Instantaneous monitoring of sleep fragmentation by point process heart rate variability and respiratory dynamics

Abstract

We present a novel, automatic point-process approach that is able to provide continuous, instantaneous estimates of heart rate variability (HRV) and respiratory sinus arrhythmia (RSA) in long duration data recordings such as those during an entire night of sleep. We analyze subjects with and without sleep apnea who underwent diagnostic polysomnography. The proposed algorithm is able to quantify multi-scale high time resolution autonomic signatures of sleep fragmentation, such as arousals and stage transitions, throughout an entire night. Results demonstrate the ability of our methods to track fast dynamic transitions from sleep to wake and between REM sleep and other sleep stages, providing resolution details not available in sleep scoring summaries. An automatic threshold-based procedure is further able to detect brief arousals, with the instantaneous indices characterizing specific arousal dynamic signatures.

Fig. 1

From top to bottom, the plots show the sleep stage (W=Wake, R=REM Sleep, N1-N3= different stages of NREM sleep), the respiratory input, the series of RR intervals, the RSA, the LF/HF index, and the residual variance of heart rate for one healthy subject (left) and one patient diagnosed with apnea (right),. The indices are averaged within the 30s scoring epochs to provide proper dynamics at the long time scale correspondent to the entire night The red stars mark times where the RSA value fall below a statistically determined threshold, indicating an arousal that often causes lightening of sleep.

Fig. 2

Example of transitions between sleep and wake, showing how the instantaneous indices (RSA, LF/HF and Var HR) computed at high resolution (5 ms) provide clear dynamic signatures associated to changes in sleep state during a time scale corresponding to a range of 900 s.

Fig. 3

Example of a transition from NREM2 to REM.

Fig. 4

Dynamic signatures of the detected CR arousals. Time =0 is where the RSA first crosses the threshold. Left: an example of the arousals found for one healthy subject. Right, for each signal we report median (dark line) and 25^th and 75^th percentile (grey lines) of the distribution at each time.