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Faculty of Medical Sciences

Finding a new predictor of human circadian phase : An examination of heart rate and electroencephalography delta power as new estimates of circadian rhythmicity in humans

Rinsema, H.M. (Heleen) (2015) Finding a new predictor of human circadian phase : An examination of heart rate and electroencephalography delta power as new estimates of circadian rhythmicity in humans. thesis, Medicine.

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Abstract

Many physiological processes and some diseases follow a predictable circadian pattern. Adjusting therapy to a person’s circadian phase is called chronotherapy and might enhance the effectiveness of treatment. The gold standard for estimating human circadian phase is through the assessment melatonin phase (DLMO). This is however not a practical method in a clinical setting. The aim of this study was to see if heart rate (ECG) and delta power peak (EEG) derived time points are good estimators of human circadian phase in comparison with DLMO and if they are predominantly circadian or sleep homeostat driven. The differences in these time points between workdays and free days were quantified. In this study heart rate measurements and EEG delta power analysis were performed and phase of melatonin was assessed. A harmonic function was fitted through the heart rate data and the time point at which this function reached a minimum was used as the indication of heart rate phase. The time point of the peak power in delta power frequency range was used as phase marker. A possible relationship with DLMO was tested with linear regressions. A repeated measures ANOVA was used to quantify differences between workdays and free days. The minimum heart rate time point was associated with DLMO. Power peak value was not associated with DLMO. No significant differences between workdays and free days could be observed in minimum heart rate time point nor in peak power time point. Heart rate might be a circadian driven process that is associated with DLMO, making it a potential alternative predictor of human circadian phase. Peak value time point in delta power is not associated with DLMO and most likely a feature dominantly influenced by the sleep-wake homeostat and therefore not an appropriate phase predictor.

Item Type: Thesis (Thesis)
Supervisor name: Faculty supervisor: and Henning, Dr. R.H.
Supervisor name: Daily supervisors: and Wams, Dr. E.J. and Hut, Dr. R.A. and Location: University of Groningen and Chronobiology department and Linnaeusborg, Zernike complex and Groningen
Faculty: Medical Sciences
Date Deposited: 25 Jun 2020 10:41
Last Modified: 25 Jun 2020 10:41
URI: https://umcg.studenttheses.ub.rug.nl/id/eprint/297

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