Noncontact Monitoring and AI‐Driven Stroke Prediction: National Center for Neurological Disorders‐Based Approach Using Smart Beds
In this study, the occurrence of stroke was successfully identified by integrating multimodal temporal data from electronic medical records. Noncontact monitoring of respiration and heart rate offers a promising approach for daily stroke surveillance in home-based populations, particularly for elderly individuals living alone.
Authors
- Rui Li (ORCID: https://orcid.org/0009-0007-2684-1958)
- Xin Wang (ORCID: https://orcid.org/0000-0003-2938-4709)
- Lan Lan
- Ling Guan (ORCID: https://orcid.org/0000-0003-3381-8370)
- Jiawei Luo (ORCID: https://orcid.org/0000-0003-4737-9014)
- Jin Yin
- Yilong Wang (ORCID: https://orcid.org/0000-0002-9575-2170)
Institutions
- University of British Columbia (CA)
- Capital Medical University (CN)
- West China Medical Center of Sichuan University (CN)
- Beijing Tian Tan Hospital (CN)
- National Clinical Research Center for Digestive Diseases (CN)
- Chinese Institute for Brain Research (CN)
Publication Details
- Journal
- Health care science
- Published
- 2025-08-26
- DOI
- https://doi.org/10.1002/hcs2.70034
- Primary Topic
- Acute Ischemic Stroke Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China