PaperarXiv:2508.02689
On Improving PPG-Based Sleep Staging: A Pilot Study
arXiv preprint (eess.SP, cs.LG)
(opens in a new tab)Wang, Jiawei et al., "On Improving PPG-Based Sleep Staging: A Pilot Study", arXiv:2508.02689, CC BY 4.0
TL;DR
Sleep monitoring through accessible wearable technology is crucial to improving well-being in ubiquitous computing. Although photoplethysmography(PPG) sensors are widely adopted in consumer devices, achieving consistently reliable sleep staging using PPG alone remains a non-trivial challenge.
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Abstract
Sleep monitoring through accessible wearable technology is crucial to improving well-being in ubiquitous computing. Although photoplethysmography(PPG) sensors are widely adopted in consumer devices, achieving consistently reliable sleep staging using PPG alone remains a non-trivial challenge. In this work, we explore multiple strategies to enhance the performance of PPG-based sleep staging. Specifically, we compare conventional single-stream model with dual-stream cross-attention strategies, based on which complementary information can be learned via PPG and PPG-derived modalities such as augmented PPG or synthetic ECG. To study the effectiveness of the aforementioned approaches in four-stage sleep monitoring task, we conducted experiments on the world's largest sleep staging dataset, i.e., the Multi-Ethnic Study of Atherosclerosis(MESA). We found that substantial performance gain can be achieved by combining PPG and its auxiliary information under the dual-stream cross-attention architecture. Source code of this project can be found at https://github.com/DavyWJW/sleep-staging-models
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APA
Wang, J., Guan, Y., Chen, C., Zhou, L., Yang, L. T., & Gu, S. (2025). On Improving PPG-Based Sleep Staging: A Pilot Study. arXiv preprint. https://doi.org/10.48550/arXiv.2508.02689
BibTeX
@misc{wang2025improving,
title = {{On Improving PPG-Based Sleep Staging: A Pilot Study}},
author = {Wang, Jiawei and Guan, Yu and Chen, Chen and Zhou, Ligang and Yang, Laurence T. and Gu, Sai},
year = {2025},
howpublished = {arXiv preprint},
doi = {10.48550/arXiv.2508.02689},
eprint = {2508.02689},
archivePrefix = {arXiv}
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