Detection of atrial fibrillation episodes using multiple heart rate variability features in different time periods.

Circadian variations of cardiac diseases have been well known. For example, atrial fibrillation (AF) episodes show nocturnal predominance. In this study, we have developed multiple formulas that detect AF episodes in different times of the day.

Detection of subjects with higher self-reporting stress scores using heart rate variability patterns during the day.

Heart rate variability (HRV) has been well established to measure instantaneous levels of mental stress. Circadian patterns of HRV features have been reported but their use to estimate levels of mental stress were not studied thoroughly. In this study, we investigated time dependent variations of HRV features to detect subjects under chronic mental stress.