Parkinson's disease detection using spectrogram-based multi-model feature fusion networks
The fusion of multi-model features more effectively captures subtle pathological signatures in PD speech, overcoming the limitations of single models. This method provides a reliable, low-cost, and non-invasive tool for auxiliary PD diagnosis, with significant potential for clinical application. The code is available at https://github.com/lvrongfu/pjs.
Authors
- Wenna Chen (ORCID: https://orcid.org/0000-0003-2543-8271)
- Xiangyu Chen (ORCID: https://orcid.org/0000-0002-3618-5954)
- Hao Wang (ORCID: https://orcid.org/0009-0009-9189-2625)
- Xiaowei Du
- Ganqin Du (ORCID: https://orcid.org/0000-0001-9097-2505)
- Jincan Zhang (ORCID: https://orcid.org/0000-0002-8317-764X)
- Rongfu Lv (ORCID: https://orcid.org/0009-0008-9709-2613)
Institutions
- Henan University of Science and Technology (CN)
- First Affiliated Hospital of Henan University of Science and Technology (CN)
Publication Details
- Journal
- Frontiers in Neurology
- Published
- 2025-11-05
- DOI
- https://doi.org/10.3389/fneur.2025.1706317
- Primary Topic
- Voice and Speech Disorders
- Type
- article
- Field-Weighted Citation Impact
- 0.00