Identification of parkinson disease patients classification using feed forward technique based on speech signals

Abstract

Parkinson’s disease is a second most Neuro degenerative disease; it is affecting the central nervous system. The people enduring from this disease like passive movement, uncontrollable hand vibrations, imbalance, etc. We present a classification method and focused on speech signals to the identification of Parkinson disease. Because the speech signal is an earlier effect on the Parkinson disease. Here we are using feed forward technique for the classification. Feed forward technique is an artificial neural network which is connected from a unit not a cycle. The newly proposed technique is easy to identify diseased patients and non-diseased patients using speech signals. In that speech signals, certain vowel, words and numbers are used. In this work we provide a brief overview of the area of feed forward technique. We will also discuss speech signals and how it is involved in the technique. The experimental result suggests that the feed forward technique gives best classification accuracy using speech signals.