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An efficient automatic arousals detection algorithm in single channel EEG

机译:单通道EEG中有效的自动唤醒检测算法

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摘要

Background and objective: Electroencephalographic arousal is a transient waveform that instantaneously happens in sleep as an inherent component. It has distinctive amplitude and frequency features. However, it is visually difficult to distinguish arousal from the background of the electroencephalogram. This visual scoring is important for brain researches, sleep studies, sleep stage scorings and assessment of sleep disorders. The scoring process is a time-consuming and difficult clinical procedure which is evaluated by sleep experts. It may also have subjective consequences due to the variability of personal expertise of physicians. Conversely, this scoring process can be significantly accelerated with computer-aided automated algorithms. Moreover, reproducible and objective results can be obtained. In this work, we propose a novel algorithm for the automatic detection of electroencephalographic arousals in sleep polysomno-graphic recordings.
机译:背景和目的:脑电图唤醒是一种瞬态波形,瞬间发生在睡眠中作为固有的成分。 它具有独特的幅度和频率特征。 然而,从脑电图的背景下,视觉难以区分唤醒。 这种视觉评分对于大脑研究,睡眠研究,睡眠阶段评分和睡眠障碍评估很重要。 评分过程是休眠专家评估的耗时和困难的临床程序。 由于医师的个人专业知识的可变性,它也可能具有主观后果。 相反,通过计算机辅助自动化算法可以显着加速该评分过程。 此外,可以获得可重复的和客观的结果。 在这项工作中,我们提出了一种新颖的综合检测睡眠多面程 - 图形记录中的脑电图唤醒的新算法。

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