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A Statistical Approach for Ocular Artifact Removal in Brain Signals

机译:一种统计方法,用于去除脑信号中的人工眼

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Brain signal analysis is a complex task. Many cases artifacts are generated at the time of signal acquisition. In this paper authors have taken an approach using statistical technique to remove the artifacts from the signal. For such attempt a new-multiscale sample entropy (new-MSE) along with the statistical method kurtosis are used for identification of artifact. Considering the automated threshold, the application of wavelet transform is performed to evaluate the exact co-efficient. Further the inverse of the transform helps to construct the artifact free signal. Proposed method proves its efficacy and is shown in the result section. Also, the signals are visually inspected in form of waveform.
机译:脑信号分析是一项复杂的任务。许多情况下,在信号采集时会产生伪像。在本文中,作者采用了一种使用统计技术从信号中去除伪像的方法。为了进行这种尝试,将新的多尺度样本熵(new-MSE)与统计方法峰度一起用于识别伪影。考虑到自动阈值,执行小波变换的应用以评估确切的系数。此外,变换的逆过程有助于构造无伪像的信号。所提出的方法证明了其有效性,并在结果部分中显示。同样,以波形形式目视检查信号。

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