Muscle-driven hand simulations emphasize the critical role of the extensor mechanism
Carvajal, M.; Murray, W. M.; Miller, L. E.; Firouzabadi, P.; Rizzoglio, F.; Darbhe, V.; Cotton, J.
Show abstract
Biomechanical simulations of complex hand motions remain scarce, due to challenges that span computation and data acquisition. Using a computer vision-based motion capture approach, a 23-degree of freedom musculoskeletal model, and direct collocation optimization, we performed muscle-driven simulations to track hand kinematics from 7 participants performing American Sign Language gestures. While proximal joints were tracked accurately, interphalangeal joint tracking was significantly worse, with a consistent flexion bias. Modifications to finger extensor muscle paths that incorporated the dual-inserting nature of the extensors improved accuracy, suggesting better representation of extensor force distribution across distal joints may be necessary for accurate hand simulations.
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