Document Type : Full Research Paper


1 M.Sc. Student, Department of Electrical Engineering, K. N. Toosi University of Technology, Tehran, Iran

2 Assistant Professor, Department of Electrical Engineering, K. N. Toosi University of Technology, Tehran, Iran



After Alzheimer, Parkinson's disease is known as the most common malignant disease of the nervous system. One of the common obstacles of this disease is the expansion of speech disorders. Since the speech production in humans is made by combination of vibration of the vocal cords (phonatory section) and then passage through the resonator in vocal tract (articulatory section), it is expected that both of these sections to be impaired. In this study, by using a noninvasive method, it is intended to diagnose Parkinson's disease from speech signal of each subject; for this purpose, using 3 sustain vowels in Persian language recorded from 48 people (27 people with Parkinson's disease and 21 healthy people), it has been evaluated to assess the extent of damage to both phonatory and articulatory sections. The phonatory model can include features such as jitter, shimmer, fundamental frequencies, opening and closing cycling time of the glottal pulses. On the other hand, for the articulatory section, features such as first, second, and third formmants, zero crossing rates, MFFCs, and LPC are investigated. In this study, 38 feature categories were extracted and four statistical parameters of mean, standard deviation, skewness and kurtosis were calculated. Genetic Algorithm was used to identify the optimum features. Then, using the SVM, KNN and the Decision Tree classifiers, the optimum extracted features are classified to determine whether a person is patient or healthy. Finally for the main aim of this study, the results of both phonatory and articulatory sections were compared and challenged. The results of this study showed that phonatory features with accuracy of 96.1±1.2% were more useful than articulatory section in diagnosing of Parkinson. Also it was proved that vowel /u/ has more significant role in the diagnosis of Parkinson's disease compared to other vowels by accuracy of 97.6%.


Main Subjects

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