A Multilayer Perceptron-based Carotid-to-Femoral Pulse Wave Velocity Estimation using PPG Signal

Mohamed Bahloul, Abderrazak Chahid, Taous-Meriem Laleg-Kirati

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

Abstract

Cardiovascular diseases (CVDs) are the primary cause of death in the world. The development of easy-to-use and non-invasive monitoring CVDs’ diagnosis methods is crucial. Among the key parameters in the cardiovascular system is arterial stiffness. An increase in arterial stiffness is considered a primary risk factor for CVDs. Although arterial stiffness can be assessed non-invasively by measuring the carotid-to-femoral pulse wave velocity (cf−PWV), which is considered as a gold standard for arterial stiffness measurement, the clinical process of assessing this parameter is very intrusive and complicated. This paper investigated the potential of estimating (cf−PWV) from distal photoplethysmogram (PPG) waveforms using regression technique based on a multilayer perceptron. Functionally, PPG offers a simple, reliable, low-cost technique to measure blood volume change and hence assess cardiovascular function. In this work, we identify and select features from the timing fiducial points-based PPG, its first, second, and third derivative waveforms. The in-silico validation shows promising results and satisfactory accuracy. It demonstrates good estimation performances with an R2 (correlation coefficient) around 0.95 and MAPE (mean absolute percentage error) less than 2.22% based on features extracted from PPG at the brachial artery level, an R2 around 0.98 and MAPE less than 1.71% based on features extracted from PPG at the radial artery level and R2 around 0.97 and MAPE less than 1.88% based on features extracted from PPG at the digital artery level.
Original languageEnglish (US)
Title of host publication2021 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI)
PublisherIEEE
ISBN (Print)9781665403580
DOIs
StatePublished - Jul 27 2021

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