Predicting sleep based on physical activity, light exposure, and Heart rate variability data using wearable devices
The results show that the performance of the sleep prediction models improved by increasing the data amount and adding HRV data. Further studies targeting insomnia patients and applied researches on non-pharmacological insomnia treatment are needed.
Authors
- Hyun Duck Hwang
- Kyungmee Park (ORCID: https://orcid.org/0000-0002-2416-2683)
- Eun Lee (ORCID: https://orcid.org/0000-0002-7462-0144)
- Do Hoon Yoon
- Eunchae Choi
- Chang‐Hee Lee (ORCID: https://orcid.org/0000-0002-7906-6517)
- Sang Eun Lee
Institutions
- Yonsei University (KR)
- Severance Hospital (KR)
- Yonsei University Health System (KR)
- Chung-Ang University (KR)
Publication Details
- Journal
- Annals of Medicine
- Published
- 2024-09-19
- DOI
- https://doi.org/10.1080/07853890.2024.2405077
- Citations
- 5
- Primary Topic
- Heart Rate Variability and Autonomic Control
- Type
- article
- Field-Weighted Citation Impact
- 2.01
Funders
- National Research Foundation
- National Research Foundation of Korea