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T. Penzel et al.
merely snore and others who represent mixed forms of snoring and sleep apnea. The
importance of HRV and cardiorespiratory coupling analyses becomes particularly
evident in the context of such borderline cases, which are even more widespread
than cases of unequivocal sleep apnea itself. For this reason, reliable validation
of such applications must be required before diagnostic employment. Otherwise,
they represent merely one more general application intended to measure data from
individuals and to expand their personal digital environment, without sustainable
background and without the possibility of specific and well-founded intervention.
First attempts in this direction are being made with recordings of single-channel
ECGs based on which HRV and EDR are determined, and from these data cardiopulmonary coupling (CPC) is estimated [41]. It is also possible to analyze various
frequency bands—i.e., low-frequency coupling (LFC) and high-frequency coupling
(HFC)—to evaluate sleep (e.g., stable sleep, instable sleep, and REM sleep/wake)
and the occurrence sleep-related breathing disorders (SRBD) that lead to an elevated
share of LFC. It is furthermore possible to characterize existing SRBD on the basis of
various patterns in LFC. An initial study has revealed greater likelihood of a narrowband sample in LFC for periodically central apnea events—whereas, in contrast, a
more pronounced broad-band pattern is characteristic of predominantly obstructive
sleep apnea [36]. However, prospective studies are required to verify the extent to
which these indications hold true.
20.8 Summary
Analysis of ECG data and heart rate during sleep provides an appreciable diversity
of information on the physiology and the pathophysiology of sleep-wake regulation. Assessment of nocturnal ECGs with respect to cyclical fluctuations of heart
rate, combined with studies of respiration-dependent alterations in ECG morphology
(e.g., amplitudes of the R waves and T waves), allows reliable recognition of sleeprelated breathing disorders. The quality of sleep itself can also be evaluated by analysis of heart-rate variations. Deep sleep and REM sleep, to be sure, demonstrate
characteristic properties in heart-rate variability.
Even now, new methods are being applied in practice by presenting sleep findings
that already include analysis of healthy sleep and sleep disorders with the aid of longterm ECG systems, data from pacemaker ECGs, multi-night actigraphy data as well
as information from innovative, reduced-scale recording systems [2, 15]. To arrive at
solid diagnostic and therapeutic conclusions from these results, it will be necessary
to conduct prospective validation studies and to perform clinical evaluation with
parallel polygraphy and polysomnography. In addition, new algorithms are needed
which allow automated processing of heart rate and heart rate variability which
results in a conclusive report, similar to the report created from sleep-stage scoring
or respiration scoring.
T. Penzel et al.
merely snore and others who represent mixed forms of snoring and sleep apnea. The
importance of HRV and cardiorespiratory coupling analyses becomes particularly
evident in the context of such borderline cases, which are even more widespread
than cases of unequivocal sleep apnea itself. For this reason, reliable validation
of such applications must be required before diagnostic employment. Otherwise,
they represent merely one more general application intended to measure data from
individuals and to expand their personal digital environment, without sustainable
background and without the possibility of specific and well-founded intervention.
First attempts in this direction are being made with recordings of single-channel
ECGs based on which HRV and EDR are determined, and from these data cardiopulmonary coupling (CPC) is estimated [41]. It is also possible to analyze various
frequency bands—i.e., low-frequency coupling (LFC) and high-frequency coupling
(HFC)—to evaluate sleep (e.g., stable sleep, instable sleep, and REM sleep/wake)
and the occurrence sleep-related breathing disorders (SRBD) that lead to an elevated
share of LFC. It is furthermore possible to characterize existing SRBD on the basis of
various patterns in LFC. An initial study has revealed greater likelihood of a narrowband sample in LFC for periodically central apnea events—whereas, in contrast, a
more pronounced broad-band pattern is characteristic of predominantly obstructive
sleep apnea [36]. However, prospective studies are required to verify the extent to
which these indications hold true.
20.8 Summary
Analysis of ECG data and heart rate during sleep provides an appreciable diversity
of information on the physiology and the pathophysiology of sleep-wake regulation. Assessment of nocturnal ECGs with respect to cyclical fluctuations of heart
rate, combined with studies of respiration-dependent alterations in ECG morphology
(e.g., amplitudes of the R waves and T waves), allows reliable recognition of sleeprelated breathing disorders. The quality of sleep itself can also be evaluated by analysis of heart-rate variations. Deep sleep and REM sleep, to be sure, demonstrate
characteristic properties in heart-rate variability.
Even now, new methods are being applied in practice by presenting sleep findings
that already include analysis of healthy sleep and sleep disorders with the aid of longterm ECG systems, data from pacemaker ECGs, multi-night actigraphy data as well
as information from innovative, reduced-scale recording systems [2, 15]. To arrive at
solid diagnostic and therapeutic conclusions from these results, it will be necessary
to conduct prospective validation studies and to perform clinical evaluation with
parallel polygraphy and polysomnography. In addition, new algorithms are needed
which allow automated processing of heart rate and heart rate variability which
results in a conclusive report, similar to the report created from sleep-stage scoring
or respiration scoring.