title: New predictors of sleep efficiency.
abstract: Sleep efficiency is a commonly and widely used measure to objectively evaluate sleep quality. Monitoring sleep efficiency can provide significant information about health conditions. As an attempt to facilitate less cumbersome monitoring of sleep efficiency, our study aimed to suggest new predictors of sleep efficiency that enable reliable and unconstrained estimation of sleep efficiency during awake resting period. We hypothesized that the autonomic nervous system activity observed before falling asleep might be associated with sleep efficiency. To assess autonomic activity, heart rate variability and breathing parameters were analyzed for 5 min. Using the extracted parameters as explanatory variables, stepwise multiple linear regression analyses and k-fold cross-validation tests were performed with 240 electrocardiographic and thoracic volume change signal recordings to develop the sleep efficiency prediction model. The developed model's sleep efficiency predictability was evaluated using 60 piezoelectric sensor signal recordings. The regression model, established using the ratio of the power of the low- and high-frequency bands of the heart rate variability signal and the average peak inspiratory flow value, provided an absolute error (mean ± SD) of 2.18% ± 1.61% and a Pearson's correlation coefficient of 0.94 (p < 0.01) between the sleep efficiency predictive values and the reference values. Our study is the first to achieve reliable and unconstrained prediction of sleep efficiency without overnight recording. This method has the potential to be utilized for home-based, long-term monitoring of sleep efficiency and to support reasonable decision-making regarding the execution of sleep efficiency improvement strategies.
authors: a Interdisciplinary Program for Biomedical Engineering , Seoul National University Graduate School , Seoul , Republic of Korea.
authors: Da Woon
authors: DW
authors: Jung
authors: b Department of Psychiatry and Behavioral Science, Seoul National University College of Medicine and Center for Sleep and Chronobiology , Seoul National University Hospital , Seoul , Republic of Korea.
authors: Yu Jin
authors: YJ
authors: Lee
authors: b Department of Psychiatry and Behavioral Science, Seoul National University College of Medicine and Center for Sleep and Chronobiology , Seoul National University Hospital , Seoul , Republic of Korea.
authors: Do-Un
authors: DU
authors: Jeong
authors: c Department of Biomedical Engineering , Seoul National University College of Medicine , Seoul , Republic of Korea.
authors: Kwang Suk
authors: KS
authors: Park
mesh_terms: D000328:Adult; D004562:Electrocardiography; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D011237:Predictive Value of Tests; D012890:Sleep / Q000502:physiology*; D012893:Sleep Wake Disorders / Q000175:diagnosis*
keywords: Sleep efficiency; breathing parameters; heart rate variability; piezoelectric sensor signal; sympathetic activation