2020 Volume Annual58 Issue Abstract Pages 305
Sleep disordered breathing (SDB) has been known to reveal cyclic changes in heart rate in association with apnea/hypopnea, so called cyclic variation of the heart rate (CVHR). We have developed an algorithm for detecting such CVHR from 24-hour Holter electrocardiogram. However, it is difficult to distinguish the change in heart rate whose magnitude is too small to detect as a CVHR from noise. In this study, we focused on the amplitude ratio of the fundamental frequency to the lower and higher frequency area in RR interval trend. We evaluated the new algorithm using 70 data of the Apnea-ECG Database (PhysioNet) and found that (1) the correlation coefficient between AHI and CVHR frequency improved from 0.71 to 0.82, (2) sensitivity and specificity to detect CVHR improved from 86% to 91% and 86% to 93%, respectively. These results suggest that the new algorithm is useful to detect severity of SDB by CVHR.
