Multi-modal multi-task deep neural networks for sleep disordered breathing assessment using cardiac and audio signals
Results show that combining cardiac and audio signals can enhance the performance of SDB detection and highlight the potential of multi-modal data fusion for further research in this domain.
Authors
- Sebastiaan Overeem (ORCID: https://orcid.org/0000-0002-6445-9836)
- Xi Long (ORCID: https://orcid.org/0000-0001-9505-1270)
- Pedro Fonseca (ORCID: https://orcid.org/0000-0003-2932-6402)
- Johannes van Dijk (ORCID: https://orcid.org/0000-0001-6188-2973)
- Jiali Xie
Institutions
- Kempenhaeghe (NL)
- Eindhoven University of Technology (NL)
Publication Details
- Journal
- International Journal of Medical Informatics
- Published
- 2025-04-17
- DOI
- https://doi.org/10.1016/j.ijmedinf.2025.105932
- Primary Topic
- Phonocardiography and Auscultation Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Technische Universiteit Eindhoven
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek
- Ministerie van Economische Zaken en Klimaat