Multiclass-Based Support Vector Machine for Parkinson’s Disease Detection on Speech Data

Author:

Devi Bali,Srivastava Sumit,Verma Vivek Kumar

Publisher

Springer International Publishing

Reference29 articles.

1. Harel, B., Cannizzaro, M., Snyder, P.J.: Variability in fundamental frequency during speech in prodromal and incipient Parkinson’s disease: a longitudinal case study. Brain Cogn. 56(1), 24–29 (2004)

2. Little, M.A., et al.: Suitability of dysphonia measurements for telemonitoring of Parkinson’s disease. IEEE Trans. Biomed. Eng. 56(4), 1015–1022 (2009)

3. Singh, N., Pillay, V., Choonara, Y.E.: Advances in the treatment of Parkinson’s disease. Prog. Neurobiol. 81(1), 29–44 (2007)

4. Parkinson’s Disease: National clinical guideline for diagnosis and management in primary and secondary care. Nat. Collaborating Centre Chronic Conditions, London, U.K. (2006)

5. Sriram, T.V.S., Rao, M.V., Narayana, G.V.S., Kaladhar, D.S.V.G.K., Vital, T.P.R.: Intelligent Parkinson disease prediction using machine learning algorithms. Int. J. Eng. Innov. Technol. (IJEIT) 3(3) (Sep 2013)

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