Decreased sample entropy during sleep-to-wake transition in sleep apnea patients.

Abstract：Objective: This study aimed to prove that there is a sudden change in human physiology system when switching from one sleep stage to another, and a physical threshold-based SampEn is able to capture this transition in RR interval time series. The rule could also be adapted to sleep disorder patients such as sleep apnea, since the basic sleep mechanism remains similar in these individuals. APPROACH The physical threshold-based SampEn was used to analyze different sleep stage RR segments from the sleep apnea subjects in St. Vincents University Hospital/University College Dublin Sleep Apnea Database, and SampEn differences were compared between two consecutive sleep stages. To ensure the stability of the transition segments, a refinement process was added to further select transition episodes with sufficient duration in both sleep and wakefulness, and the specific sleep stage before the transition was also considered to assess the influence of the previous state. MAIN RESULTS The findings suggested that although SampEn was unable to discriminate RR segments from different sleep stages, it was sensitive to the sleep stage transitions, and the sleep-to-wake transitions presented an entropy decrease significantly larger than those intra-sleep ones (P<0.01). Moreover, the SampEn decrease was even more obvious in sleep-to-wake transition episodes with sufficient time duration than those without (P<0.01), and significant entropy differences between the sleep and the subsequent wakefulness were showed when the previous sleep stage was either S1 (P<0.05), S2 (P<0.01), or S4 (P<0.05). SIGNIFICANCE The results demonstrated that physical threshold-based SampEn has the capability of depicting the physiological change in cardiovascular system during sleep-to-wake transition in sleep apnea patients. This noninvasive HRV measure is a potential tool for further evaluation of sleep physiological time series.