3D muscle networks based on vibrational mechanomyography

• Published in: Journal of neural engineering 2023-12, Vol.20 (6), p.66008
• Main Authors: Mancero Castillo, C Sebastian, Atashzar, S Farokh, Vaidyanathan, Ravi
• Format: Article
• Language: English
• Subjects: Elbow; Electromyography; Forearm; Humans; intermuscular coherence; mechanomyography; Muscle Fibers, Skeletal; muscle networks; Muscle, Skeletal - physiology
• ISSN: 1741-2560; 1741-2552
• DOI: 10.1088/1741-2552/ad017c

. Muscle network modeling maps synergistic control during complex motor tasks. Intermuscular coherence (IMC) is key to isolate synchronization underlying coupling in such neuromuscular control. Model inputs, however, rely on electromyography, which can limit the depth of muscle and spatial information acquisition across muscle fibers. . We introduce three-dimensional (3D) muscle networks based on vibrational mechanomyography (vMMG) and IMC analysis to evaluate the functional co-modulation of muscles across frequency bands in concert with the longitudinal, lateral, and transverse directions of muscle fibers. vMMG is collected from twenty subjects using a bespoke armband of accelerometers while participants perform four hand gestures. IMC from four superficial muscles (flexor carpi radialis, brachioradialis, extensor digitorum communis, and flexor carpi ulnaris) is decomposed using matrix factorization into three frequency bands. We further evaluate the practical utility of the proposed technique by analyzing the network responses to various sensor-skin contact force levels, studying changes in quality, and discriminative power of vMMG. . Results show distinct topological differences, with coherent coupling as high as 57% between specific muscle pairs, depending on the frequency band, gesture, and direction. No statistical decrease in signal strength was observed with higher contact force. . Results support the usability vMMG as a tool for muscle connectivity analyses and demonstrate the use of IMC as a new feature space for hand gesture classification. Comparison of spectrotemporal and muscle network properties between levels of force support the robustness of vMMG-based network models to variations in tissue compression. We argue 3D models of vMMG-based muscle networks provide a new foundation for studying synergistic muscle activation, particularly in out-of-clinic scenarios where electrical recording is impractical.