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[Intermuscular coupling based on wavelet packet-cross frequency coherence].

Yihao Du1, Xiaolin Bai1, Wenjuan Yang1

  • 1Key Lab of Measurement Technology and Instrumentation of Hebei Province, Institute of Electric Engineering, Yanshan University, Qinhuangdao, Hebei 066004, P.R.China.

Sheng Wu Yi Xue Gong Cheng Xue Za Zhi = Journal of Biomedical Engineering = Shengwu Yixue Gongchengxue Zazhi
|April 25, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces a novel wavelet packet-n:m coherence model to analyze muscle coordination. The findings reveal how linear and nonlinear muscle coupling strength changes during elbow movements, aiding in understanding human motion control and rehabilitation.

Keywords:
electromyography signaln:m coherence analysisnonlinear couplingwavelet packet decomposition

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Biomechanics

Background:

  • Human motion control exhibits complex nonlinear characteristics.
  • Analyzing nonlinear coupling in surface electromyogram (sEMG) signals offers insights into muscle function and movement mechanisms.
  • Understanding intermuscular coordination is crucial for motor control research and rehabilitation.

Purpose of the Study:

  • To develop and validate a novel analysis model for intermuscular cross-frequency coupling using wavelet packet decomposition and n:m coherence.
  • To quantitatively evaluate the nonlinear coupling strength between muscles during elbow flexion and extension.
  • To explore the relationship between coupling characteristics and muscle function in healthy adults.

Main Methods:

  • Collected sEMG signals from 20 healthy adults during 30% maximum voluntary contraction (MVC) elbow flexion/extension.
  • Applied wavelet packet decomposition to obtain subband components of sEMG signals.
  • Calculated n:m coherence (including linear 1:1 and nonlinear ratios like 1:2, 2:1, 1:3, 3:1) to analyze intermuscular coupling.

Main Results:

  • Linear coupling (1:1) was stronger than nonlinear coupling (1:2, 2:1, 1:3, 3:1) during elbow flexion at 30% MVC.
  • Intermuscular nonlinear coupling strength decreased with increasing frequency ratios (n:m).
  • Significant intermuscular coupling was observed in beta and gamma bands, with distinct patterns for synergistic and antagonistic muscle pairs.

Conclusions:

  • The proposed wavelet packet-n:m coherence method effectively quantifies nonlinear intermuscular coupling strength.
  • This approach provides a valuable tool for understanding human motor control mechanisms.
  • The findings offer a theoretical basis for rehabilitation evaluation in individuals with motor dysfunction.