基于小波的眼电信号信号调理新技术

A. Bhandari, V. Khare, M. Trikha, S. Anand
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引用次数: 15

摘要

在本文中,我们提出了一种新的简单的EOG信号调理技术,主要包括对损坏信号进行去噪和对信号进行后处理。以往的研究主要集中在眼电信号上,主要解决眼伪影的去除问题。我们从一个新的角度提出了一个方案,主要是处理EOG信号的增强。采用基于多分辨率分析和小波变换理论的方法对非平稳时变EOG信号进行处理。Coiflet小波用于利用系数阈值的概念从(awgn)损坏的EOG信号中去除噪声。SURE用于阈值选择。在信噪比方面,将其性能与Birge-Massart、Donoho和Johnstone提出的策略进行比较。采用基于Haar的高阶小波对eeg信号进行后处理。信号后处理的一个显著优点是,它有助于估计意图手势的时间瞬间和持续时间,这主要应用于基于人机界面的设备的开发
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Wavelet based Novel Technique for Signal Conditioning of Electro-Oculogram Signals
In this paper, we present a novel and simple technique for signal conditioning of EOG signals which primarily involves denoising corrupted signals and post-processing for signal enhancement. Researches in the past have mainly focused on the EOG signals where the problem of removal of ocular artifacts from the electroencephalogram was dealt. We present, from a new perspective, a scheme which essentially deals with enhancement of EOG Signals. The non-stationary and time-varying EOG signals are processed using methodologies anchored on multiresolution analyses and the wavelet transform theory. Coiflet wavelets are used for subsequent removal of noise from the (awgn) corrupted EOG signals using the concept of coefficient thresholding. SURE is used for threshold selection. Its performance, in terms of SNR, is compared with strategies suggested by Birge-Massart and Donoho and Johnstone. Haar based wavelets of higher orders are used for post-processing of EOG signals. A pronounced advantage of post-processing of signals is that it facilitates the estimation of time instants and durations of intentional eye gestures which mainly find application in the development of human-computer interface based devices
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