Gotman J, Gloor P
Electroencephalogr Clin Neurophysiol. 1976 Nov;41(5):513-29. doi: 10.1016/0013-4694(76)90063-8.
An attempt was made at using a small computer to recognize and quantify interictal epileptic activity (spikes and sharp waves) in the human scalp EEG. To perform the automatic recognition, the EEG of each channel is broken down into half-waves. A half-wave is characterized by its duration and its amplitude relative to the background activity. A wave is characterized by the durations and amplitudes of its two component half-waves, by the second derivative at its apex measured relative to the background activity, and by the duration and amplitude of the following half-wave. Particular combinations of these parameters were found to characterize spikes and sharp waves and are used for their recognition and quantification. Specific methods are used for the rejection of spike-like or sharp wave-like wave forms such as eye blinks, muscle potentials and sharp alpha activity and were found to perform with a high level of reliability. Interchannel relationships are thoroughly examined to determine areas of maximal epileptogenicity. Sixteen channels can be analyzed in real time. Results are presented in a simple picture containing localizing and quantitative information. Specific questions regarding the time relationships of spikes in different channels can be asked interactively by the user. The system is of potential use in clinical electroencephalography.
曾尝试使用小型计算机识别和量化人类头皮脑电图中的发作间期癫痫活动（棘波和尖波）。为了进行自动识别，每个通道的脑电图被分解为半波。一个半波的特征在于其持续时间及其相对于背景活动的幅度。一个波的特征在于其两个组成半波的持续时间和幅度、相对于背景活动在其顶点处测量的二阶导数，以及随后半波的持续时间和幅度。发现这些参数的特定组合可表征棘波和尖波，并用于它们的识别和量化。使用特定方法来排除类似尖波或尖波样的波形，如眨眼、肌肉电位和尖α活动，并且发现这些方法具有很高的可靠性。全面检查通道间关系以确定最大致痫性区域。可以实时分析16个通道。结果以包含定位和定量信息的简单图表呈现。用户可以交互式地询问关于不同通道中棘波时间关系的特定问题。该系统在临床脑电图中具有潜在用途。
