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首页> 外文期刊>Computer Methods and Programs in Biomedicine: An International Journal Devoted to the Development, Implementation and Exchange of Computing Methodology and Software Systems in Biomedical Research and Medical Practice >Detection of eye blink artifacts from single prefrontal channel electroencephalogram
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Detection of eye blink artifacts from single prefrontal channel electroencephalogram

机译：从单个前额叶脑波图检测眨眼伪影

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摘要

Eye blinks are one of the most influential artifact sources in electroencephalogram (EEG) recorded from frontal channels, and thereby detecting and rejecting eye blink artifacts is regarded as an essential procedure for improving the quality of EEG data. In this paper, a novel method to detect eye blink artifacts from a single-channel frontal EEG signal was proposed by combining digital filters with a rule-based decision system, and its performance was validated using an EEG dataset recorded from 24 healthy participants. The proposed method has two main advantages over the conventional methods. First, it uses single channel EEG data without the need for electrooculogram references. Therefore, this method could be particularly useful in brain-computer interface applications using headband-type wearable EEG devices with a few frontal EEG channels. Second, this method could estimate the ranges of eye blink artifacts accurately. Our experimental results demonstrated that the artifact range estimated using our method was more accurate than that from the conventional methods, and thus, the overall accuracy of detecting epochs contaminated by eye blink artifacts was markedly increased as compared to conventional methods. The MATLAB package of our library source codes and sample data, named Eyeblink Master, is open for free download. (C) 2015 Elsevier Ireland Ltd. All rights reserved.
机译：眨眼是从额叶脑电图记录的脑电图（EEG）中最有影响力的伪影来源之一，因此，检测和拒绝眨眼伪影被视为提高EEG数据质量的必要程序。本文提出了一种通过将数字滤波器与基于规则的决策系统相结合来从单通道额叶脑电信号中检测眨眼伪像的新方法，并使用从24名健康参与者处记录的脑电数据集来验证其性能。与常规方法相比，所提出的方法具有两个主要优点。首先，它使用单通道EEG数据，而无需眼电图参考。因此，此方法在使用头带式可穿戴式EEG设备并具有几个正面EEG通道的脑机接口应用中可能特别有用。其次，该方法可以准确估计眨眼伪影的范围。我们的实验结果表明，使用我们的方法估计的伪影范围比传统方法更准确，因此，与传统方法相比，检测被眨眼伪影污染的历时的整体准确性显着提高。我们的库源代码和示例数据的MATLAB软件包名为Eyeblink Master，可以免费下载。 （C）2015 Elsevier Ireland Ltd.保留所有权利。

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