Palem K, Barr R E
Comput Programs Biomed. 1982 Apr;14(2):145-55. doi: 10.1016/0010-468x(82)90017-4.
This paper describes the development and evaluation of a period-peak algorithm for background analysis of the clinical electroencephalogram (EEG). The procedure is a time-domain method which is harmonious with manual interpretation of the EEG tracing. Conceptually the algorithm functions in 2 modes. Major counts are detected by successive baseline crossings in the period analysis mode. Presence of superimposed activity between major-counts induces a transition to the peak-detection mode. In this manner, period-peak analysis is capable of detecting the simultaneity of slow base-waves and relatively fast superimposed activity in the EEG. Preliminary studies have been conducted in which the analysis results of this procedure were compared to those of other EEG algorithms. In general, the period-peak algorithm offered less bias towards either end of the EEG spectrum. Subsequent to testing of a FORTRAN version, the period-peak algorithm has been implemented in assembly language on a dedicated microprocessor system for on-line analysis of EEG data.
本文描述了一种用于临床脑电图（EEG）背景分析的周期峰值算法的开发与评估。该程序是一种时域方法，与脑电图描记图的人工解读相一致。从概念上讲，该算法以两种模式运行。在周期分析模式下，通过连续的基线交叉检测主要计数。主要计数之间叠加活动的存在会导致转换到峰值检测模式。通过这种方式，周期峰值分析能够检测脑电图中慢基波和相对快速叠加活动的同时性。已经进行了初步研究，将该程序的分析结果与其他脑电图算法的结果进行了比较。一般来说，周期峰值算法对脑电图频谱的两端偏差较小。在测试了FORTRAN版本之后，周期峰值算法已在专用微处理器系统上用汇编语言实现，用于脑电图数据的在线分析。
