A robust ensemble data method for identification of human joint mechanical properties during movement.

This paper describes a perturbation method for the identification of linear time-varying systems with an unknown input (voluntary joint input) using ensemble data. The method separates the unknown input and the perturbation through high-pass filtering and recasts the multi-input single-output system identification into single-input single-output system identification. The method is robust to intertrial variation, and can track changes of system dynamics up to 5 Hz. Analysis and simulation are given for the conditions similar to those for the human arm experiments. Experiments show that mechanical properties of the human elbow joint change with voluntary movement speed and that the mean stiffness with voluntary movement is in the range of the posture and is higher than reported before.