Analysis of different uncertainties in the inverse dynamic analysis of human gait

Inverse dynamics techniques are used in gait analysis to calculate the net joint torques that the musculo-skeletal system produces during human locomotion. Errors present in the input data may affect significantly the results of the inverse dynamics problem. In this work we analyze the influence on the results of errors in the body segment parameter estimation, in the kinematic data processing and in the ground reaction force measurement. Those errors are unavoidable when analyzing human gait and have been modeled in different ways depending on their nature. The paper presents detailed results and discussions to quantify the effects of the above errors on the inverse dynamic analysis. Simulations show that the results are more sensitive to errors in ground contact forces and in kinematic data processing than in body inertial parameters.

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► A 16-DoF model of the body is used to study the inverse dynamics of human gait.
► The kinematic consistency is ensured by means of an optimization approach.
► Uncertainties in BSP have a little effect in the results of the inverse dynamics.
► The results are sensitive to inaccuracies in the process to obtain consistent data.
► The results are also sensitive to errors in the force plate measurements.