Detection of cyclic sleep phenomena using instantaneous heart rate.

Abstract The development of the Heart Beat Domain and the Fourier transform of the Heart Beat Domain (which we call the Beatquency Domain) has provided new and useful tools for the quantitative analysis of sleep level patterns. This method of analysis has produced remarkable intersubject as well as intra-subject consistency and the only physiologic parameter required in the analysis is beat-by-beat heart rate. This analytical tool was designed to aid in the detection of sleep cycles, or more specifically, the rhythmic transitions from REM+ (awake Stages 1 and REM combined) to NREM (Stage 2, 3 and 4 combined) over a normal night of sleep. Employing this method on minute-by-minute sleep recordings from 9 normal sleep subjects, 2 complete nights each, we were able to distinguish between the REM+ and NREM stages with an average accuracy of approximately 80%. Considering that beat-by-beat heart rate was our only criteria, we felt that the algorithm performed with significant success.