近年来随着人们对外科手术麻醉的安全与无痛苦的要求日益增长,麻醉过程中的监护问题就显得越来越重要了。因而对某些生理参数如呼啦、脉搏、瞳孔尺寸、汗、肌肉松弛及其它一些可观察的临床信息作无损伤的、客观的测量是十分必要的。众所周知,从头皮上测得的EEG信号的幅值和频率与麻醉过程的变化是有某种联系的。尽量减少有效数据而只提取少量EEG特征数据的方法是一种分析EEG的合适方法。标准的斜率分析是十分容易进行实时计算的,即使是用最普通的微型计算机也能很好地从理论上建立和表明这些基本信息和EEG的关系。同时还表明EEG的自相关作用能用标准的斜率分析去解释。用Hlorth氏的三个参量:活动性、变动性及复合性有可能找出EEG出现时间的信息之间的联系。这三个参最之间的内在联系通过其复合波谱的细节来描述,同时通过分析其特征 In recent years, with the increasing demands for the safety and painlessness of surgical anesthesia, the problem of guardianship during anesthesia becomes more and more important. Therefore, it is necessary to make objective and nondestructive measurements of certain physiological parameters such as hula, pulse, pupil size, sweat, muscle relaxation and other observable clinical information. It is well-known that the amplitude and frequency of EEG signals measured from the scalp have some connection to changes in the anesthetic process. A method of minimizing valid data and extracting only a small amount of EEG characterization data is a suitable method for analyzing EEG. The standard slope analysis is very easy to perform in real time, and even the most common microcomputer can well establish and demonstrate the relationship between these basic information and EEG theoretically. It also shows that the autocorrelation of EEG can be explained by a standard slope analysis. Using Hlorth’s three parameters: Activity, Variance, and Complexity, it is possible to find out the connection between the EEG occurrences. The intrinsic relationship between these three parameters is described by the details of their complex spectra and by analyzing their characteristics