A genetic programming approach to detecting artifact-generating eye movements from EEG in the absence of electro-oculogram

A genetic programming approach to detecting artifact-generating eye movements from EEG in the absence of electro-oculogram
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DOI：
10.1109/ner.2011.5910575
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发表时间：
2011-06
期刊：
2011 5th International IEEE/EMBS Conference on Neural Engineering
影响因子：
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通讯作者：
R. Poli;C. Cinel;L. Citi;M. Salvaris
R. Poli;C. Cinel;L. Citi;M. Salvaris
中科院分区：
其他
文献类型：
--
作者：
R. Poli;C. Cinel;L. Citi;M. Salvaris

文献摘要

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在本文中，我们使用遗传编程（一种进化程序归纳技术）来进化算法，以精确地近似基于眼电图（EOG）的两个标准眼动检测器的行为。该预测完全基于 EEG 信号，即不使用 EOG，即使在没有 EOG 或眼动追踪的情况下记录的数据中也可以检测眼球运动。这种方法的实验结果非常令人鼓舞。
In this paper we use genetic programming - an evolutionary program-induction technology - to evolve algorithms that accurately approximate the behaviour of two standard detectors of ocular movement based on Electro-oculogram (EOG). The prediction is based entirely on EEG signals, i.e., without using EOG, making it possible to detect eye movements even in data recorded without EOG or eye tracking. Experimental results with this approach are very encouraging.