Evaluation of denoising techniques for EOG signals based on SNR estimation

A. Dasgupta, S. Chakrborty, Aritra Chaudhuri, A. Routray
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引用次数: 7

Abstract

This paper evaluates four algorithms for denoising raw Electrooculography (EOG) data based on the Signal to Noise Ratio (SNR). The SNR is computed using the eigenvalue method. The filtering algorithms are a) Finite Impulse Response (FIR) bandpass filters, b) Stationary Wavelet Transform, c) Empirical Mode Decomposition (EMD) d) FIR Median Hybrid Filters. An EOG dataset has been prepared where the subject is asked to perform letter cancelation test on 20 subjects.
基于信噪比估计的EOG信号去噪技术评价
本文对四种基于信噪比的原始眼电数据去噪算法进行了评价。采用特征值法计算信噪比。滤波算法是a)有限脉冲响应(FIR)带通滤波器,b)平稳小波变换,c)经验模态分解(EMD) d) FIR中值混合滤波器。准备了EOG数据集,要求受试者对20名受试者进行字母取消测试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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