File:Analysing photoplethysmogram signals.pdf

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Analysing photoplethysmogram signals using statistical modelling and machine learning

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English: Developing models to analyse photoplethysmogram (PPG) signals using statistical modeling or machine learning.

Adapted from: https://doi.org/10.1109/JPROC.2022.3149785

Original files are available here.

Sources: Produced using data from: (i) the Vortal dataset acquired at the finger using a clinical monitor; and (ii) data from the PWDB Database.

(i) P. H. Charlton et al., "Extraction of respiratory signals from the electrocardiogram and photoplethysmogram: Technical and physiological determinants", Physiol. Meas., vol. 38, no. 5, pp. 669-690, 2017.

(ii) P. H. Charlton, J. M. Harana, S. Vennin, Y. Li, P. Chowienczyk and J. Alastruey, "Modeling arterial pulse waves in healthy aging: A database for in silico evaluation of hemodynamics and pulse wave indexes", Amer. J. Physiol.-Heart Circulatory Physiol., vol. 317, no. 5, pp. H1062-H1085, Nov. 2019.
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Source Own work
Author Peterhcharlton

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