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The correlation behavior in the heart beat rate significantly differs with respect to light sleep, deep sleep, and REM sleep. We investigate whether fluctuations of the heart beat rhythm may serve as a surrogate parameter for rapidly changing sleep phenomena, and if these changes are accessible by progressive beatby-beat analysis of the sleep electrocardiogram (ECG).

Question of the study Sleep stages are known to differ in the heart rate variability (HRV). REM sleep and wakefulness are characterized by long-range correlations in the heart beat rate. In SWS, a statistical correlation extends only to very few (3-6) of the heart beats that follow. In the present paper, this difference is utilized to separate NREM sleep from REM sleep and wakefulness on-line in polysomnographic whole-night sleep recordings. Methods So far, 48 whole-night recordings of 19 healthy subjects have been subjected to numerical analysis. Extracting the RR intervals from the ECG channels of the polysomnographies, a time series was established and analysed with a variety of numerical methods. In particular, we have applied the progressive detrended fluctuation analysis (PDFA), a tool that we recently developed to find and localize statistical 'change points', and a continuously moving wavelet analysis that we adapted for this purpose. Spectral methods were applied to gain indirect information on the sympathetic activity. Results PDFA and the wavelet method were found to be sensitive to transitions between particular sleep stages and consistently insensitive to others when superimposed on a sleep chart of visually scored colour-coded sleep stages: Short embedded periods of wakefulness are detected with excellent sensitivity and reliability. 'Numerical events' reliably mark transitions from deeper to lighter sleep (e.g. from stage 4 to stage 3 or 2) but are consistently missing for transitions from deep to light sleep (e.g. from stage 3 or 2 to stage 4). By varying a built-in scaling parameter of the method, a visual display is generated that clearly differentiates REM sleep and wakefulness from NREM sleep. Wakefulness and REM cannot be distinguished in this way. The examples discussed are typical of the 48 whole-night polysomnographies.Conclusions The fact that our numerical method is not sensitive to the more gradual settling from the initiation of sleep into SWS rules out the possibility of progressive on-line sleep staging based on the PDFA approach. The discrimination between REM sleep/wake and NREM sleep gives rise to an automated aid to visual scoring. Since PDFA events seem to be related to the occurrence of autonomic arousals, our approach has the potential to provide an alternative way to detect and classify arousals.Keywords heart rate variability -time series analysis -sleep stage reconstructionautonomic arousal. ZusammenfassungFragestellung Schlafstadien unterscheiden sich in der Herzschlagvariabilität. Statistische Analysen des Herzschlags ergeben kurz-und lang-reichweitige sehr unterschiedliche Korrelationszeiten in der Zeitreihe der RR-Intervalle. REM-Schlaf und Wachstadien sind charakterisiert durch statistische Korrelation über viele RR-Intervalle. Im SWS erstreckt sich Somnologie 8: 33-41, 2004 eine statistische Korrelation nur über 3-6 RR-Intervalle. In der vorliegenden Arbeit wird der Versuch einer automatisierten und fortlaufenden Unterscheidung von NREM-Schlafstadien und REM-Schlaf bz...