Muscle networks analysis on an active occupational shoulder exoskeleton

Muscle networks describe how different muscles, driven by neural inputs from motor cortex areas, can share oscillatory signals and form functional connections. These networks may help explain how the brain coordinates movement despite many degrees of freedom. This study examined how an assistive wearable device (an occupational exoskeleton) affects these neural–muscular structures. Functional muscle networks were analyzed in healthy participants (N = 9) during isometric and load-carrying tasks performed with and without the exoskeleton. Inter-muscular coherence (IMC) and network metrics, including betweenness centrality (BC) and clustering coefficient (CC), were extracted. At the global level, the exoskeleton preserved spectral organization and bilateral symmetry in both tasks, with no significant changes in global BC or CC ( p > 0 . 05 ), consistent with known muscle synergies and supporting muscle networks as a potential neurophysiological biomarker. Locally, three effects emerged: (a) a shift of IMC toward lower frequencies, suggesting stronger contralateral coupling; (b) connection gains/losses aligned with device assistance, with trapezius showing increased connectivity (+2) and deltoids reduced connectivity (−3); and (c) reductions in muscle effort correlated linearly with decreases in BC (R = 0.652, p = 0 . 041 ), indicating that more assisted muscles lose centrality within local anatomical circuits. Despite the limited sample size, these results suggest functional muscle networks can quantify how assistive devices modulate neural coherence and muscle coordination, complementing time-domain analyses. The proposed methodology may guide future exoskeleton designs toward improved usability, wearability, and optimized assistance.