Robust Assessment of Photoplethysmogram Signal Quality in the Presence of Atrial Fibrillation

Tania Pereira, Kais Gadhoumi, Mitchell Ma, Rene Colorado, Kevin J. Keenan, Karl Meisel, Xiao Hu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations


A great deal of algorithms currently available to assess the quality of photoplethysmogram (PPG) signals is based on the similarity between pulses to derive signal quality indices. This approach has limitations when pulse morphology become variable due to the presence of some arrhythmia as in the case of atrial fibrillation (AFib). AFib is a heart arrhythmia characterized in the electrocardiogram mainly by an irregular irregularity. This arrhythmicity is reflected on PPG pulses by the presence of non-uniform pulses and poses challenges in the evaluation of the signal quality. In this work, we first test the performance of few algorithms from the body of methods reported in literature using a dataset of PPG records with AFib, and demonstrate their limitation. Second, we present a novel SVM-based classifier for PPG quality assessment in 30s-long segments of PPG records extracted from pulse oximetry data of 13 stroke patients admitted to the UCSF medical center neuro ICU. 40 time-domain, frequency domain and non-linear features were extracted from all segments. Using an independent test set, the classifier reached a 0.94 accuracy, 0.95 sensitivity and 0.91 specificity. These results demonstrate the robustness of the proposed method in properly evaluating PPG signal quality in the presence of atrial fibrillation.

Original languageEnglish (US)
Title of host publicationComputing in Cardiology Conference, CinC 2018
PublisherIEEE Computer Society
ISBN (Electronic)9781728109589
StatePublished - Sep 2018
Externally publishedYes
Event45th Computing in Cardiology Conference, CinC 2018 - Maastricht, Netherlands
Duration: Sep 23 2018Sep 26 2018

Publication series

NameComputing in Cardiology
ISSN (Print)2325-8861
ISSN (Electronic)2325-887X


Conference45th Computing in Cardiology Conference, CinC 2018

ASJC Scopus subject areas

  • Computer Science(all)
  • Cardiology and Cardiovascular Medicine


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