In this application, 3D electromagnetic sensors have been integrated into a data-glove to accurately model and capture the motion of the human hand. By modelling the movement of the human hand, this system has been shown to accurately measure the rest tremor evident in subjects with Parkinson's disease. It was found that 11 sensors were sufficient to model the human hand, including all the phalanges. A capture rate of 10 measurements per 1 s was achieved. A discrete Fourier analysis has been applied to extract the tremor frequency from the sensor data time series. Further an analysis of the instantaneous speed of hand motion has been used to extract clinically significant diagnosis. The technique described is seen to provide an objective and quantitative method for the analysis of clinic conditions such as Parkinson's disease (PD) and essential tremor (ET) as a way to asscss the eflect of therapeutic interventions.
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