Photoplethysmography wave morphology in patients with atrial fibrillation

Objective.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.Approach.10 min PPG signals were obtained from patients with persistent/paroxysmal AF and NSR. Nine morphological parameters (1/ΔT), 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 [R-R] that differ by more than 50 ms [NN50], standard deviation of theR-Rintervals [SDNN]) were calculated.Main results.Eighty subjects, including 33 with AF and 47 with NSR were recruited. In univariate analysis five morphological features (1/ΔT,p< 0.001; b/a,p< 0.001; [b-e]/a,p< 0.001; CT,p= 0.011 and Area,p< 0.001) and all HRV parameters (p= 0.01 for HR andp< 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,p< 0.001; e/a,p= 0.011; (b-e)/a,p< 0.001) and three of HRV parameters (ShE,p= 0.01; NN50,p< 0.001, HR,p= 0.01) were significant.Significance.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.