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. 2012:2012:4927-30.
doi: 10.1109/EMBC.2012.6347040.

Dynamic SVM detection of tremor and dyskinesia during unscripted and unconstrained activities

Bryan T Cole  1 , Pinar Ozdemir, S Hamid Nawab
Affiliations

Dynamic SVM detection of tremor and dyskinesia during unscripted and unconstrained activities

Bryan T Cole et al. Annu Int Conf IEEE Eng Med Biol Soc. 2012.

Abstract

In this paper, we report an experimental comparison of dynamic support vector machines (SVMs) to dynamic neural networks (DNNs) in the context of a system for detecting dyskinesia and tremor in Parkinson's disease (PD) patients wearing accelerometer (ACC) and surface electromyographic (sEMG) sensors while performing unscripted and unconstrained activities of daily living. These results indicate that SVMs and DNNs of comparable computational complexities yield approximately identical performance levels when using an identical set of input features.

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