Correlational analysis of ECG & CGM

Correlation analysis of heart rate variations and glucose fluctuations during sleep Taira Kajisa*1, Toshiya Kuroi2, Hiroyuki Hara2, and Toshiyuki Sakai3 1. Course of Bio-Nano Science Fusion, Graduate School of Interdisciplinary New Science, Toyo University, 2100 Kujirai, Kawagoe, Saitama 310-8585, Japan 2. Hakuju Institute for Health Science Co., Ltd. 3. Department of Student, Student Support Division, Toyo University, 2100 Kujirai, Kawagoe, Saitama 350-8585, Japan ABSTRACT Objective: The body’s glucose concentration is influenced by carbohydrate intake, insulin-induced carbohydrate reduction, and hepatic glycogen breakdown induced by stress hormones. This study investigated the potential of employing glucose fluctuations as a measure of stress by examining the relationship between heart rate variability (HRV) data and glucose levels during sleep in healthy subjects. Methods: In this cross-sectional study, a chest-worn electrocardiogram (ECG) and continuous glucose monitoring device (CGM) were respectively used to monitor the heart rate intervals and glucose fluctuations of five subjects (two males, three females) during sleep. A time-series correlation analysis was performed on the HRV data extracted from heart rate intervals and the corresponding glucose fluctuation data. Results: The time-series analysis of ECG and CGM data collected from subjects during sleep (n = 25 nights) revealed a moderate negative correlation between glucose levels and HRV, with a cross-correlation coefficient of r = –0.453. Conclusion: Similar to HRV, changes in stress levels can be detected by observing glucose fluctuations, particularly during sleep when the impact of food intake can be eliminated. Our findings highlight a significant correlation between glucose levels and HRV, indicating that glucose fluctuations can be used as an indicator of autonomic nervous system activity.