Classification of abnormal muscle synergies during sit-to-stand motion in individuals with acute stroke

Abstract For clinicians to provide more efficient early mobilization in patients with acute stroke, they must quantitatively evaluate the motion characteristics of the patients. To measure the motion in the acute phase, it is necessary to prevent physical interference between the measurement and medical equipment. This study classified abnormal muscle synergies during sit-to-stand motion in patients with acute stroke by using small, wirelessly operable, noninvasive surface electromyography devices. Four patients with acute stroke and four healthy adults performed a six-directional isometric contraction task and a sit-to-stand motion task. A nonnegative matrix factorization algorithm was applied to the muscle activity data to extract the muscle synergies. Hierarchical cluster analysis was used to classify these synergies. The results suggest that sit-to-stand motion characteristics according to the severity of effects in patients with acute stroke can be quantitatively classified by muscle synergy analysis. The spatial structure of muscle synergies of patients was classified into different clusters from that of the healthy adults. The abnormal muscle synergy in patients with severe paresis is considered severe in that it cannot be modulated according to the task. The muscle synergies in patients with moderate paresis were modulated in the sit-to-stand motion to compensate for extensor muscle weakness. Such abnormal muscle synergy in the sit-to-stand motion is useful as a reference for motion practice, especially for early mobilization after the onset of a stroke. In addition, the results verify that the early to late stages of recovery can be consistently evaluated with this small, wireless noninvasive electromyography device.