Cough sound spectro-temporal analysis and automated detection using Vision Transformers
Vision Transformers with optimised spectrogram preprocessing enable accurate, scalable cough detection across diverse populations, performing comparably to popular convolutional neural networks on a larger, more diverse, and more challenging dataset. These findings support the use of ViT-based systems for objective, automated cough monitoring in clinical practice.
Authors
- John A. Smith (ORCID: https://orcid.org/0000-0001-8837-4928)
- Patrick Gaydecki (ORCID: https://orcid.org/0000-0002-8180-6836)
- K.P. Tan (ORCID: https://orcid.org/0000-0002-2729-3312)
Institutions
- University of Manchester (GB)
- Manchester University NHS Foundation Trust (GB)
- Institute of Infection and Immunity (CA)
Publication Details
- Journal
- Digital Health
- Published
- 2025-05-01
- DOI
- https://doi.org/10.1177/20552076251394623
- Primary Topic
- Respiratory and Cough-Related Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00