Detection of motion artifacts in photoplethysmographic signals based on time and period domain analysis
Abstract
The presence of motion artifacts in the photoplethysmographic (PPG) signals is one of the major obstacles in the extraction of reliable cardiovascular parameters in real time and continuous monitoring applications. In the current paper we present an algorithm for motion artifact detection, which is based on the analysis of the variations in the time and period domain characteristics of the PPG signal. The extracted features are ranked using a feature selection algorithm (NMIFS) and the best features are used in a Support Vector Machine classification model to distinguish between clean and corrupted sections of the PPG signal. The results achieved by the current algorithm (SE: 0.827 and SP: 0.927) show that both time and especially period domain features play an important role in the discrimination of motion artifacts from clean PPG pulses.
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Coucerio et al. achieved a specificity of 92.7% and a sensitivity of 82.7% using time-domain and period domain analysis of 26 features.
“They were able to achieve a specificity of 92.7% and a sensitivity of 82.7%.”
From Sources of inaccuracy in photoplethysmography for continuous cardiovascular monitoring (2021) · cites this paper as [172]
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Sources of inaccuracy in photoplethysmography for continuous cardiovascular monitoring
Fine, J., Branan, K. L., Rodriguez, A. J., Boonya-ananta, T., Ajmal, Ramella-Roman, J. C., McShane, M. J., & Coté, G. L. (2021) · Biosensors · doi:10.3390/bios11040126 · Cited by 348 · see citing works
- Authors
- Couceiro, R., Carvalho, P., Paiva, R. P., Henriques, J., & Muehlsteff, J.
- Affiliations
- University of Coimbra (PT)
- Philips (Netherlands) (NL)
- Venue
- 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
- Publisher
- IEEE
- Published
- 2012-08
- Volume
- 2012
- Pages
- 2603-2606
- ISSN
- 2375-7477 (ISSN-L)
- OpenAlex
- W2006046606
- Cited by
- 33
- References
- 34
- Citations by year
- 2025: 1 · 2023: 1 · 2022: 1 · 2021: 2 · 2020: 1 · 2019: 3 · 2018: 5 · 2017: 4 · 2016: 4 · 2015: 4 · 2014: 5 · 2013: 2
- FWCI
- 7.56
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (publishedVersion)
- PubMed (publishedVersion)
- 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
- motion artifact detection, photoplethysmography, PPG signal quality, time-domain features, feature selection, support vector machine, cardiovascular monitoring
- MeSH terms
- Adult, Algorithms, Humans, Models, Theoretical, Photoplethysmography, Young Adult, Support Vector Machine
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