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Neural network based prediction of parkinsonian hand tremor using surface electromyography

Neural network based prediction of parkinsonian hand tremor using surface electromyography Tremor is unwanted movement of body part. Tremor model estimations are employed in intelligent tremor prediction and compensation scheme. One way of modelling Parkinsonian tremor is the analysis-synthesis approach, in which theoretically guessed properties of the individual parts are combined mathematically. However, this approach has limited success in predicting certain tremor characteristics. The second method uses different measures of the tremor (frequency, amplitude, effect of loading, etc.) in order to infer the underlying phenomena. Electromyogram (EMG) being a related physiological event, is included in the parameter domain, which helps to estimate certain tremor characteristics. An artificial neural network based study of tremor in Parkinson’s disease and its compensation technique is discussed here. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Signal and Imaging Systems Engineering Inderscience Publishers

Neural network based prediction of parkinsonian hand tremor using surface electromyography

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd. All rights reserved
ISSN
1748-0698
eISSN
1748-0701
DOI
10.1504/IJSISE.2012.050316
Publisher site
See Article on Publisher Site

Abstract

Tremor is unwanted movement of body part. Tremor model estimations are employed in intelligent tremor prediction and compensation scheme. One way of modelling Parkinsonian tremor is the analysis-synthesis approach, in which theoretically guessed properties of the individual parts are combined mathematically. However, this approach has limited success in predicting certain tremor characteristics. The second method uses different measures of the tremor (frequency, amplitude, effect of loading, etc.) in order to infer the underlying phenomena. Electromyogram (EMG) being a related physiological event, is included in the parameter domain, which helps to estimate certain tremor characteristics. An artificial neural network based study of tremor in Parkinson’s disease and its compensation technique is discussed here.

Journal

International Journal of Signal and Imaging Systems EngineeringInderscience Publishers

Published: Jan 1, 2012

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