Photoplethysmography wave morphology in patients with atrial fibrillation

Most current algorithms for detecting atrial fibrillation (AF) rely on heart rate variability (HRV), and only a few studies analyse the variability of photopletysmography (PPG) waveform. This study aimed to compare morphological features of the PPG curve in patients with AF to those presenting a nor...

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Bibliographic Details
Published in:Physiological measurement 2023-04, Vol.44 (4), p.45001
Main Authors: Basza, Mikołaj, Waląg, Damian, Kowalczyk, Weronika, Bożym, Aleksandra, Ciurla, Michalina, Krzyżanowska, Małgorzata, Maciejewski, Cezary, Bojanowicz, Wojciech, Soliński, Mateusz, Kołtowski, Łukasz
Format: Article
Language:English
Subjects:
algorithm
Algorithms
atrial fibrillation
Atrial Fibrillation - diagnosis
Female
Heart Rate - physiology
heart rate variability
Humans
photoplethysmography
Photoplethysmography - methods
screening
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Summary:Most current algorithms for detecting atrial fibrillation (AF) rely on heart rate variability (HRV), and only a few studies analyse the variability of photopletysmography (PPG) waveform. This study aimed to compare morphological features of the PPG curve in patients with AF to those presenting a normal sinus rhythm (NSR) and evaluate their usefulness in AF detection. 10 min PPG signals were obtained from patients with persistent/paroxysmal AF and NSR. Nine morphological parameters (1/Δ ), Pulse Width [PW], augmentation index [AI], b/a, e/a, [b-e]/a, crest time [CT], inflection point area [IPA], Area and five HRV parameters (heart rate [HR], Shannon entropy [ShE], root mean square of the successive differences [RMSSD], number of pairs of consecutive systolic peaks [ - ] that differ by more than 50 ms [NN50], standard deviation of the - intervals [SDNN]) were calculated. Eighty subjects, including 33 with AF and 47 with NSR were recruited. In univariate analysis five morphological features (1/Δ , < 0.001; b/a, < 0.001; [b-e]/a, < 0.001; CT, = 0.011 and Area, < 0.001) and all HRV parameters ( = 0.01 for HR and < 0.001 for others) were significantly different between the study groups. In the stepwise multivariate model (Area under the curve [AUC] = 0.988 [0.974-1.000]), three morphological parameters (PW, < 0.001; e/a, = 0.011; (b-e)/a, < 0.001) and three of HRV parameters (ShE, = 0.01; NN50, < 0.001, HR, = 0.01) were significant. There are significant differences between AF and NSR, PPG waveform, which are useful in AF detection algorithm. Moreover adding those features to HRV-based algorithms may improve their specificity and sensitivity.
ISSN:0967-3334
1361-6579
DOI:10.1088/1361-6579/acc725