REAL-TIME ESTIMATION OF PATHOLOGICAL TREMOR PARAMETERS IN NEUROPSYHODIAGNOSIS AUTOMATED SYSTEMS
The paper analyzes the existing ideas about the nature and mechanisms of generation of tremor. The two-stage algorithm of estimation of the tremor parameters in real-time is suggested. In the first stage, the algorithm divides the tremor and accompanying arbitrary movements, based on their different distribution in the frequency domain. Furthermore, the evaluation of a movement is removed from the set of kinematic data to generate the estimate of tremor. Then, this estimate is submitted to the second stage, a suspended Fourier transform, to estimate the freque- ncy of tremor, and the Kalman filter, which uses obtained frequencies to estimate the amplitude of tremor.As a result, the algorithm provides high accuracy of the estimate of the amplitude and frequency of tremor. A two-step algorithm was tested on tremograms of patients, suffering from pathological states that cause tremors during the clinical and functional problems. This algorithm can be used in automated systems of neuropsychodiag- nosis, as well as for microsurgical robotics to compensate the hand tremor of a surgeon during operations