Wavelet Coherence Analysis of Post-Stroke Intermuscular Coupling Modulated by Myoelectric-Controlled Interfaces

Area of Science:

• Neuroscience
• Rehabilitation Engineering
• Biomedical Engineering

Background:

• Intermuscular coupling, crucial for muscle control, is impaired after stroke.
• The impact of stroke on intermuscular coupling and the potential of myoelectric-controlled interfaces (MCI) remain under-explored.

Purpose of the Study:

• To investigate how the dimensionality of myoelectric-controlled interfaces (MCI) influences intermuscular coupling in stroke survivors.
• To assess the efficacy of different MCI dimensionalities on motor performance and muscle coordination post-stroke.

Main Methods:

• Ten age-matched controls and eight stroke patients performed elbow tracking tasks using 1D or 2D MCI.
• Movement performance was measured using root mean square error (RMSE).
• Intermuscular coupling was analyzed using wavelet coherence in alpha (8-12 Hz) and beta (15-35 Hz) bands.

Main Results:

• Both groups showed improved performance (smaller RMSE) with 2D MCI compared to 1D MCI.
• Stroke patients exhibited significantly lower alpha-band wavelet coherence during elbow extension compared to controls.
• Increasing MCI dimensionality led to decreased alpha- and beta-band wavelet coherence in both groups.

Conclusions:

• Stroke-related neural impairments negatively affect motor performance and intermuscular coordination.
• Myoelectric-controlled interfaces (MCI) demonstrate promise as a rehabilitation tool by directly modulating muscle activation patterns.
• Further research into MCI dimensionality could optimize stroke rehabilitation strategies.