Pietilä T, Vapaakoski S, Nousiainen U, Värri A, Frey H, Häkkinen V, Neuvo Y
University of Tampere, Department of Neurology, Finland.
Electroencephalogr Clin Neurophysiol. 1994 Jun;90(6):438-43. doi: 10.1016/0013-4694(94)90134-1.
A new method of recognition of epileptic activity using adaptive segmentation in EEG during long-term intensive monitoring was developed in Tampere. The performance of the system was validated and compared to the commercially available discharge recognition system of Gotman. Twelve approximately 30 min EEG segments recorded during intensive monitoring from 6 patients were analysed. On these EEG segments two EEG specialists marked the occurrence of epileptic activity independently. Later they re-evaluated any differences in their scoring. This consensus file was used as a reference in validating the performance of the two computer programs. We found that the program developed in Tampere detected discharge activity more often than the Gotman system. Both systems performed poorly in spike recognition. In the specificity of the recognized segments, the Gotman system was better.
坦佩雷研发出一种在长期密集监测脑电图（EEG）过程中使用自适应分割识别癫痫活动的新方法。该系统的性能得到了验证，并与戈特曼市售的放电识别系统进行了比较。分析了从6名患者密集监测期间记录的12个约30分钟的脑电图片段。在这些脑电图片段上，两名脑电图专家独立标记了癫痫活动的发生情况。之后他们重新评估了评分中的任何差异。这份达成共识的文件被用作验证两个计算机程序性能的参考。我们发现，坦佩雷研发的程序比戈特曼系统更频繁地检测到放电活动。两个系统在尖峰识别方面表现都很差。在识别片段的特异性方面，戈特曼系统表现更好。
