Muscle co-contraction during the execution of motor tasks or training is common in poststroke subjects. EMG-derived muscular activation indexes have been used to evaluate muscle co-contractions during movements. In addition, robot-assisted bilateral arm training provides a repetitive and stable training method to improve arm movements. However, quantitative measures of muscle contractions during this training in poststroke subjects have not been described.
Seventeen subjects experiencing spastic hemiplegia after a stroke were recruited to perform robot-assisted bilateral wrist flexion and extension movements. The co-contraction index and two new indexes, temporal correlation and cross mutual information, which are derived from the EMGs of working muscles without the need for envelope normalization, are used to quantify intermuscular activation during wrist movements.
Higher temporal correlation as well as higher co-contraction index was demonstrated in the affected muscles, implying the recruitment of muscle co-contractions to complete the movement task. On the other hand, a higher value of cross mutual information was exhibited in the unaffected muscles which was attributed to their distinct, rhythmic muscle contractions. The plot of temporal correlation versus cross mutual information further defined affected, unaffected synergistic, and unaffected agonist-antagonist muscular regions. Moreover, with the modified Ashworth scale, multiple regression models based on the co-contraction index and cross mutual information had the highest R-squared value of 0.733.
EMG-derived intermuscular activation parameters demonstrated muscle co-contractions in the affected muscles and different types of intermuscular contractions during robot-assisted bilateral arm training. The modified Ashworth scale estimation based on multiple regression analysis of the activation indexes also demonstrated EMG-derived index a valuable method for assessing muscle spasticity in subjects with poststroke hemiplegia.

Copyright © 2021. Published by Elsevier Ltd.

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