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首页> 外文会议>First International Conference on Artificial intelligence, modelling amp; simulation >Adaptive Powerline Interference Removal from Cardiac Signals Using Leaky Based Normalized Higher Order Filtering Techniques
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Adaptive Powerline Interference Removal from Cardiac Signals Using Leaky Based Normalized Higher Order Filtering Techniques

机译：使用基于泄漏的归一化高阶滤波技术从心脏信号中自适应去除电力线干扰

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摘要

In this paper we present an adaptive filter for denoising the ECG signal based on Least Mean Fourth (LMF) algorithms. LMF algorithm exhibits lower steady state error than the conventional LMS algorithm. This is due to the fact that the excess mean-square error of the LMS algorithm is dependent only on the second order moment of the noise. The second order moment, or variance of the noise evaluates to be the same for all the noise environments. Based upon this other types of mean fourth based algorithms are implemented. These are Normalized LMF (NLMF) and Error Normalized LMF (ENLMF). In order to increase the stability of the filter leakage factor is introduced. Based on these considerations Normalized Leaky LMF (NLLMF) and Error Normalized Leaky LMF (ENLLMF) adaptive cancellers are developed for cardiac signal enhancement. Different filter structures are presented to eliminate the 60 Hz power line interference from the ECG signal. Finally, we have applied this algorithm on ECG signals from the MIT-BIH data base and compared its performance with the conventional LMS algorithm. The results show that the performance of the ENLLMF based noise reduction filter is superior than the other implementations in terms of signal to noise ratio increment.
机译：在本文中，我们提出了一种基于最小均四（LMF）算法对ECG信号进行去噪的自适应滤波器。与传统的LMS算法相比，LMF算法具有更低的稳态误差。这是由于以下事实：LMS算法的多余均方误差仅取决于噪声的二阶矩。对于所有噪声环境，二阶矩或噪声的方差估计都相同。基于此，实现了其他类型的基于均值第四的算法。它们是归一化LMF（NLMF）和错误归一化LMF（ENLMF）。为了增加滤波器的稳定性，引入了泄漏系数。基于这些考虑，开发了归一化泄漏LMF（NLLMF）和误差归一化泄漏LMF（ENLLMF）自适应抵消器来增强心脏信号。提出了不同的滤波器结构，以消除ECG信号中的60 Hz电源线干扰。最后，我们将该算法应用于来自MIT-BIH数据库的ECG信号，并将其性能与常规LMS算法进行了比较。结果表明，基于ENLLMF的降噪滤波器的性能在信噪比增加方面优于其他实现。

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