Statistical approach for the detection of motion/noise artifacts in Photoplethysmogram
Abstract
Motion and noise artifacts (MNA) have been a serious obstacle in realizing the potential of Photoplethysmogram (PPG) signals for real-time monitoring of vital signs. We present a statistical approach based on the computation of kurtosis and Shannon Entropy (SE) for the accurate detection of MNA in PPG data. The MNA detection algorithm was verified on multi-site PPG data collected from both laboratory and clinical settings. The accuracy of the fusion of kurtosis and SE metrics for the artifact detection was 99.0%, 94.8% and 93.3% in simultaneously recorded ear, finger and forehead PPGs obtained in a clinical setting, respectively. For laboratory PPG data recorded from a finger with contrived artifacts, the accuracy was 88.8%. It was identified that the measurements from the forehead PPG sensor contained the most artifacts followed by finger and ear. The proposed MNA algorithm can be implemented in real-time as the computation time was 0.14 seconds using Matlab®.
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Selvaraj et al. used kurtosis and Shannon Entropy to determine motion artifacts and achieved an accuracy of 88.8% in a laboratory setting.
“Kurtosis and Shannon Entropy were the measurements used by Selvaraj et al. to determine motion artifacts, and they were able to perform an accuracy of 88.8% in a laboratory setting [174].”
From Sources of inaccuracy in photoplethysmography for continuous cardiovascular monitoring (2021) · cites this paper as [174]
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Sources of inaccuracy in photoplethysmography for continuous cardiovascular monitoring
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- Authors
- Selvaraj, N., Mendelson, Y., Shelley, K. H., Silverman, D. G., & Chon, K. H.
- Affiliations
- Worcester Polytechnic Institute (US)
- Yale University (US)
- Venue
- 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
- Publisher
- IEEE
- Published
- 2011-08
- Volume
- 2011
- Pages
- 4972-4975
- ISSN
- 2375-7477 (ISSN-L)
- OpenAlex
- W2080146198
- Cited by
- 119
- References
- 7
- Citations by year
- 2026: 11 · 2025: 11 · 2024: 13 · 2023: 9 · 2022: 16 · 2021: 14 · 2020: 11 · 2019: 15 · 2018: 5 · 2017: 5 · 2016: 5 · 2015: 2 · 2014: 1 · 2013: 1
- FWCI
- 1.35
- 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
- photoplethysmogram, motion artifact detection, kurtosis, Shannon entropy, vital signs monitoring, real-time monitoring, signal quality assessment
- MeSH terms
- Algorithms, Data Interpretation, Statistical, Diagnosis, Computer-Assisted, Humans, Movement, Oxygen, Sensitivity and Specificity, Reproducibility of Results, Artifacts, Photoplethysmography
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