Research Article
GEN AI Based Parkinson’s Disease Detection
@INPROCEEDINGS{10.4108/eai.28-4-2025.2358057, author={N. Selvakumar and G. Ramesh Kalyan and P. Akshay and K. R. Aravind and K. Arun Das and J. Ashwin}, title={GEN AI Based Parkinson’s Disease Detection}, proceedings={Proceedings of the 4th International Conference on Information Technology, Civil Innovation, Science, and Management, ICITSM 2025, 28-29 April 2025, Tiruchengode, Tamil Nadu, India, Part II}, publisher={EAI}, proceedings_a={ICITSM PART II}, year={2025}, month={10}, keywords={parkinson's disease acoustic features fever voice analysis ai- enhanced individual system clinical features early discovery disease operation}, doi={10.4108/eai.28-4-2025.2358057} }- N. Selvakumar
G. Ramesh Kalyan
P. Akshay
K. R. Aravind
K. Arun Das
J. Ashwin
Year: 2025
GEN AI Based Parkinson’s Disease Detection
ICITSM PART II
EAI
DOI: 10.4108/eai.28-4-2025.2358057
Abstract
Parkinson's disease is a debilitating neurodegenerative disorder that affects millions worldwide, characterized by motor symptoms such as tremors, rigidity, and bradykinesia, as well as non-motor symptoms like speech impairments. This project, Gen AI-Based Parkinson's Disease Detection, introduces an innovative, AI-driven approach to early PD detection using voice analysis, offering a non-invasive, cost-effective, and scalable solution. The system employs a curated dataset of voice recordings from both Parkinson's patients and healthy individuals, which are preprocessed and transformed into visual representations These visual features are then analyzed using advanced machine learning algorithms, including Convolutional Neural Networks (CNNs) and ensemble methods, to classify the presence or absence of Parkinson's disease with high accuracy.
