Identification of Parkinson’s Disease in Patients using Vocal Features

Authors

  • K. Deepa
  • Senthamilselvi ‎
  • Jansirani Sankar
  • A. Arthi Krithika

Abstract

Parkinson’s disease (PD) is a nervous system disorder and it is progressive neurodegenerative which affects multiple motor and non-motor characteristics like movement. The early stage of the Parkinson’s disease is face vocal impairments The recent research area or study in Parkinson’s disease based on the diagnosis systems based on vocal disorders. To deal with, this paper proposes a new framework that uses Support Vector Machine (SVM). The work of SVM is for classification of Parkinson’s disease with the feature like set of vocal (i.e.,) speech. Input given to the SVM has different feature set as combined. The training dataset taken from UCI Machine Learning repository for the Proposed model. The performance of model is accessed based on accuracy and sensitivity. The proposed model gives better result to distinguish between healthy person with PD patients and also boost up the discriminative power of the classifier.

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Published

2020-02-19

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Section

Articles