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… Click to show full abstract
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 the R–R intervals [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 and p < 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.
               
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