Alignment of R-R interval signals using the circadian heart rate rhythm

Abstract

R-R interval signals that come from different subjects are regularly aligned and averaged according to the horological starting time of the recordings. We argue that the horological time is a faulty alignment criterion and provide evidence in the form of a new alignment method. Our main motivation is that the human heart rate (HR) rhythm follows a circadian cycle, whose pattern can vary among different classes of people. We propose two novel alignment algorithms that consider the HR circadian rhythm, the Puzzle Piece Alignment Algorithm (PPA) and the Event Based Alignment Algorithm (EBA). First, we convert the R-R interval signal into a series of time windows and compute the mean HR per window. Then our algorithms search for matching circadian patterns to align the signals. We conduct experiments using R-R interval signals extracted from two databases in the Physionet Data Bank. Both algorithms are able to align the signals with respect to the circadian rhythmicity of HR. Furthermore, our findings confirm the presence of more than one pattern in the circadian HR rhythm. We suggest an automatic classification of signals according to the three most prominent patterns.