Muscle-driven forward dynamics simulation for the study of differences in muscle function during stair ascent and descent.

The main scope of this study is to analyse muscle-driven forward dynamics simulation of stair locomotion to understand the functional differences of individual muscles during the movement. A static optimization was employed to minimize a performance criterion based on the muscle energy consumption to resolve muscle redundancy during forward dynamics simulation. The proposed method was employed to simulate a musculoskeletal system with ten degrees of freedom in the sagittal plane and containing 18 Hill-type musculotendon actuators per leg. Simulation results illustrated that simulated joint kinematics closely tracked experimental quantities with root-mean-squared errors less than 1 degree. In addition, estimated muscle activations have a good agreement with the salient features of the electromyographic recordings of the major muscles of the lower extremity. Distribution of mechanical power for individual muscles was estimated to elucidate the muscle's contribution to body support and forward progression during stair locomotion. The accuracy and relatively high computational performance of the proposed method make it suitable to generate subject-specific simulations of various activities for individuals with movement disorders in clinical studies.

Feedback control of the neuromusculoskeletal system in a forward dynamics simulation of stair locomotion.

The aim of this study is to employ feedback control loops to provide a stable forward dynamics simulation of human movement under repeated position constraint conditions in the environment, particularly during stair climbing. A ten-degrees-of-freedom skeletal model containing 18 Hill-type musculotendon actuators per leg was employed to simulate the model in the sagittal plane. The postural tracking and obstacle avoidance were provided by the proportional-integral-derivative controller according to the modulation of the time rate change of the joint kinematics. The stability of the model was maintained by controlling the velocity of the body's centre of mass according to the desired centre of pressure during locomotion. The parameters of the proposed controller were determined by employing the iterative feedback tuning approach to minimize tracking errors during forward dynamics simulation. Simultaneously, an inverse-dynamics-based optimization was employed to compute a set of desired musculotendon forces in the closed-loop simulation to resolve muscle redundancy. Quantitative comparisons of the simulation results with the experimental measurements and the reference muscles' activities illustrate the accuracy and efficiency of the proposed method during the stable ascending simulation.