Herrmann C S, Arnold T, Visbeck A, Hundemer H P, Hopf H C
Max Planck Institute of Cognitive Neuroscience, PO Box 500 355, D-04303, Leipzig, Germany.
Comput Biol Med. 2001 Nov;31(6):407-27. doi: 10.1016/s0010-4825(01)00017-8.
We present a hybrid system for automatic analysis of clinical routine EEG, comprising a spectral analysis and an expert system. EEG raw data are transformed into the time-frequency domain by the so-called adaptive frequency decomposition. The resulting frequency components are converted into pseudo-linguistic facts via fuzzification. Finally, an expert system applies symbolic rules formulated by the neurologist to evaluate the extracted EEG features. The system detects artefacts, describes alpha rhythm by frequency, amplitude, and stability and after artefact rejection detects pathologic slow activity. All results are displayed as linguistic terms, numerical values and maps of temporal extent, giving an overview about the clinical routine EEG.
我们提出了一种用于临床常规脑电图自动分析的混合系统，该系统包括频谱分析和专家系统。脑电图原始数据通过所谓的自适应频率分解转换到时频域。通过模糊化将得到的频率成分转换为伪语言事实。最后，专家系统应用神经科医生制定的符号规则来评估提取的脑电图特征。该系统可检测伪迹，通过频率、振幅和稳定性描述阿尔法节律，并在排除伪迹后检测病理性慢波活动。所有结果均以语言术语、数值和时间范围图的形式显示，给出临床常规脑电图的概况。
