Antagonistic co-contraction can minimize muscular effort in systems with uncertainty

• DOI: 10.7717/peerj.13085
• Publication Date: 2022-04-07T07:24:05Z
• Authors: Anne D. Koelewijn; Antonie J. Van De...
• Keywords: Feed forward; Feedforward neural network

Muscular co-contraction of antagonistic muscle pairs is often observed in human movement, but it considered inefficient and can currently not be predicted simulations where muscular effort or metabolic energy are minimized. Here, we investigated the relationship between minimizing systems with random uncertainty to see if minimize such system. We also effect time delay muscle, by varying neural control as well activation constant. solved optimal problems for a one-degree-of-freedom pendulum actuated two identical muscles, using forward shooting, find controller parameters that minimized while remained upright presence noise added moment at base pendulum. compared without feedforward control. Task precision was defined bounding root mean square deviation from position, different perturbation levels task difficulty. found when nonzero, even necessary perform task, which indicates uncertainty. level increased delay, both constant added. Furthermore, controllers trajectory than one without, simulation trajectories dependent on architecture. Future movement predictions should therefore account dynamics control, carefully choose The ability models predict minimization has important clinical sports applications. If undesirable, aim remove cause rather itself.