Multi-scale surface electromyography modeling to identify changes in neuromuscular activation with myofascial pain

Ching Fen Jiang, Yu Ching Lin, Nan Ying Yu

研究成果: Article

7 引文 (Scopus)

摘要

To solve the limitations in using the conventional parametric measures to define myofascial pain, a 3-D multi-scale wavelet energy variation graph is proposed as a way to inspect the pattern of surface electromyography (SEMG) variation between the dominant and nondominant sides at different frequency scales during a muscle contraction cycle and the associated changes with the upper-back myofascial pain. The model was developed based on the property of the wavelet energy of the SEMG signal revealing the degree of correspondence between the shape of the motor unit action potential and the wavelet waveform at a certain scale in terms of the frequency band. The characteristic pattern of the graph for each group (30 normal and 26 patient subjects) was first derived and revealed the dominant-hand effect and the changes with myofascial pain. Through comparison of individual graphs across subjects, we found that the graph pattern reveals a sensitivity of 53.85% at a specificity of 83.33% in the identification of myofascial pain. The changes in these patterns provide insight into the transformation between different fiber recruitment, which cannot be explored using conventional SEMG features. Therefore, this multi-scale analysis model could provide a reliable SEMG features to identify myofascial pain.

原文English
文章編號6327369
頁(從 - 到)88-95
頁數8
期刊IEEE Transactions on Neural Systems and Rehabilitation Engineering
21
發行號1
DOIs
出版狀態Published - 2013 一月 16

指紋

Electromyography
Chemical activation
Pain
Back Pain
Muscle Contraction
Action Potentials
Frequency bands
Muscle
Hand
Fibers

All Science Journal Classification (ASJC) codes

  • Internal Medicine
  • Neuroscience(all)
  • Biomedical Engineering

引用此文

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