File:Analysing photoplethysmogram signals.pdf
Summary
Description |
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. |
Date | |
Source | Own work |
Author | Peterhcharlton |
Licensing
I, the copyright holder of this work, hereby publish it under the following license:
This file is licensed under the Creative Commons Attribution 4.0 International license.
- You are free:
- to share – to copy, distribute and transmit the work
- to remix – to adapt the work
- Under the following conditions:
- attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.