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Frequency Analysis of Handwriting for Diagnosis of Parkinson’s Disease

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  • Sana Delavari

    (Biomedical Engineering Department, Science and Research Branch, Islamic Azad University, Tehran, Iran)

Abstract

Parkinson’s disease (PD) is one of the most common diseases which involves the central nervous system. In this disease, certain regions of the brain lose their ability to produce dopamine (one of the nerve carriers). The definite diagnosis of PD may occur several years after the early stages, so it is tried to find a way to diagnose PD in the early stages. Diagnosis of PD before it causes irreversible damage to the brain can significantly impact disease control. In this project, the different handwriting records of healthy people and those with PD under frequency behaviours were compared. The various analysis in different time frequencies and extracting different features to determine the accuracy of the diagnosis of PD in early stages were performed. It is tried to differentiate between various levels of PD. The amount of mean and standard deviation for accuracy is 75.78 and 3.29, for specificity is 74.91 and 3.91, and for sensitivity is 76.78 and 4.49. It shows that the system will report two classes of healthy people and people with PD with high accuracy.

Suggested Citation

  • Sana Delavari, 2020. "Frequency Analysis of Handwriting for Diagnosis of Parkinson’s Disease," Technium, Technium Science, vol. 2(6), pages 96-102, August.
    • Handle: RePEc:tec:techni:ojs:1507
    DOI: 10.47577/technium.v2i6.1507
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