Coherence Networks of Bilateral Upper Limb Motions in Chronic Stroke Patients

Abstract

Understanding the mechanisms of how the skeletal system reduces multiple degrees of freedom in motor control is very important in the field of neurorehabilitation. We therefore need to understand the functional connectivity of these synergistic patterns in bilateral upper limb of stroke patients from different Brunnstrom Stages. The intermuscular coherence at different frequency bands is decomposed to obtain muscle synchronization. Muscle networks were then applied to describe the functional connectivity between muscle pairs. We recruited 35 stroke patients with Brunnstrom Stages III-VI. Muscle activity was acquired from seven muscles around forearm while participants performed voluntary upward reaching with both affected and unaffected sides. We decomposed IMC spectra by negative matrix factorization to identify shared frequencies and co-modulated muscles. Two muscle networks were found and functional muscle networks are evaluated by strength, transitivity and global efficiency. Results showed that the network topology was different significantly between the two sides and between Brunnstrom stages of stroke patients. These findings can throw light on the understanding of motor control and rehabilitation of motor impairment for stroke survivors, which may promote the post-stroke rehabilitation process by detecting impaired neuromuscular coordination in frequency domain.