Detection of Parkinson’s Disease by using Voice Analysis

In this paper, we tend to gift associate degree assessment of the sensible worth of existing ancient and nonstandard measures for discriminating healthy individuals from individuals with Parkinson's sickness (PD) by detection speech defect. We tend to introduce a brand new measure of speech defect, pitch amount entropy (PPE), that is powerful to several uncontrollable contradictory effects together with creaky acoustic environments and normal, healthy variations in voice frequency in our project uses feed forward neural network classifier to extend the classification performance with having high sensitivity, specificity and accuracy. Finally, we discover that nonstandard ways are best ready to separate healthy from metal subjects. The chosen nonstandard ways are sturdy to several uncontrollable variations in acoustic setting and individual subjects, and are so likeminded to tele monitoring applications.