Cited by 33Non-Invasive Vital Sign MonitoringHeart Rate Variability and Autonomic ControlECG Monitoring and Analysis

Detection of motion artifacts in photoplethysmographic signals based on time and period domain analysis

Couceiro, R., Carvalho, P., Paiva, R. P., Henriques, J., Muehlsteff, J.·2012·2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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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Crossref · 10.1109/embc.2012.6346497

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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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