MMG recordings, whilst improving patient comfort and reducing experiment duration.
Copyright © 2015 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Contraction time; Injury; Mechanomyography; Muscle; Stimulation

Mesh:

Year:  2015        PMID: 26188951     DOI: 10.1016/j.jelekin.2015.06.003

Source DB:  PubMed          Journal:  J Electromyogr Kinesiol        ISSN: 1050-6411            Impact factor:   2.368


  3 in total

1.  The effect of exercise hypertrophy and disuse atrophy on muscle contractile properties: a mechanomyographic analysis.

Authors:  Christian Than; Danijel Tosovic; Laura Seidl; J Mark Brown
Journal:  Eur J Appl Physiol       Date:  2016-09-10       Impact factor: 3.078

2.  The effects of accumulated muscle fatigue on the mechanomyographic waveform: implications for injury prediction.

Authors:  D Tosovic; C Than; J M M Brown
Journal:  Eur J Appl Physiol       Date:  2016-06-03       Impact factor: 3.078

3.  An Individual Finger Gesture Recognition System Based on Motion-Intent Analysis Using Mechanomyogram Signal.

Authors:  Huijun Ding; Qing He; Yongjin Zhou; Guo Dan; Song Cui
Journal:  Front Neurol       Date:  2017-11-08       Impact factor: 4.003

  3 in total

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