Prediction of Ankle Brachial Index with Photoplethysmography Using Convolutional Long Short Term Memory
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Deep learning has recently been used to develop a model for assessing arterial stiffness from the PPG.
“deep learning has recently been used to develop a model for assessing arterial stiffness from the PPG”
From Wearable Photoplethysmography for Cardiovascular Monitoring (2022) · cites this paper as [173]
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Wearable Photoplethysmography for Cardiovascular Monitoring
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Wearable Photoplethysmography for Cardiovascular Monitoring.
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An XGBoost-based model for assessment of aortic stiffness from wrist photoplethysmogram
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- Authors
- Lee, J. J., Heo, J. H., Han, J. H., Kim, B. R., Gwon, H. Y., & Yoon, Y. R.
- Affiliations
- Yonsei University (KR)
- Corresponding author
- Yoon, Young Ro
- Venue
- Journal of Medical and Biological Engineering
- Published
- 2020-02-18
- Volume
- 40
- Issue
- 2
- Pages
- 282-291
- ISSN
- 1609-0985 (ISSN-L)
- 2199-4757
- OpenAlex
- W3008239069
- Cited by
- 11
- References
- 46
- Citations by year
- 2025: 1 · 2024: 1 · 2022: 5 · 2021: 4
- FWCI
- 0.71
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Medical and Biological Engineering (publishedVersion)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Health and Disease Prevention
- Keywords
- ankle-brachial index, photoplethysmography, convolutional long short-term memory, cardiovascular disease detection, arterial disease, non-invasive blood pressure measurement, deep learning classification, primary care
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