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Updated: May 26, 2026
Quantifying Infra-slow Dynamics of Spectral Power and Heart Rate in Sleeping Mice
Published on: August 2, 2017
Linear mixed-effects modeling of the relationship between heart rate variability and fatigue arising from sleep
Donovan L Fogt1, William H Cooke, John E Kalns
1Department of Health and Kinesiology, The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249-1644, USA. donovan.fogt@utsa.edu
Introduction:
Fatigue degrades cognitive performance, yet there is no universally accepted objective measure of fatigue. We tested whether fatigue arising from sleep deprivation can be quantified objectively using heart rate variability (HRV).
Methods:
There were 35 male subjects (mean +/- SD; age = 21.4 +/- 2.6 yr) who were assigned to one of two experimental groups: (1) control (N = 16), or (2) 48-h sleep-deprived (N=19). Using 3-h sampling intervals, we simultaneously tracked fatigue level, cognitive performance, and HRV. Linear mixed-effects (LME) models were used to evaluate linear relationships between fatigue level and cognitive performance, as well as between fatigue level and HRV.
Results:
Significant negative slopes were observed in LME models of cognitive performance and fatigue level. Of the several HRV parameters examined during standing and supine rest, the ratio of low-frequency to high-frequency R-R interval in the supine position had the clearest significant relationship when modeled against fatigue level.
Discussion:
In summary, our results suggest that HRV tracks fatigue arising from sleep deprivation. This noninvasive, objective tool can quantify fatigue in real time.
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