Force enhancement and force depression in a modified muscle model used for muscle activation prediction

Abstract

Functional biomechanical tests allow the assessment of musculoskeletal system impairments in a simple way. Muscle force synergies associated with movement can provide additional information for diagnosis. However, such forces cannot be directly measured noninvasively. This study aims to estimate muscle activations and forces exerted during the preparation phase of the single leg triple hop test. Two different approaches were tested: static optimization (SO) and computed muscle control (CMC). As an indirect validation, model-estimated muscle activations were compared with surface electromyography (EMG) of selected hip and thigh muscles. Ten physically healthy active women performed a series of jumps, and ground reaction forces, kinematics and EMG data were recorded. An existing OpenSim model with 92 musculotendon actuators was used to estimate muscle forces. Reflective markers data were processed using the OpenSim Inverse Kinematics tool. Residual Reduction Algorithm (RRA) was applied recursively before running the SO and CMC. For both, the same adjusted kinematics were used as inputs. Both approaches presented similar residuals amplitudes. SO showed a closer agreement between the estimated activations and the EMGs of some muscles. Due to inherent EMG methodological limitations, the superiority of SO in relation to CMC can be only hypothesized. It should be confirmed by conducting further studies comparing joint contact forces. The workflow presented in this study can be used to estimate muscle forces during the preparation phase of the single leg triple hop test and allows investigating muscle activation and coordination.