Multi-Scale Permutation Entropy: A Potential Measure for the Impact of Sleep Medication on Brain Dynamics of Patients with Insomnia

Abstract

Insomnia is a common sleep disorder that is closely associated with the occurrence and deterioration of cardiovascular disease, depression and other diseases. The evaluation of pharmacological treatments for insomnia brings significant clinical implications. In this study, a total of 20 patients with mild insomnia and 75 healthy subjects as controls (HC) were included to explore alterations of electroencephalogram (EEG) complexity associated with insomnia and its pharmacological treatment by using multi-scale permutation entropy (MPE). All participants were recorded for two nights of polysomnography (PSG). The patients with mild insomnia received a placebo on the first night (Placebo) and temazepam on the second night (Temazepam), while the HCs had no sleep-related medication intake for either night. EEG recordings from each night were extracted and analyzed using MPE. The results showed that MPE decreased significantly from pre-lights-off to the period during sleep transition and then to the period after sleep onset, and also during the deepening of sleep stage in the HC group. Furthermore, results from the insomnia subjects showed that MPE values were significantly lower for the Temazepam night compared to MPE values for the Placebo night. Moreover, MPE values for the Temazepam night showed no correlation with age or gender. Our results indicated that EEG complexity, measured by MPE, may be utilized as an alternative approach to measure the impact of sleep medication on brain dynamics.

Novel method combining multiscale attention entropy of overnight blood oxygen level and machine learning for easy sleep apnea screening

“…The upper bound of the scale factor was often heuristically set to a value between 10 and 50. 33 – 35 Given the high sampling rate of signals, the scale factors applied in previous studies correspond to very short temporal scales that are often less than 1 minute. In the present study, we set the maximum scale factor to 1800, which corresponds to a temporal scale of 30 minutes, to extract useful information about the signal complexity at short, medium, and long time scales.…”

Wavelet Entropy Analysis of Electroencephalogram Signals During Wake and Different Sleep Stages in Patients with Insomnia Disorder

“… 10 Some scholars found that entropy can reflect the change of consciousness state, and the response to anesthetics during anesthesia, which can be used as one of the indicators for monitoring intraoperative anesthesia. 11 Guo et al 12 found that the multi-scale permutation entropy values of EEG signals decreased significantly in patients with insomnia during the night they received sleep medication compared with the night they received placebo. Zhou et al 13 discovered significant differences in brain entropy between patients with chronic insomnia and healthy control groups.This disparity reflects changes in the intrinsic temporal regularity of brain activity in chronic insomnia patients, which may be associated with decreased sleep quality in patients with chronic primary insomnia.…”