THE USE OF INVERSE DYNAMICS SOLUTIONS IN DIRECT DYNAMICS SIMULATIONS

Previous attempts to use inverse dynamics solutions in direct dynamics simulations have failed to replicate the input data of the inverse dy namics problem. Measurement and derivative estimation error, different inverse dynamics and direct dynamics models, and numerical integratio n error have all been suggested as possible causes of inverse dynamics simulation failure. However, using a biomechanical model of the type typically used in gait analysis applications for inverse dynamics calc ulations of joint moments, we produce a direct dynamics simulation tha t exactly matches the measured movement pattern used as input to the i nverse dynamic problem. This example of successful inverse dynamics si mulation demonstrates that although different inverse dynamics and dir ect dynamics models may lead to inverse dynamics simulation failure, m easurement and derivative estimation error do not. In addition, invers e dynamics simulation failure due to numerical integration errors can be avoided. Further, we demonstrate that insufficient control signal d imensionality (i.e., freedom of the control signals to take on differe nt ''shapes''), a previously unrecognized cause of inverse dynamics si mulation failure, will cause inverse dynamics simulation failure even with a perfect model and perfect data, regardless of sampling frequenc y.