Prediction of posture-dependent tremor by the calculation of the endpoint compliance.

This paper proposes to use the analysis of human mechanical impedance to predict spatial behavior of tremor. Traditional studies have revealed that the variability in force is proportional to the mean level of force generated, which is described as signal dependent noise. The variability in force sometimes generates unintentional and uncontrollable rhythmic muscle movements, called tremor. Tremor appears most commonly on arms and hands due to not only a symptom of a neurological disorder, but also when we tighten our muscles. This study hypothesizes that the posture-dependent tremor at the hand is affected by the mechanical impedance of the arm, which is represented as the endpoint compliance ellipsoid. To verify this hypothesis, we measured the trajectory of the endpoint of the arm by human experiments, and compared the results with the endpoint compliance ellipsoid computationally obtained. The human experiment where the oscillations at the hand are measured revealed that the simulation results well correspond with the human experiments. This suggests that the posture-dependent motion noise is affected by the mechanical impedance of human body.