Implementation of adaptive filters for ECG Data Processing

O. Shultseva, J. Hauer
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引用次数: 12

Abstract

One of the main problems in biomedical data processing like electrocardiography is the separation of the wanted signal from noises caused by power line interference, high frequency interference, extern electromagnetic fields and random body movements and respiration. Different types of digital filters are used to remove signal components from unwanted frequency ranges. It is difficult to apply filters with fixed coefficients to reduce random noises, because hum behaviour is not exact known depending on the time. Adaptive filter technique is required to overcome this problem. In the article two types of adaptive filters are considered. Results of simulations in MATLAB are presented. Filters were coded in MPLAB C compiler and tested on a digital signal processor of microchip family dsPIC30f6014, based on the results of modeling.
心电数据处理中自适应滤波器的实现
像心电图这样的生物医学数据处理的主要问题之一是将想要的信号从电力线干扰、高频干扰、外部电磁场以及随机身体运动和呼吸引起的噪声中分离出来。不同类型的数字滤波器用于从不需要的频率范围中去除信号分量。使用固定系数的滤波器来降低随机噪声是困难的,因为嗡嗡声的行为并不确切地知道随时间的变化。为了克服这一问题,需要采用自适应滤波技术。本文考虑了两种类型的自适应滤波器。给出了MATLAB仿真结果。在MPLAB C编译器中对滤波器进行了编码,并根据建模结果在单片机dsPIC30f6014上进行了测试。
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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