Affiliations: [a] "Electrical Engineering, Indian Institute of Technology Gandhinagar, Gandhinagar, India
| [b] Department of Biomedical Engineering, University at Buffalo, Buffalo, NY, USA
Correspondence:
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Address for correspondence: Adyasha Dash, AB-5/205, Indian Institute of Technology Gandhinagar, Gandhinagar, Gujarat 382355, India. Tel.: +91 9913320856; E-mail: adyasha.dash@iitgn.ac.in.
Abstract: BACKGROUND:Reduction in grip-strength due to spasticity is a common cause of impairment after stroke. OBJECTIVE:To find an objective measure of post-stroke spasticity affecting grip-strength through quantification of interaction between antagonist and agonist muscles using complexity analysis of surface electromyogrm (sEMG) signals during isometric grip in healthy and post-stroke participants. METHODS:The interaction between sEMG signals from antagonist and agonist muscles is quantified through Multiscale-Multivariate-Sample-Entropy (MMSE). This is used to quantify dissimilarity between hands of 12 healthy and 8 post-stroke participants during isometric grip. The clinical relevance of MMSE is explored by examining its correlation with spasticity score i.e. Modified-Ashworth-Scale (MAS). Further, potential of sEMG-based approach to quantify muscle-specific dissimilarity in sEMG activation across hands is investigated in terms of Cepstral-coefficients and power content of sEMG during grip tasks. RESULTS:Mean MMSE scores of sEMG signals were significantly different (p < 0.05) between paretic and non-paretic hands of Post-stroke participants. High negative correlation was observed between spasticity and complexity scores of paretic hand for post-stroke participants. CONCLUSIONS:A negative correlation between MAS and MMSE shows higher spasticity can lead to reduced complexity in sEMG. Thus, MMSE based complexity analysis can be used as an indicator of spasticity, affecting grip function.
