Parkinson’s disease is known as the second common neurological disorder after Alzheimer. It influxes several
aspects of human’s functions in which speech disorder is the most prominent. Several researches have been
proposed for diagnosis of PD with voice analysis [5]-[8]. In this paper, a method based on combination of genetic
algorithm and SVM network, for classification of healthy people and people with Parkinson of various
numbers of features, was investigated. Results showed that the highest accuracy was achieved with extracting 4
optimized features: Fhi (Hz), Fho (Hz), jitter (RAP) and shimmer (APQ5). It is observed that there is no major
difference between accuracy of our technique and Reference [7].