Camera Measurement of Blood Oxygen Saturation
Fuente:
arXiv
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| Autores principales: | , , , , , , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866913716501479424 |
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| author | Tang, Jiankai Liu, Xin McDuff, Daniel Jiang, Zhang Hu, Hongming Zhou, Luxi Nagao, Nodoka Suzuki, Haruta Nagahama, Yuki Li, Wei Ji, Linhong Shi, Yuanchun Nishidate, Izumi Wang, Yuntao |
| author_facet | Tang, Jiankai Liu, Xin McDuff, Daniel Jiang, Zhang Hu, Hongming Zhou, Luxi Nagao, Nodoka Suzuki, Haruta Nagahama, Yuki Li, Wei Ji, Linhong Shi, Yuanchun Nishidate, Izumi Wang, Yuntao |
| contents | Blood oxygen saturation (SpO2) is a crucial vital sign routinely monitored in medical settings. Traditional methods require dedicated contact sensors, limiting accessibility and comfort. This study presents a deep learning framework for contactless SpO2 measurement using an off-the-shelf camera, addressing challenges related to lighting variations and skin tone diversity. We conducted two large-scale studies with diverse participants and evaluated our method against traditional signal processing approaches in intra- and inter-dataset scenarios. Our approach demonstrated consistent accuracy across demographic groups, highlighting the feasibility of camera-based SpO2 monitoring as a scalable and non-invasive tool for remote health assessment. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_01699 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Camera Measurement of Blood Oxygen Saturation Tang, Jiankai Liu, Xin McDuff, Daniel Jiang, Zhang Hu, Hongming Zhou, Luxi Nagao, Nodoka Suzuki, Haruta Nagahama, Yuki Li, Wei Ji, Linhong Shi, Yuanchun Nishidate, Izumi Wang, Yuntao Computational Engineering, Finance, and Science Blood oxygen saturation (SpO2) is a crucial vital sign routinely monitored in medical settings. Traditional methods require dedicated contact sensors, limiting accessibility and comfort. This study presents a deep learning framework for contactless SpO2 measurement using an off-the-shelf camera, addressing challenges related to lighting variations and skin tone diversity. We conducted two large-scale studies with diverse participants and evaluated our method against traditional signal processing approaches in intra- and inter-dataset scenarios. Our approach demonstrated consistent accuracy across demographic groups, highlighting the feasibility of camera-based SpO2 monitoring as a scalable and non-invasive tool for remote health assessment. |
| title | Camera Measurement of Blood Oxygen Saturation |
| topic | Computational Engineering, Finance, and Science |
| url | https://arxiv.org/abs/2503.01699 |