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

Ching Fen Jiang, Yu Ching Lin, Nan Ying Yu

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number6327369
Pages (from-to)88-95
Number of pages8
JournalIEEE Transactions on Neural Systems and Rehabilitation Engineering
Volume21
Issue number1
DOIs
Publication statusPublished - 2013 Jan 16

All Science Journal Classification (ASJC) codes

  • Internal Medicine
  • Neuroscience(all)
  • Biomedical Engineering

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