Photoplethysmography wave morphology in patients with atrial fibrillation

被引:3
|
作者
Basza, Mikolaj [1 ]
Walag, Damian [2 ]
Kowalczyk, Weronika [3 ]
Bozym, Aleksandra [3 ]
Ciurla, Michalina [3 ]
Krzyzanowska, Malgorzata [3 ]
Maciejewski, Cezary [3 ]
Bojanowicz, Wojciech [1 ]
Solinski, Mateusz [4 ]
Koltowski, Lukasz [3 ]
机构
[1] Med Univ Silesia, Katowice, Silesia, Poland
[2] Warsaw Univ Technol, Fac Phys, PL-00662 Warsaw, Poland
[3] Med Univ Warsaw, Chair & Dept Cardiol 1, Warsaw, Poland
[4] Kings Coll London, Fac Life Sci & Med, Sch Biomed Engn & Imaging Sci, London WC2R 2LS, England
关键词
algorithm; atrial fibrillation; heart rate variability; photoplethysmography; screening; OUTCOMES;
D O I
10.1088/1361-6579/acc725
中图分类号
Q6 [生物物理学];
学科分类号
071011 ;
摘要
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/Delta T), 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/Delta T, 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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页数:10
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