Proceedings of the 4th International Conference on Informatics, Technology and Engineering 2023 (InCITE 2023)

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Analyzing the Probability Density Distribution of Sustained Phoneme Voice Features in the PC-GITA Dataset for Parkinson’s Disease Identification

Authors
Nemuel Daniel Pah1, *, Veronica Indrawati1, Dinesh K. Kumar2, Mohammod A. Motin3
1Universitas Surabaya, Surabaya, 60293, Indonesia
2RMIT University, Melbourne, VIC, 3000, Australia
3Rajshahi University of Engineering and Technology, Rajshahi, 6204, Bangladesh
*Corresponding author. Email: nemuelpah@staff.ubaya.ac.id
Corresponding Author
Nemuel Daniel Pah
Available Online 19 November 2023.
DOI
10.2991/978-94-6463-288-0_53How to use a DOI?
Keywords
Parkinsonian dysarthria; voice features; probability density distribution
Abstract

One of the possibilities for developing computerized diagnostic tools for Parkinson’s disease (PD) is to utilize the voice change known as Parkinsonian dysarthria. Voice features extracted from sustained phonemes have been statistically investigated as parameters for this purpose. However, the commonly used statistical presentation methods often obscure interpretations. This paper introduces an alternative approach using probability density distribution analysis to analyze voice features. The analysis was applied to recordings of sustained phonemes from the PC-GITA dataset. The findings reveal a significant overlap between the distributions of PD and healthy subjects (HC), with PD features exhibiting a wider distribution compared to HC. This result suggests the potential use of these features to identify PD, but it should be noted that a considerable number of PD cases may have voice features similar to HC.

Copyright
© 2023 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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Volume Title
Proceedings of the 4th International Conference on Informatics, Technology and Engineering 2023 (InCITE 2023)
Series
Atlantis Highlights in Engineering
Publication Date
19 November 2023
ISBN
978-94-6463-288-0
ISSN
2589-4943
DOI
10.2991/978-94-6463-288-0_53How to use a DOI?
Copyright
© 2023 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.

Cite this article

risenwbib
TY  - CONF
AU  - Nemuel Daniel Pah
AU  - Veronica Indrawati
AU  - Dinesh K. Kumar
AU  - Mohammod A. Motin
PY  - 2023
DA  - 2023/11/19
TI  - Analyzing the Probability Density Distribution of Sustained Phoneme Voice Features in the PC-GITA Dataset for Parkinson’s Disease Identification
BT  - Proceedings of the 4th International Conference on Informatics, Technology and Engineering 2023 (InCITE 2023)
PB  - Atlantis Press
SP  - 640
EP  - 649
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-288-0_53
DO  - 10.2991/978-94-6463-288-0_53
ID  - Pah2023
ER  -