Soliton-based single-point pulse wave velocity model: A quantum mechanical approach

Evangelos Piliouras, Taous-Meriem Laleg-Kirati

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Cardiovascular diseases (CVDs) are one of the strongest contributors to mortality rates worldwide. To assess the severity of a clinical situation, various indices of CVD risk have been established, one of them being the arterial stiffness. Arterial stiffness is the quantification of the arterial elasticity. There exist several methodologies to assess the level of arterial stiffness where their non-invasiveness is a matter of great importance. The pulse wave velocity (PWV) is used as an indicator of the arterial stiffness and satisfies the non-invasiveness requirement. Specifically, the carotid-femoral PWV-based method is considered one of the most trustworthy methodology in quantifying the arterial stiffness. This paper proposes a new model for the PWV along with insights on a real scenario implementation. The model utilizes Semi-classical signal analysis (SCSA) as the main signal processing framework to analyze the blood pressure waveform. The proposed model is suggested to be used as an add-on to existing methodologies, bringing the feature of single-point measurement, once a calibration phase has preceded. The use of such a model can eliminate the pulse propagation time-delay, one of the dominant sources of PWV error. Additionally, the single-point measurement paves the way of prolonged PWV monitoring that can reveal new clinical features of the PWV. The model was validated both in a theoretical and data basis, validating its predicted hyperbolic PWV behavior with respect to the SCSA parameters.
Original languageEnglish (US)
Pages (from-to)103188
JournalBiomedical Signal Processing and Control
StatePublished - Oct 20 2021

Bibliographical note

KAUST Repository Item: Exported on 2021-10-22
Acknowledgements: Research reported in this publication was supported by King Abdullah University of Science and Technology. Base Research Fund, (BAS/1/1627-01-01).

ASJC Scopus subject areas

  • Health Informatics
  • Signal Processing


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