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Multi-scale complexity analysis of muscle coactivation during gait in children with cerebral palsy

Wen Tao1, Xu Zhang1, Xiang Chen1

  • 1Neuromuscular Control Laboratory, Department of Electronic Science and Technology, University of Science and Technology of China Hefei, China.

Frontiers in Human Neuroscience
|August 11, 2015
PubMed

Insights

This study used advanced analysis to examine muscle coordination in children with cerebral palsy (CP) during walking. Results show unique complexity patterns in CP, offering insights into neuropathology and motor function assessment.

Area of Science:

  • Biomedical Engineering
  • Neuroscience
  • Rehabilitation Science

Background:

  • Cerebral palsy (CP) affects motor control, impacting gait and muscle coordination.
  • Understanding the complexity of muscle coactivation during gait is crucial for CP assessment.
  • Existing methods may not fully capture the nuanced dynamics of muscle activity in CP.

Purpose of the Study:

  • To characterize lower-extremity muscle coactivation and coordination complexity during gait in children with CP.
  • To compare gait muscle coordination complexity between children with CP, typically developing (TD) children, and healthy adults.
  • To apply multivariate multi-scale entropy (MMSE) analysis to surface electromyographic (EMG) signals for novel insights into CP neuropathology.

Main Methods:

  • Collected 16-channel surface EMG data from thigh and lower leg muscles during walking in 11 CP children, 8 TD children, and 7 healthy adults.
  • Processed EMG data using multivariate empirical mode decomposition (MEMD) for aligned data scales.
  • Applied multivariate multi-scale entropy (MMSE) analysis across 14 schemes varying muscle combinations and time durations.

Main Results:

  • Typically developing children and healthy adults exhibited consistent MMSE curves, indicating stable muscle coactivation complexity.
  • Children with CP displayed distinct and diverse MMSE curve patterns compared to the control group.
  • Abnormal complexity patterns in CP were linked to motor control impairments, altered muscle couplings, spasticity, or paralysis.

Conclusions:

  • CP is associated with altered dynamical complexity of muscle coactivation and coordination during gait.
  • Neuropathological processes in CP manifest as diverse muscle activation patterns.
  • This novel approach may lead to quantitative indices for assessing muscle activation and motor function in CP.
  • Findings expand understanding of CP neuropathology through the lens of muscle co-activation complexity.

Keywords:
cerebral palsyelectromyographygait analysismulti-scale analysismultivariate sample entropy

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