A PPG sensor-based multi-feature machine learning approach for wide-range and high-precision S <sub>p</sub> O <sub>2</sub> measurement
- DOI
- 10.1088/1361-6579/aebe9b
- Published
- 2026-11-05
- Container
- Physiological Measurement
- Publisher
- IOP Publishing
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1088/1361-6579/aebe9b,
title = {A PPG sensor-based multi-feature machine learning approach for wide-range and high-precision S
<sub>p</sub>
O
<sub>2</sub>
measurement},
author = {Lian Guo and Zhen Chen and Yijun Li and Haiyang Hu and De He and Zhen Mei and Xuesheng Ma},
year = {2026},
journal = {Physiological Measurement},
doi = {10.1088/1361-6579/aebe9b},
url = {https://doi.org/10.1088/1361-6579/aebe9b}
}RIS
TY - JOUR
TI - A PPG sensor-based multi-feature machine learning approach for wide-range and high-precision S
<sub>p</sub>
O
<sub>2</sub>
measurement
AU - Lian Guo
AU - Zhen Chen
AU - Yijun Li
AU - Haiyang Hu
AU - De He
AU - Zhen Mei
AU - Xuesheng Ma
PY - 2026
JO - Physiological Measurement
DO - 10.1088/1361-6579/aebe9b
UR - https://doi.org/10.1088/1361-6579/aebe9b
ER - APA
Guo, L., Chen, Z., Li, Y., Hu, H., He, D., Mei, Z., & Ma, X. (2026). A PPG sensor-based multi-feature machine learning approach for wide-range and high-precision S <sub>p</sub> O <sub>2</sub> measurement. Physiological Measurement. https://doi.org/10.1088/1361-6579/aebe9b
Source records
- crossref · retrieved 2026-11-10T10:42:07.066Z