Background: It is increasingly popular to use heart-rate variability (HRV) to tailor training for athletes. A time-efficient method is HRV assessment during deep sleep.
Aim: To validate the selection of deep-sleep segments identified by RR intervals with simultaneous electroencephalography (EEG) recordings and to compare HRV parameters of these segments with those of standard morning supine measurements.