Novel mechanomyogram/electromyogram hybrid transducer measurements reflect muscle strength during dynamic exercise — Pedaling of recumbent bicycle

Shinichi Fukuhara, Shogo Watanabe, Hisao Oka

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Simultaneous measurements of mechanomyogram (MMG) and electromyogram (EMG) may be useful for accurate evaluation of skeletal muscle contraction. However, unlike the EMG, the MMG is rarely used in clinical tests. As the target muscle has to be fixed during conventional MMG measurements, it is not possible to measure MMG during dynamic exercises such as sports and rehabilitation. To solve these problems, the authors developed an MMG (displacement-MMG)/EMG hybrid transducer system that allows simultaneous MMG and EMG measurements. Furthermore, we also developed an analysis method that is able to evaluate muscle contraction using the power spectra of each signal. The measurement system and the analysis method were applied to recumbent bicycle pedaling, during which work rate was increased incrementally. The results showed that this transducer system provided MMG/EMG measurements stably during dynamic exercise. When the work rate of the bicycle pedaling increased; that is, when the dynamic muscle strength increased, the sum of the power spectra of the MMG/EMG also increased. The MMG/EMG hybrid transducer system and the analysis method were useful for evaluating muscle strength during dynamic exercise.

Original languageEnglish
Pages (from-to)47-54
Number of pages8
JournalAdvanced Biomedical Engineering
Volume7
DOIs
Publication statusPublished - Jan 1 2018

Fingerprint

Bicycles
Muscle Strength
Electromyography
Transducers
Muscle
Foot
Power spectrum
Muscle Contraction
Systems Analysis
Sports
Patient rehabilitation
Skeletal Muscle
Rehabilitation
Muscles

Keywords

  • Displacement-MMG
  • Electromyogram (EMG)
  • Mechanomyogram (MMG)
  • Recumbent bicycle

ASJC Scopus subject areas

  • Biomedical Engineering
  • Biomaterials
  • Biotechnology
  • Computer Science Applications
  • Computer Vision and Pattern Recognition

Cite this

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