Abstract
Objective: While neuroplasticity and functional reorganization during motor recovery can be indirectly reflected and evaluated by functional corticomuscular coupling (fCMC), little work has been published regarding the cortical origin of abnormal muscle synergy and compensatory mechanism in the separation movement of stroke patients.
Methods: In this study, we proposed to use extended partial directed coherence (ePDC) combined with an optimal spatial filtering approach to estimate fCMC in stroke patients and healthy controls, and further established muscle synergy model (MSM) to jointly explore the modulation mechanism between cortex and muscles.
Results: Compared to healthy controls, stroke patients had significantly reduced coupling strength in both descending and ascending pathway. Moreover, the MSM were abnormal with high variability and low similarity in the separation stage of stroke patients. Further exploration of the positive relationship between fCMC characteristics and MSM parameters proved the possibility of using fCMC-MSM-based correlation indicator to evaluate abnormality of the cortical related synergy movement as well as the rehabilitation level of stroke patients.
Conclusion: We developed a computational procedure to evaluate the correlation between fCMC and MSM in stroke patients. Significance: This article provides a quantitative evaluation metrics based on fCMC to reveal the deficits during poststroke motor restoration and a promising approach to help patients correct abnormal movement habits, paving the way for neurophysiological assessment of neuromuscular control in conjunction with clinical scores.
Original language | English |
---|---|
Journal | IEEE Transactions on Biomedical Engineering |
Early online date | 25 Mar 2021 |
DOIs | |
Publication status | Early online - 25 Mar 2021 |
Keywords
- abnormal movement
- Correlation
- Couplings
- Electroencephalography
- Electromyography
- Functional corticomuscular coupling
- muscle synergy
- Muscles
- neurophysiological metrics
- stroke
- Stroke (medical condition)
- Task analysis