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Photoplethysmography signal processing and synthesis
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“This low-pass filtering is a compromise between retaining the original signal features and increasing robustness to noise [10].”
From Wearable Photoplethysmography for Cardiovascular Monitoring (2022) · cites this paper as [10]
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Cited by
Sorted by citations
Wearable Photoplethysmography for Cardiovascular Monitoring
Charlton, P. H., Kyriacou, P. A., Mant, J., Marozas, V., Chowienczyk, P., & Alastruey, J. (2022) · Proceedings of the IEEE · doi:10.1109/jproc.2022.3149785 · Cited by 250
Self-citation
Metadata
- Authors
- Mejía-Mejía, E., Allen, J., Budidha, K., El-Hajj, C., Kyriacou, P. A., & Charlton, P. H.
- Affiliations
- Coventry University (GB)
- University of London (GB)
- Corresponding author
- Allen, John
- Budidha, Karthik
- El-Hajj, Chadi
- Kyriacou, Panicos A.
- Charlton, Peter H.
- Venue
- Photoplethysmography
- Publisher
- Elsevier
- Published
- 2022
- Pages
- 69-146
- OpenAlex
- W3186366455
- Cited by
- 138
- References
- 243
- Citations by year
- 2026: 37 · 2025: 37 · 2024: 37 · 2023: 14 · 2022: 13
- FWCI
- 35.48
- Type
- book chapter
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- Elsevier eBooks (publishedVersion)
- Pure (Coventry University) (submittedVersion)
- Newcastle University ePrints (Newcastle Univesity)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Rate Variability and Autonomic Control
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › ECG Monitoring and Analysis
- Keywords
- photoplethysmography, PPG signal processing, signal preprocessing, time-domain analysis, frequency domain analysis, machine learning, physiological parameter estimation
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