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Decoding temporal muscle synergy patterns based on brain activity for upper extremity in ADL movements.

Mahdie Khaliq Fard1, Ali Fallah1, Ali Maleki2

  • 1Biomedical Engineering Department, Amirkabir University of Technology, Tehran, Iran.

Cognitive Neurodynamics
|May 3, 2024
PubMed
Summary

This study maps brain activity to muscle synergies during daily movements, developing a new method for neural decoding. This advance aids in creating better neurorehabilitation tools like neuroprosthetics.

Keywords:
ADL movementsElectroencephalogramElectromyogramMuscle synergiesPLS-CCAUpper extremity

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Motor Control

Background:

  • Muscle synergies are theorized motor primitives simplifying complex movements.
  • The neural basis and brain activity expression of muscle synergies remain unclear.
  • Investigating brain-muscle synergy links is crucial for understanding motor control and developing assistive technologies.

Purpose of the Study:

  • To develop a synergy-based neural decoding method for motor primitives.
  • To map brain activity and muscle synergies in the upper extremity during daily living activities.
  • To establish a novel approach for estimating neural decoding performance in motor control.

Main Methods:

  • Simultaneous acquisition of electroencephalogram (EEG) and electromyogram (EMG) signals during activities of daily living.
  • Application of partial least squares and canonical correlation analysis (PLS-CCA) to correlate neural commands with muscle synergies.
  • Utilizing an Elman neural network for decoding the relationship between motor commands and muscle synergies.
  • Validation through tenfold cross-validation.

Main Results:

  • The proposed method achieved high accuracy in estimating muscle synergies from brain activity (R: 84±2.6%, VAF: 70±4.7%, MSE: 0.00011±0.00002).
  • Reconstructed muscle activations showed over 92% correlation with actual activations.
  • The model demonstrated significantly higher accuracy compared to existing methods.
  • Confirmed the utility of muscle synergy expression in brain activity for neural decoding.

Conclusions:

  • Muscle synergy expression in brain activity can effectively estimate neural decoding performance.
  • The developed synergy-based neural decoding method offers a promising approach for motor control research.
  • This research paves the way for advanced neurorehabilitation tools, including neuroprostheses.