Complex Network Analysis of Surface Electromyography Shows Impaired Global Structure of Chronic Stroke Survivors with Hemiparesis

Abstract

<h3>Research Objectives</h3> To investigate the use of high-density surface electromyography (EMG) and complex network analysis to quantify upper extremity motor impairment in chronic stroke survivors with hemiparesis. EMG can provide insights into the residual neuro-muscular activity during attempted functional movement. Using network analysis, we can determine how different muscle regions interact to create complex motion and the associated deficits after stroke. <h3>Design</h3> In three two-hour sessions, we led participants through attempted functional movements of the hand, fingers, and wrist while recording EMG activity using the NeuroLife® Sleeve, a 150-electrode wearable forearm garment. <h3>Setting</h3> Studies were conducted within Battelle's research facilities in Columbus, Ohio. <h3>Participants</h3> Six chronic stroke survivors (>6 months post-stroke) with moderate UE impairment (UEFM: 7-38). <h3>Interventions</h3> Not applicable. <h3>Main Outcome Measures</h3> Global efficiency and local clustering of the functional EMG networks. Global efficiency measures the ease of traversal of the network topology, with many regions in close coordination with each other showing increased efficiency. Local clustering measures the amount of electrode triads that appear in the network architecture, a measure of local microstructure. <h3>Results</h3> We find that network graphs from participants show differing topological structure that relates to the level of impairment of the participant. Specifically, participants with moderate to severe hand impairment had lower global network efficiency and local clustering when compared to mild-impairment participants or able-bodied controls. These results show that differences in network topology are sensitive to the pathophysiology that follows stroke. <h3>Conclusions</h3> Complex network analysis of surface EMG can provide a novel, quantifiable assessment of the extent of deficit in subjects with chronic stroke. <h3>Author(s) Disclosures</h3> None.