Development of an automatic sleep-wake staging method for rats

Ting-Ying Wei, C. Young
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Abstract

The study proposed an automated sleep-wake scoring system by using the features of electroencephalogram (EEG) and electromyogram (EMG). The method of normalization has been used to reduce the difference of features between the subjects. The proposed system would automatically discriminate the sleep-wake states into both three-state (waking, NREM and REM) and five-state (waking, NREM stage 1, NREM stage 2, transition sleep, and REM). The automated scoring results were compared with the manual scoring results that scored by the experts. The results of global agreement between the automated scoring and experts consensus in three-state scoring are 92.5% (κ=0.88) and 95.3% (κ=0.91) in five-state scoring. The results indicated that the performance of the automated sleep-wake staging system has highly reliability and accuracy.
大鼠睡眠-觉醒自动分期方法的建立
本研究提出了一种利用脑电图(EEG)和肌电图(EMG)特征的自动睡眠-觉醒评分系统。采用归一化的方法来减少受试者之间的特征差异。该系统将自动将睡眠-觉醒状态分为三状态(清醒、非快速眼动和快速眼动)和五状态(清醒、非快速眼动阶段1、非快速眼动阶段2、过渡睡眠和快速眼动)。将自动评分结果与专家打分的人工评分结果进行比较。自动评分与专家共识在三状态评分中的全局一致性为92.5% (κ=0.88),在五状态评分中的全局一致性为95.3% (κ=0.91)。结果表明,该自动睡眠-觉醒分期系统具有较高的可靠性和准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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