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Home / Archives / Volume-6 / Issue-2 / Article-4

Volume - 6 | Issue - 2 | june 2024

Prediction of Parkinson’s Disease using Handwriting Analysis and Voice Dataset- A Review
Himaja G  , Nagarathna C R, Jayasri A, Kundan K M
Pages: 118-132
Cite this article
G, Himaja, Nagarathna C R, Jayasri A, and Kundan K M. "Prediction of Parkinson’s Disease using Handwriting Analysis and Voice Dataset- A Review." Journal of Innovative Image Processing 6, no. 2 (2024): 118-132
Published
22 May, 2024
Abstract

Parkinson's disease is a common neurological movement illness that impairs motor coordination. Parkinson’s disease (PD) symptoms and severity, however, differ from person to person. By extracting insights, trends, and possibilities from the data, data research can be utilized to uncover solutions to problems in medical research by utilizing data, machine learning algorithms, and cutting-edge technology. Among the less evident early signs of Parkinson's disease are tremors, muscle stiffness, imbalance problems, and difficulty walking. There is currently no test to detect the illness early on, when symptoms might not be evident. However, handwriting and hand- drawn subjects in humans have been linked to PD. In addition to being a useful tool for PD prediction, speech smearing functions as an early warning system. In order to control symptoms and maybe halt the disease's progression, early detection makes it possible to organize treatments and intervene promptly. For those with Parkinson's disease, early application of certain therapies and medications can extend survival and enhance quality of life.

Keywords

PD Hand Writing Voice Dataset Machine Learning Methods Early Diagnosis

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