Parkinson’s Disease Prediction Using Handwritten And Voice Dataset

DOI

10.2991/978-94-6463-858-5_87How to use a DOI?

Keywords

Parkinson’s Disease; Machine Learning; Voice Analysis; Handwriting Analysis; Mutli-Modal Fusion; XGBoost; Random Forest; Ensemble Learning

Abstract

Parkinson’s Disease (PD) is a progressive neurodegenerative condition with motor impairment and vocal deficiency. This work proposes a machine learning-based non-invasive early diagnosis system of PD from speech recordings and handwriting samples. MFCCs, jitter, shimmer, and pitch features were obtained from speech recordings and HOG features from spiral and wave handwriting images. Normalization, PCA, and feature selection were the preprocessing techniques. SMOTE was used to address class imbalance. Random Forest, XGBoost, and Voting Classifier ensemble were trained on the multimodal feature set, which reported the maximum accuracy of 90% by the ensemble. The results demonstrate that multimodal data fusion has a very crucial impact on PD detection and is a promising aid for clinical decision support systems.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Y. Amar Babui
AU  - Ch. Yamini
AU  - G. Narendra
AU  - Sk. Basith Ali
PY  - 2025
DA  - 2025/11/04
TI  - Parkinson’s Disease Prediction Using Handwritten And Voice Dataset
BT  - Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025)
PB  - Atlantis Press
SP  - 1047
EP  - 1061
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-858-5_87
DO  - 10.2991/978-94-6463-858-5_87
ID  - Babui2025
ER  -