Thomsen C E, Prior P
Department of Clinical Neurophysiology, St. Bartholomew's Hospital, London.
Ugeskr Laeger. 1998 Feb 23;160(9):1323-9.
Methodology for assessment of depth of anaesthesia based on analysis of the electroencephalogram (eeg) is controversial. Techniques range from display of single measures, for example median value of the frequency spectrum, to dedicated pattern recognition systems based on measures of several eeg features. We have compared the performance of four techniques using tape-recorded data from 23 patients anaesthetised with either halothane or isoflurane using standardised regimens. The techniques were: median frequency, spectral edge frequency, the cerebral function analysing monitor (CFAM-1) and a depth of anaesthesia monitor based on eeg pattern recognition (ADAM). Dose-response curves are presented for stepwise increases in stable end-tidal concentrations of each agent. Results indicated considerable inter-patient variability and showed the limitations of single eeg measures, particularly with deeper anaesthesia producing burst suppression patterns in the eeg. Pattern recognition techniques reduced these difficulties and appeared to be promising over a wide range of anaesthetic levels.
基于脑电图（EEG）分析来评估麻醉深度的方法存在争议。技术范围从单一测量值的显示，例如频谱的中值，到基于多种EEG特征测量的专用模式识别系统。我们使用来自23例接受氟烷或异氟烷标准化麻醉方案麻醉患者的磁带记录数据，比较了四种技术的性能。这些技术分别是：中值频率、频谱边缘频率、脑功能分析监测仪（CFAM - 1）以及基于EEG模式识别的麻醉深度监测仪（ADAM）。给出了每种药物稳定呼气末浓度逐步增加时的剂量 - 反应曲线。结果表明患者间存在相当大的变异性，并显示出单一EEG测量的局限性，特别是在较深麻醉导致EEG出现爆发抑制模式时。模式识别技术减少了这些困难，并且在广泛的麻醉水平范围内似乎很有前景。
