睡眠(系统调用)
清醒
脑电图
睡眠阶段
医学
多导睡眠图
神经科学
麻醉
生物医学工程
心理学
计算机科学
操作系统
作者
Ya‐Tao Wang,Yue‐Ming Zhang,Xu Wu,Chong‐Yang Ren,Zhe‐Zhe Zhang,Qi‐Gang Yang,Xue‐Yan Li,Gui‐Hai Chen
摘要
INTRODUCTION: Currently, electroencephalogram (EEG)/electromyogram (EMG) system is widely regarded as the "golden standard" for sleep monitoring. Imperfectly, its invasive monitoring may somehow interfere with the natural state of sleep. Up to now, noninvasive methods for sleep monitoring have developed, which could preserve the undisturbed and naïve sleep state of mice to the greatest extent, but the feasibility of their application under different conditions should be extensive validated. METHODS: Based on existing research, we verified the feasibility of a sleep monitoring system based on mouse behaviors under different conditions. The experimental mice were exposed to various stresses and placed into a combined device comprising noninvasive sleep monitoring equipment and an EEG/EMG system, and the sleep status was recorded under different physiological, pharmacological, and pathophysiological conditions. The consistency of the parameters obtained from the different systems was calculated using the Bland-Altman statistical method. RESULTS: The results demonstrated that the physiological sleep times determined by noninvasive sleep monitoring system were highly consistent with those obtained from the EEG/EMG system, and the coefficients were 94.4% and 95.1% in C57BL/6J and CD-1 mice, respectively. The noninvasive sleep monitoring system exhibited high sensitivity under the sleep-promoting effect of diazepam and caffeine-induced wakefulness, which was indicated by its ability to detect the effect of dosage on sleep times, and accurate determination of the sleep/wakeful status of mice under different pathophysiological conditions. After combining the data obtained from all the mice, the coefficient between the sleep times detected by behavior-based sleep monitoring system and those obtained from the EEG/EMG equipment was determined to .94. CONCLUSION: The results suggested that behavior-based sleep monitoring system could accurately evaluate the sleep/wakeful states of mice under different conditions.
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