Accelerometer-based bed occupancy detection for automatic, non-invasive long-term cough monitoring

Pahar, M. orcid.org/0000-0002-5926-0144, Miranda, I., Diacon, A. orcid.org/0000-0001-8641-6792 et al. (1 more author) (2023) Accelerometer-based bed occupancy detection for automatic, non-invasive long-term cough monitoring. IEEE Access, 11. pp. 30739-30752. ISSN 2169-3536

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Item Type: Article
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© 2023 The Authors. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/

Keywords: Accelerometer; bed occupancy; cough monitoring; long short-term memory (LSTM); machine learning
Dates:
  • Published: 24 March 2023
  • Published (online): 24 March 2023
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 23 Jan 2025 09:27
Last Modified: 23 Jan 2025 09:27
Published Version: https://doi.org/10.1109/access.2023.3261557
Status: Published
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Refereed: Yes
Identification Number: 10.1109/access.2023.3261557
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Sustainable Development Goals:
  • Sustainable Development Goals: Goal 3: Good Health and Well-Being
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