Abstract 2308: A Novel Method for Automatic Detection of Atrial Fibrillation Episode for Extremely Long Period of Daily Life Using Pulse Oximetry
Background: Asymptomatic atrial fibrillation (AF) is also a major risk factor for stroke. However, it is difficult to detect asymptomatic AF because of problem in recording ECG for a very long period. We tried to evaluate a new method for detection of AF episode with pulse oximetry which is much easier than Holter monitoring for a very long period.
Method: We recorded pulse waves (PW) using a portable pulse oximeter modified for this study, and ECG for 100 beats simultaneously in 13 AF patients and 11 control sinus rhythm (SR) patients. We measured peak to peak intervals of PW and compared them with the corresponding R-R intervals. Moreover, we calculated each coefficient of variation (CV). We also analysed PW for 1 minute using the pulse oximeter 3 minutes before and after recovery to SR or revert to AF in 6 paroxysmal AF patients. We compared CV in PW (CV-PW) during AF (CV-PW(AF)) with CV-PW during SR (CV-PW(SR)) .
Results: The PW intervals closely correlated with R-R intervals in AF patients(r=0.9784±0.0189). CV-PW also well correlated with CV in ECG (AF: r=0.765, p<0.002, SR: r=0.960, p<0.0001). Similarly to R-R interval analysis, CV-PW was significantly greater in AF patients than controls (p<0.0001). The dispersion of peak to peak intervals of PW during AF were significantly greater than during SR(Figure⇓). CV-PW(AF) was significantly greater than CV-PW(SR) (p<0.001).
Conclusions: These results indicated that pulse oximetry-based CV measurement was unexpectedly accurate and could be much easier to detect even asymptomatic AF, if used for a very long period, than the conventional Holter monitering.