Circadian rhythm based detection and prediction of chronic stress and atrial fibrillation

Abstract

Circadian rhythm represents regular changes in mental and physical characteristics that occur with the period slightly longer than 24 hours. Circadian rhythm is associated with variety of body functions such as body temperature, hormone secretion, urine production, changes in blood pressure, and other biological activities. When disruption of circadian rhythm is lasted for a long time, biological functions do not work properly. It may increase the risk of developing cancers and leading negative health consequences on peripheral organs outside the brain, particularly in the development or exacerbation of cardiovascular disease. Thus, circadian rhythm has been appraised as a useful tool for better understanding of many health problems. In this study, circadian rhythm based detection and prediction techniques were investigated in subjects with chronic mental stress and atrial fibrillation (AF). Chronic mental stress is detrimental to our health and one of well known major risk factors for many cardiovascular diseases such as coronary artery diseases, AF, and hypertension. Thus, effective stress management for high risk patients is important issue to prevent the development of these diseases. We investigated the daytime patterns of heart rate variability (HRV) to provide a preliminary evidence for the reliable detection of subjects under relatively high level of chronic mental stress. Results suggested that subjects with higher self-reporting stress scores (high stress group) showed suppressed circadian patterns of HRV features compared to subjects with lower scores (low stress group). Logistic regression models based on the degree of difference from normal reference patterns showed the accuracy up to 69.8% in predicting the membership of stress groups. We also studied HRV patterns of AF episodes during the daytime and evening time to improve the accuracy of detection and prediction of AF episodes. HRV features were calculated from electrocardiogram (ECG) da...