Patch-Type Heart Rate Variability Analysis with Artificial Intelligence for Detection of Obstructive Sleep Apnea
The patch-type HRV analyzer with AI analysis provides accurate, low-interference OSA screening, suitable for large-scale clinical and home use.
Authors
- Ying-Shuo Hsu
- Ofer Jacobowitz (ORCID: https://orcid.org/0000-0003-2290-0520)
- Cheng-Han Chou (ORCID: https://orcid.org/0009-0005-5862-6449)
- Yu-En Kuo
- Chia-Mo Lin
- Yi Chang
- Yu-Cheng Lin
- Cheryl Yang
- Terry Kuo
- Shih-Chieh Lo
- Mei-Chun Chou
Institutions
- Fu Jen Catholic University (TW)
- Ministry of Health and Welfare (KR)
- National Yang Ming Chiao Tung University (TW)
- ENT and Allergy (US)
- Taipei City Hospital (TW)
- Electronics Testing Center (TW)
- Memorial Hospital (US)
Publication Details
- Journal
- Nature and Science of Sleep
- Published
- 2026-02-01
- DOI
- https://doi.org/10.2147/nss.s568569
- Primary Topic
- Obstructive Sleep Apnea Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Shanghai Educational Development Foundation
- Shin Kong Wu Ho-Su Memorial Hospital
- National Science and Technology Council