Use of Modified S-Transform for EEG Artifact Removal

S. Behera, M. Mohanty
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Abstract

Stock-well transform (ST) as an effective tool for time-frequency analysis has been utilized for some decades. However, its application on artifact removal is a new direction in biomedical research. In this paper, the authors tried to eliminate the artifact from the brain signal. The brain signal is collected from Mendeley and the PhysioNet database. The ST is modified by considering the orthonormal property of the signal along with the symmetric property. The modified orthonormal S transform (MOST) preserves the non-redundant samples of the signal, similar to application of discrete orthonormal S transform (DOST). Further, the artifacts are removed well, keeping the conjugate symmetry property so that low frequency EEG signal is reconstructed as original signal. For the comparative analysis DWT, DCT, ST, and DOST are also verified, and found that the proposed MOST technique well performs as compared to other transform-based methods with low complexity of $O (N \ log \ N)$ similar to the DFT computation.
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基于改进s变换的脑电信号伪影去除
Stock-well transform (ST)作为一种有效的时频分析工具已经被应用了几十年。然而,将其应用于去除伪影是生物医学研究的一个新方向。在本文中,作者试图消除大脑信号中的伪影。大脑信号从Mendeley和PhysioNet数据库中收集。通过考虑信号的正交性和对称性对ST进行修正。改进的标准正交S变换(MOST)保留了信号的非冗余样本,类似于离散标准正交S变换(DOST)的应用。此外,该方法还能很好地去除伪影,保持其共轭对称性,从而将低频脑电信号重构为原始信号。对于DWT, DCT, ST和DOST的对比分析也进行了验证,并发现所提出的MOST技术与其他基于变换的方法相比具有良好的性能,其复杂度为$O (N \ log \ N)$,类似于DFT计算。
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