Abstract: N. Zhang, K. Li, G. Li, R. Nataraj, N. Wei (2021)

IEEE Transactions on Neural Systems and Rehabilitation Engineering, 29, 2055–2066p. (2021) DOI:10.1109/TNSRE.2021.3117286

Multiplex Recurrence Network Analysis of Inter-Muscular Coordination During Sustained Grip and Pinch Contractions at Different Force Levels

Production of functional forces by human motor systems require coordination across multiple muscles. Grip and pinch are two prototypes for grasping force production. Each grasp plays a role in a range of hand functions and can provide an excellent paradigm for studying fine motor control. Despite previous investigations that have characterized muscle synergies during general force production, it is still unclear how intermuscular coordination differs between grip and pinch and across different force outputs. Traditional muscle synergy analyses, such as non-negativematrix factorizationor principal component analysis, utilize dimensional reduction without consideration of nonlinear characteristics of muscle co-activations. In this study, we investigated the novel method of multiplex recurrence networks (MRN) to assess the inter-muscular coordination for both grip and pinch at different force levels. Unlike traditional methods, the MRN can leverage intrinsic similarities in muscle contraction dynamics and project its layers to the correspondingweighted network (WN) to better model muscle interactions. Twenty-four healthy volunteers were instructed to grip and pinch an apparatus with force production at 30%, 50%, and 70% of their respective maximal voluntary contraction (MVC). The surface electromyography (sEMG) signals were recorded from eight muscles, including intrinsic and extrinsic muscles spanning the hand and forearm. The sEMG signals were then analyzed using MRNs and WNs. Interlayer mutual information (I) and average edge overlap (omega) of MRNs and average shortest path length (L) of WNs were computed and compared across groups for grasp types (grip vs. pinch) and force levels (30%, 50% and 70% MVC). Results showed that the extrinsic, rather than the intrinsic muscles, had significant differences in network parameters between both grasp types (p < 0.05), and force levels (p < 0.05), and especially at higher force levels. Furthermore, I and omega were strengthened over time (p < 0.05) except with pinch at 30% MVC. Results suggest that the central nervous system (CNS) actively increases cortical oscillations over time in response to increasing force levels and changes in force production with different sustained grasping types. Muscle coupling in extrinsic muscles was higher than in intrinsic muscles for both grip and pinch. The MRNs may be a valuable tool to provide greater insights into inter-muscular coordination patterns of clinical populations, assess neuromuscular function, or stabilize force control in prosthetic hands.

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