
Meeting Abstract
Accurately modeling muscle forces produced during dynamic animal movements is critical for understanding the biomechanics and neural control of locomotion. Although a large amount of effort has been put towards this endeavor, muscle models are still unable to predict forces during dynamic gaits, especially with perturbations (e.g. moving over obstacles). In this study, we use a novel model inspired by the winding-filament hypothesis to predict forces in running guinea fowl. Lateral gastrocnemius and digital flexor muscle lengths, activations and forces were measured using sonomicrometry, implanted EMG, and tendon buckles, respectively. Two fowls were recorded running on a treadmill under three conditions; level running, running over a 5cm obstacle, and running over a 7cm obstacle. Physiological parameters measured from the birds included the pennation angle, mass of the muscle, and the muscle resting length. The EMG was smoothed, transformed to a percentage of maximum activation, and a time delay was introduced to account for excitation-contraction coupling. The winding filament model (WFM) uses second-order differential equations to describe the kinetics and kinematics of a damped mass-spring system that consists of a contractile element in series with a spring. The contractile element is also in series and parallel with a second spring and damper, which wraps around a pulley and represents the titin protein. Muscle length and activation are inputs to the model, and muscle force is predicted in each time step. The free parameters were optimized and the predicted force was compared to the measured force. Early results show that the WFM-based model can more accurately predict forces during perturbed and level gaits (R2 = 0.59 -0.86) than published results using complex Hill-type models.