Measurement and Analytics Method for Daily Differences Variation and Seasonal Variation for the Association Between Bedroom Environment and Heart Rate During Sleep, and Identification of the Number of Repeated Measurements

Abstract

In this study, we proposed a method for long-term repeated measurements and analysis based on examining the necessary number of repeated measurements for testing, to confirm daily and seasonal variations on how the bedroom affects the heart rate during sleep. We measured the heart rate in the subject's bedroom with a pressure-sensitive mat sensor, which allows for non-contact and non-restraint measurement without burdening the body. We did not specify experimental conditions. The methodology for analyzing seasonal variations in physiological measures employs mixed-effects models. Using the acquired heart rate data, we determined an adequate sample size and the number of repeated measures that yielded a statistical power of over 80% for the fixed effect of seasonal variation in the mixed-effects model. We analyzed daily fluctuations using a Spearman rank correlation matrix, confirming a correlation with temperature.