大鼠睡眠评分仪器的信号分析方法。

Waking and sleeping Pub Date : 1980-01-01
W B Mendelson, W J Vaughn, M J Walsh, R J Wyatt
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引用次数: 0

摘要

自动大鼠睡眠分析侧重于脑电图的统计规则波形,如θ和δ节律。这种随机过程可以用几种方式来量化。时域统计,如自动和相互关联产生的输出很难使用,最好在软件中执行。频谱密度等频域统计数据通过工频分布精确地量化睡眠状态,但也需要复杂的计算机处理。使用通带滤波的连续频率分析以在线方式精确测量信号功率,并采用相对便宜的硬件通过对信号的平方进行积分来估计功率。这种方法与以前报道的依赖于信号幅度分析的其他系统有本质上的不同。该系统与人类评分者的比较表明了高度的有效性和可重复性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A signal analysis approach to rat sleep scoring instrumentation.

Automated rat sleep analysis focuses on the statistically regular waveforms of the EEG, such as theta and delta rhythms. Such stochastic processes can be quantified in several manners. Time domain statistics such as auto- and cross-correlations produce outputs that are difficult to use and are best performed in software. Frequency domain statistics like spectral density accurately quantify the sleep state by power-frequency distributions but also require sophisticated computer processing. Continuous frequency analysis, using pass-band filtering, accurately measures signal power in an on-line fashion and employs relatively inexpensive hardware to estimate power by integrating the square of the signal. This method differs substantively from other previously reported systems which rely on signal amplitude analysis. Comparison of this system with a human scorer indicates high degrees of validity and reproducibility.

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