Analysis of Heart Rate Variability by Big Data

Abstract

Heart Rate Variability has various indices and many of them correlate with each other, suggesting the presence of common underlying factors determining them. We therefore extracted common factors among indices using big data and analyzed the characteristics of each factor. We performed factor analysis on mean NN, SDNN, rMSSD, VLF, LF, HF, LF / HF, scaling exponent alpha 1, DC, the amplitude of cyclic variation of heart rate, and non-Gaussianity index of lambda 25s obtained from 254,357 subjects with sinus rhythm in ALLSTAR 24-h electrocardiogram big data. Two factors that reflect cardiac vagal function and complexity/irregularity of fluctuation, respectively, were extracted. They showed different relationships from each other with aging and daily physical activities.