Key result
Methodologies for heart rate variability analysis during sleep, such as time-frequency analysis and long time correlation, can address non-stationarities and long-term analysis needs.
This methodological review outlines techniques for analyzing heart rate variability during sleep to assess autonomic regulation in physiological and pathological conditions.
May refine autonomic assessment via sleep HRV; leaves open prospective clinical validation.
In the last years we have witnessed the growing interest in the heart rate variability (HRV) signal analysis during sleep. The study of the autonomic regulation during sleep allowed developing methods for automatic detection and classification of some sleep characteristics, both in physiological and pathological conditions. The main problems which require to be faced are the presence of frequent non-stationarities in the signal and the need of dealing with long term analysis, in order to provide reliable indices able to describe the whole night of sleep. In the present paper we are presenting some of the methodologies we recently employed in the study of the heart rate variability during sleep, ranging from time-frequency analysis to long time correlation. Some results are also presented, related to different applications, dealing with both physiological and pathological conditions.
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Bianchi et al. (2013) conducted a review in Sleep (physiological and pathological conditions). Heart rate variability (HRV) analysis methods was evaluated. Methodologies for heart rate variability analysis during sleep, such as time-frequency analysis and long time correlation, can address non-stationarities and long-term analysis needs.
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