[Pattern recognition techniques in sleep polygraphy].

M Jobert, W Scheuler, W Röske, E Poiseau, S Kubicki
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引用次数: 0

Abstract

The evaluation of EEG-patterns is usually accomplished by visual analysis. Nowadays however, even personal computers are fast enough for an efficient pattern recognition of EEG signals. Using sleep spindles and K-complexes as examples, our aim was to demonstrate how patterns can be detected in an EEG signal with a high degree of accuracy. Furthermore, recognition of K-complexes has been improved by applying an additional "adaptive algorithm" allowing individual adjustments to the signal's form and amplitude.

[睡眠测谎中的模式识别技术]。
脑电图模式的评估通常是通过视觉分析来完成的。然而,现在即使是个人计算机也足够快,可以对脑电图信号进行有效的模式识别。以睡眠纺锤波和k -复合体为例,我们的目的是演示如何在脑电图信号中以高度准确的方式检测模式。此外,通过应用额外的“自适应算法”,允许对信号的形式和幅度进行单独调整,k复合物的识别得到了改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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