Taouli S A, Bereksi-Reguig F
Biomedical Engineering Research Laboratory, Biomedical Electronics Department, Science Engineering Faculty, University Aboubekr Belkaid, BP 230, Tlemcen 13000, Algeria.
J Med Eng Technol. 2010 Feb;34(2):87-96. doi: 10.3109/03091900903336886.
Electrocardiogram (ECG) signals describe the electrical activity of the heart, and are universally by physicists in the diagnosis of cardiac pathologies. However, during the acquisition of ECGs they are often contaminated with different sources of noise, making interpretation difficult. Different techniques have been used to filter the ECG signal, in order to optimize the signal to noise ratio (S/N). In this paper, an approach based on morphological filtering is developed in order to filter the ECG. Morphological filtering is concerned with the detection of the ECG morphology, therefore allowing the suppression of noises and particularly baseline wandering. The implemented filter is evaluated using signals taken from the MIT-BIH ECG universal database. The results show that the performance of this filter is good compared with other filtering techniques.
心电图(ECG)信号描述了心脏的电活动,在心脏病诊断中被物理学家广泛应用。然而,在心电图采集过程中,它们常常受到不同来源噪声的干扰,使得解读变得困难。为了优化信噪比(S/N),人们使用了不同的技术来过滤心电图信号。本文开发了一种基于形态学滤波的方法来过滤心电图。形态学滤波关注心电图形态的检测,因此能够抑制噪声,尤其是基线漂移。使用从麻省理工学院 - 贝斯以色列女执事医疗中心(MIT - BIH)心电图通用数据库获取的信号对实现的滤波器进行评估。结果表明,与其他滤波技术相比,该滤波器的性能良好。