Classification and diagnosis of the parkinson disease by stacked autoencoder

Parkinson disease is neuro-degenerative motion disorder this disease causes voice and speech dysfunctions. Therefore, disease can be diagnosed by determining dysphonia produced by a subject with parkinson diseases. In this paper we have introduced a new classification method of the parkinson disease which is based on the stacked autoencoder. The method is tested with two data sets and results show that the performance of the stacked autoencoder is significantly better than the-state-art-methods.