20 Sleep-Related Modulations of Heart Rate Variability…
323
20.7 Discussion
New attempts are being undertaken with procedures involving more cost-effective
equipment and with easily accessible devices—such as with smartphones—to record
heart and pulse rates. From data gathered in this manner, spectral analysis and procedures from nonlinear dynamics are used to calculate heart rate variability. Attempts
are likewise being made to apply findings from the above-described studies to work
with the signals involved. Other endeavors with smartphone applications use simply
recorded signals to detect not only the respective sleep stages but also the occurrence
of sleep apnea.
These often inexpensive applications have found extensive use, since they offer
insights into sleep, from analysis conducted simply at home, of nocturnal sleep and
sleep apnea. In contrast to cardiorespiratory polysomnography among healthy and
sleep-apnea patients, none of these algorithms has until now been validated in clinical
studies. Clarification is still required of the extent to which these possibilities offer
diagnostic and prognostic potential.
Unfortunately, until now there is no analysis standard for the one-channel ECG that
goes beyond simple statistics such as mean heart rate and maximum and minimum
heart rate values. Current clinical practice does not apply established or new algorithms for HRV or cardiorespiratory coupling analysis, and therefore lags behind
the state-of-the-art techniques and knowledge of basic sleep research. In case of
HRV this may be due to the known interference between respiration and heart rate
variability parameters and only controlled conditions in terms of paced breathing
would allow a comparison of inter and intra individual changes. However, cardiorespiratory coupling does influence both interdependent systems and therefore could
be very useful for clinical interpretation of PSG recordings. A necessary step in
expediting translational research might be a closer interaction between clinicians
and researchers on this topic. This may also help to interpret changes in parameters
as observed during autonomous arousals, which are not observed in EEG leads as
central nervous activations. Such arousals can be a consequence of brief movements
and respiratory irregularities such as sighs or other phenomena observed during
sleep that lead to short alterations in ECG and heart rate as well as blood pressure.
Currently, these brief events are not further evaluated and may be disregarded as
simple perturbations and noise although short transient events may be important for
a differential diagnosis and furthermore for a decision in treatment of persons with
sleep disorders.
New methods for the evaluation of ECG and blood pressure will allow to better
distinguish between subjects being healthy or disturbed sleepers, as already seen
in subjects with obstructive snoring, bruxism, or periodic leg movements without
cortical arousals. These people do suffer without obvious indications in conventional
sleep EEG parameters.
This uncertainty is especially significant in light of the necessary assumption
that this form of investigation is being conducted not only with healthy subjects
and with patients definitely suffering from sleep apnea, but also with persons who
323
20.7 Discussion
New attempts are being undertaken with procedures involving more cost-effective
equipment and with easily accessible devices—such as with smartphones—to record
heart and pulse rates. From data gathered in this manner, spectral analysis and procedures from nonlinear dynamics are used to calculate heart rate variability. Attempts
are likewise being made to apply findings from the above-described studies to work
with the signals involved. Other endeavors with smartphone applications use simply
recorded signals to detect not only the respective sleep stages but also the occurrence
of sleep apnea.
These often inexpensive applications have found extensive use, since they offer
insights into sleep, from analysis conducted simply at home, of nocturnal sleep and
sleep apnea. In contrast to cardiorespiratory polysomnography among healthy and
sleep-apnea patients, none of these algorithms has until now been validated in clinical
studies. Clarification is still required of the extent to which these possibilities offer
diagnostic and prognostic potential.
Unfortunately, until now there is no analysis standard for the one-channel ECG that
goes beyond simple statistics such as mean heart rate and maximum and minimum
heart rate values. Current clinical practice does not apply established or new algorithms for HRV or cardiorespiratory coupling analysis, and therefore lags behind
the state-of-the-art techniques and knowledge of basic sleep research. In case of
HRV this may be due to the known interference between respiration and heart rate
variability parameters and only controlled conditions in terms of paced breathing
would allow a comparison of inter and intra individual changes. However, cardiorespiratory coupling does influence both interdependent systems and therefore could
be very useful for clinical interpretation of PSG recordings. A necessary step in
expediting translational research might be a closer interaction between clinicians
and researchers on this topic. This may also help to interpret changes in parameters
as observed during autonomous arousals, which are not observed in EEG leads as
central nervous activations. Such arousals can be a consequence of brief movements
and respiratory irregularities such as sighs or other phenomena observed during
sleep that lead to short alterations in ECG and heart rate as well as blood pressure.
Currently, these brief events are not further evaluated and may be disregarded as
simple perturbations and noise although short transient events may be important for
a differential diagnosis and furthermore for a decision in treatment of persons with
sleep disorders.
New methods for the evaluation of ECG and blood pressure will allow to better
distinguish between subjects being healthy or disturbed sleepers, as already seen
in subjects with obstructive snoring, bruxism, or periodic leg movements without
cortical arousals. These people do suffer without obvious indications in conventional
sleep EEG parameters.
This uncertainty is especially significant in light of the necessary assumption
that this form of investigation is being conducted not only with healthy subjects
and with patients definitely suffering from sleep apnea, but also with persons who