Work

Parkinson's Disease Speech Classification Using 1D Convolutional Neural Networks

Year: 2024

Type: article

Abstract: Parkinson's Disease (PD) is a neurodegenerative disorder caused by a lack of dopamine secretion. Both motor and non-motor activities of Parkinson's patients are affected. This study proposes a method for Parkinson's disease audio feature classification based on Convolutional Neural Networks (CNN). By extracting features from the speech signals of Parkinson's patients, and leveraging the powerful feature extraction and classification capabilities of CNNs, an efficient diagnosis of Parkinson's disease can be achieved. To evaluate the performance of the proposed method, experiments were conducted on two datasets, achieving accuracy rates of 100% and 92.86%, respectively.

Source: Frontiers in Computing and Intelligent Systems

DOI: 10.54097/agw6qc09

Authors: Zhen Yue, Haiyang Wang

Institutions: Jilin University of Chemical Technology, BaiCheng Normal University

Language: English

Topic: Voice and Speech Disorders

Subfield: Physiology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: diamond

Funder: People's Government of Jilin Province