PD-ADSV: An Automated Diagnosing System Using Voice Signals and Hard Voting Ensemble Method for Parkinson's Disease

2023/04/11 by Paria Ghaheri, Ghaheri, Paria, Ahmadreza Shateri +3
Medicine · #Audio and Speech Processing (eess.AS) #FOS: Computer and information sciences #FOS: Electrical engineering #Machine Learning (cs.LG) #Signal Processing (eess.SP) #Sound (cs.SD) #Voice and Speech Disorders #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.2304.06016

openalex publication_date 2023/04/11 · openalex created_date 2023/04/15 · openalex updated_date 2026/07/28

Abstract

Parkinson's disease (PD) is the most widespread movement condition and the second most common neurodegenerative disorder, following Alzheimer's. Movement symptoms and imaging techniques are the most popular ways to diagnose this disease. However, they are not accurate and fast and may only be accessible to a few people. This study provides an autonomous system, i.e., PD-ADSV, for diagnosing PD based on voice signals, which uses four machine learning classifiers and the hard voting ensemble method to achieve the highest accuracy. PD-ADSV is developed using Python and the Gradio web framework.

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