Lozoya X, García-Peña J, González-Villalpando C, Solís-Camara P, Parra A
Arch Invest Med (Mex). 1975;6(3):467-76.
Correlation of hormonal changes and EEG activity requires objective measurements to define the behavior of the different frequency bands during sleep. With this purpose, EEG activity of six healthy male volunteers (19-22 years) was recorded throughout all night during spontaneous sleep. The C4-left mastoid EEG combination was channeled to a frequency analyzer with four band pass filters (beta, alpha, theta, and delta) using a one minute averaging interval. Analyzer data were fed to an IBM-1130 computer, programmed with RC filter recursive algorithm. Sleep stages were characterized in the polygraphic record (Rechtshaffen criteria), and identified in the smoothed profile. The latter was computed for mean voltage value of each band during the sleep stages. Differences in the behavior of each band throughout sleep stages were statistically tested. Delta activity showed the highest discriminatory capacity characterized by a statistically different mean voltage value in all sleep stages, with the exception of R-I. The method is proposed for quantitative correlation of the EEG sleep phenomena with another physiological parameters.
激素变化与脑电图活动之间的相关性需要客观测量来确定睡眠期间不同频段的行为。为此，对六名健康男性志愿者（19 - 22岁）在自然睡眠的整个夜间进行脑电图活动记录。使用一分钟平均间隔，将C4 - 左侧乳突脑电图组合输入到带有四个带通滤波器（β、α、θ和δ）的频率分析仪中。分析仪数据被输入到一台用RC滤波器递归算法编程的IBM - 1130计算机中。睡眠阶段在多导睡眠图记录中进行特征描述（ Rechtschaffen标准），并在平滑曲线上进行识别。后者是针对睡眠阶段中每个频段的平均电压值计算得出的。对每个频段在整个睡眠阶段的行为差异进行了统计学检验。δ活动显示出最高的辨别能力，其特征是除R - I外，在所有睡眠阶段的平均电压值在统计学上都不同。该方法被提出用于脑电图睡眠现象与其他生理参数的定量相关性研究。
