A pilot study for speech assessment to detect the severity of Parkinson’s disease: An ensemble approach
Dividing the multiclass problem into four binary problems gives the optimum speech features for each class. This pilot study, conducted on a small public dataset, shows the potential of computerized speech analysis using DDK to evaluate the severity of Parkinson's disease voice symptoms.
Authors
- Nemuel Daniel Pah (ORCID: https://orcid.org/0000-0002-0181-3199)
- João Paulo Papa (ORCID: https://orcid.org/0000-0002-6494-7514)
- Quoc Cuong Ngo (ORCID: https://orcid.org/0000-0002-8071-5342)
- Guilherme Camargo de Oliveira (ORCID: https://orcid.org/0000-0002-9698-2445)
- Arissa Yoshida (ORCID: https://orcid.org/0000-0002-6715-4050)
- Dinesh Kumar (ORCID: https://orcid.org/0000-0003-3602-4023)
- N Gomes (ORCID: https://orcid.org/0000-0002-8571-8198)
Institutions
- University of Surabaya (ID)
- MIT University (MK)
- RMIT University (AU)
- Universidade Estadual Paulista (Unesp) (BR)
Publication Details
- Journal
- Computers in Biology and Medicine
- Published
- 2024-12-21
- DOI
- https://doi.org/10.1016/j.compbiomed.2024.109565
- Citations
- 8
- Primary Topic
- Voice and Speech Disorders
- Type
- article
- Field-Weighted Citation Impact
- 2.61
Funders
- Stiftelsen Promobilia
- Fundação de Amparo à Pesquisa do Estado de São Paulo
- Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
- Conselho Nacional de Desenvolvimento Científico e Tecnológico