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A morphology algorithm based on 2-dimensional flat structure element on ECG baseline wander elimination

机译:基于二维平面结构元素的心电图基线漂移消除的形态学算法

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Baseline wander always exists along with ECG signal. It is a kind of noise and may interference the diagnosis of cardio diseases, especially for the automatic diagnosis. Most methods could eliminate baseline wander already, however be difficult to meet the requisition of low distortion. To solve this problem, a morphology algorithm based on 2-D flat structure element is proposed, where flat structure element is often employed in previous work. The structure element is designed according to the shape, amplitude, period of the ECG signal itself, for a more accurate approximating to the ECG waveforms. Moreover, such structure element is variable by the feedback of filtered waveforms, which could elevate its robust. This algorithm is tested with the data from 8 files of MIT/BIH arrhythmia database, which contains 8 different shapes in ST segment, covering most of the cardiac conditions. The results are estimated in the baseline elimination as well as the distortion induced by filtering on the P waveform, QRS wave group, and the ST segments of ECG signal. Compared with those arguments of several classical strategies, the signal to noise ratio after processed by morphology based on non-flat structure element reaches the highest among all methods, and the ratio of deformation lowest, which means that this algorithm could both reduce the baseline wander, and control the distortion effectively.
机译:基线漂移总是伴随着ECG信号而存在。它是一种噪声,可能会干扰心脏疾病的诊断,尤其是对于自动诊断。大多数方法可以消除基线漂移,但是很难满足低失真的要求。为了解决这个问题,提出了一种基于二维平面结构元素的形态学算法,在以前的工作中经常采用平面结构元素。根据ECG信号本身的形状,幅度,周期设计结构元素,以便更精确地近似ECG波形。而且,这种结构元件通过滤波后的波形的反馈是可变的,这可以提高其鲁棒性。 MIT / BIH心律失常数据库的8个文件中的数据对该算法进行了测试,该文件在ST段中包含8种不同形状,涵盖了大多数心脏疾病。在基线消除以及通过滤波P波形,QRS波组和ECG信号的ST段引起的失真中估计结果。与几种经典策略的论点相比,基于非平面结构元素的形态学处理后的信噪比在所有方法中达到最高,而变形率最低,这意味着该算法可以减少基线漂移,并有效控制失真。

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