Automatic Classification of Parkinson’s Disease Through the Fusion of Sustained Vowel Descriptors

Sahar Hafsi, Sahar Hafsi, Linda Marrakchi-Kacem, Farouk Mhamdi, Farouk Mhamdi, Sonia Djaziri-Larbi

2025

Abstract

Voice disorders are early symptoms of Parkinson’s disease (PD) and have motivated the use of speech as a biomarker for PD. In particular, dysfunctional phonation of sustained vowels has gained increasing interest in the automatic classification of PD. However, most studies typically focus on a single vowel to extract disease descriptors, which may limit the detection of subtle vocal alterations present in PD patients. The main objective of this study is to investigate the contribution of analyzing two vowels for the automatic classification of PD, as opposed to relying on a single vowel. In this paper, we propose a novel automatic approach to identify dysphonia in PD by combining speech descriptors extracted from two sustained vowels, /a:/ and /i:/. This fusion enables the detection of a broader range of vocal alterations, thereby increasing the robustness of the predictive models. A preprocessing of the speech signals was performed, followed by feature selection using the ReliefF algorithm. Then, a robust nested cross-validation was applied to evaluate the models. The results clearly indicate higher classification performance when combining the descriptors of /a:/ and /i:/.

Paper Citation

in Harvard Style

Hafsi S., Marrakchi-Kacem L., Mhamdi F. and Djaziri-Larbi S. (2025). Automatic Classification of Parkinson’s Disease Through the Fusion of Sustained Vowel Descriptors. In Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOSIGNALS; ISBN 978-989-758-731-3, SciTePress, pages 878-885. DOI: 10.5220/0013156100003911

in Bibtex Style

@conference{biosignals25,
author={Sahar Hafsi and Linda Marrakchi-Kacem and Farouk Mhamdi and Sonia Djaziri-Larbi},
title={Automatic Classification of Parkinson’s Disease Through the Fusion of Sustained Vowel Descriptors},
booktitle={Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOSIGNALS},
year={2025},
pages={878-885},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013156100003911},
isbn={978-989-758-731-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOSIGNALS
TI - Automatic Classification of Parkinson’s Disease Through the Fusion of Sustained Vowel Descriptors
SN - 978-989-758-731-3
AU - Hafsi S.
AU - Marrakchi-Kacem L.
AU - Mhamdi F.
AU - Djaziri-Larbi S.
PY - 2025
SP - 878
EP - 885
DO - 10.5220/0013156100003911
PB - SciTePress