Exploring the power of photoplethysmogram matrix for atrial fibrillation detection with integrated explainability

Author:

Fuster-Barceló Caterina,Guerrero-López AlejandroORCID,Camara Carmen,Peris-Lopez PedroORCID

Funder

European Regional Development Fund

Spain Ministry of Science Innovation and Universities

Comunidad de Madrid

Publisher

Elsevier BV

Reference59 articles.

1. A deep learning approach for atrial fibrillation classification using multi-feature time series data from ECG and PPG;Aldughayfiq;Diagnostics,2023

2. Atrial fibrillation detection from raw photoplethysmography waveforms: A deep learning application;Aschbacher;Heart Rhythm O2,2020

3. Sensitivity and specificity of wearables for atrial fibrillation in elderly populations: A systematic review;Babar;Curr. Cardiol. Rep.,2023

4. Atrial fibrillation detection in icu patients: A pilot study on mimic iii data;Bashar,2019

5. Novel density Poincaré plot based machine learning method to detect atrial fibrillation from premature atrial/ventricular contractions;Bashar;IEEE Trans. Biomed. Eng.,2020

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