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Analysis of Brain Wave Due to Stimulus Using EEG

机译:使用脑电图刺激因脑波分析

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摘要

Brain wave is a generic term used to refer to the electrical impulses generated by the neurons or during interaction between them. These impulses also known as Neural Oscillations can be observed by the measuring technique known as Electroencephalogram (EEG). Even though research in the field has been carried out since the 1960s, high level applications using brain waves have not emerged yet. Our objective will be to obtain EEG data for different thinking process and visual stimulus. The primary deterrent while obtaining EEG data is noise. The hardware setup is optimized to acquire the data with minimal interference. After initial data acquisition, filters are applied to reduce the noise and leave relevant data. After noise has been reduced and bandwidth limited, Recurrent Neural Network (RNN) or Support Vector Machine (SVM) classification techniques are applied on the dataset to discreetly identify different wave charts generated due to different stimulus.
机译:脑波是用于指神经元产生的电脉冲或它们之间的相互作用的通用术语。可以通过称为脑电图(EEG)的测量技术来观察被称为神经振荡的这些脉冲。尽管自20世纪60年代以来已经进行了该领域的研究,但尚未出现使用脑波的高水平应用。我们的目标是获得不同思维过程和视觉刺激的EEG数据。获取EEG数据的主要威慑是噪声。硬件设置优化以获取具有最小干扰的数据。在初始数据采集后,应用过滤器以减少噪声并留下相关数据。在减少噪声和带宽限制之后,在数据集上应用经常性神经网络(RNN)或支持向量机(SVM)分类技术,以谨慎地识别由于不同的刺激而产生的不同波图。

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