Garcia JMV, Bahloul MA, Laleg-Kirati TM. A Multiple Linear Regression Model for Carotid-to-Femoral Pulse Wave Velocity Estimation Based on Schrodinger Spectrum Characterization.
ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2022;
2022:143-147. [PMID:
36085988 DOI:
10.1109/embc48229.2022.9871031]
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Abstract
In this paper, a multiple linear regression model for estimating the Carotid-to-femoral pulse wave velocity (cf-PWV) from a single non-invasive peripheral pulse wave, namely blood pressure or photoplethysmography, is proposed. The training and testing datasets were extracted from in-silico, publicly available, pulse waves and hemodynamics data. The proposed model relies on a preprocessing and features extraction steps, which are performed using a semi-classical signal analysis (SCSA) method. The obtained results provide more evidence for the feasibility of machine learning and the SCSA method as a smart tool for the efficient assessment of the cf-PWV.
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