Abstract
Tremor is rhythmic involuntary oscillatory movement of body parts. There have been attempts to separate tremors due to different extrapyramidal diseases with objective techniques by measuring the acceleration of hands and applying the features of conventional spectral description, peak value and peak frequency of power spectral density (PSD). However, no clear-cut separation has been found with these methods; none of the parameters helps to decide reliably which kind of pathological tremor is present. The task is then twofold: to exploit other PSD features and to apply descriptions extracting new information from existing data. This article shows that the features of this process, based on the application of cumulants and polyspectra, represent different types of tremor and may stand as the basis for recognition between them. The results of numerical experiments are presented and discussed.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
