Constrained Optimization for Prediction of Posture

The ability to stand still in one place is important in a variety of activities of daily living. For persons with motion disorders, orthopaedic treatment, which changes geometric or biomechanical properties, can improve the individual’s posture and walking ability. Decisions on such treatment require insight in how posture and walking ability are affected, however, despite expectations based on experience, it is never a-priori known how a patient will react to a treatment. As this is very challenging to observe by the naked eye, engineering tools are increasingly employed to support clinical diagnostics and treatment planning. The development of predictive simulations allows for the evaluation of the effect of changed biomechanical parameters on the human biological system behavior and could become a valuable tool in future clinical decision making. In the first paper, we evaluated the use of the Zero Moment Point as a computationally inexpensive tool to obtain the ground reaction forces (GRFs) for normal human gait. The method was applied on ten healthy subjects walking in a motion analysis laboratory and predicted GRFs are evaluated against the simultaneously measured force plate data. Apart from the antero-posterior forces, GRFs are well-predicted and errors fall within the error ranges from other published methods. The computationally inexpensive method evaluated in this study can reasonably well predict the GRFs for normal human gait without using prior knowledge of common gait kinetics. The second manuscript addresses the complications in the creation and analysis of a posture prediction framework. The fmincon optimization function in MATLAB was used in conjunction with a musculoskeletal model in OpenSim. One clear local minimum was found in the form of a symmetric standing posture but perturbation analyses revealed the presence of many other postural configurations, each representing its own unique local minimum in the feasible parameter space. For human postural stance, this can translate to there being many different ways of standing without actually noticing a difference in the efforts required for these poses. Descriptors: Static optimization, Multibody system, Musculoskeletal model