Adaptive ECG Signal Filtering Using Bayesian Based Evolutionary Algorithm

Author(s):  
Thibaut Bernard ◽  
Amir Nakib
2003 ◽  
Vol 36 (15) ◽  
pp. 295-300 ◽  
Author(s):  
S.M. Szilágyi ◽  
Z. Benyó ◽  
L. Dávid
Keyword(s):  

In order to detect the Myocardial Infarction from ECG records of the patients, the physicians study the electrical motion of the heart. A Myocardial Infarction is an illness condition related to the heart and it is recognized when the pathway to the heart is blocked. These blocks interrupt the regular functioning of the heart; which is spotted through the deviations in the readings of ECG signals. For the sake of detecting Myocardial Infarction, it is essential to detect ST-Elevation followed by the removal of noise in ECG signals with the help of the filtering process. ECG signals are getting affected by various noises with high and low frequencies that will originate the incorrect interpretation. The methodologies for ECG signal filtering using filtering algorithms and for STEMI feature selection from the resultant noise free ECG signals are presented in this paper by employing the MATLAB tool


2014 ◽  
Vol 513-517 ◽  
pp. 3757-3760
Author(s):  
Yan Peng ◽  
Zhi Gang Qin

According to the process of the ECG signal extraction, the ECG signal is susceptible to interference which will affect the quality and effect of ECG test. In this essay, we designed an ECG signal filtering system based on ARM. It can filter the interference signal and reduce the interference of the common mode signal and power frequency, through the design circuit of the preamplifier, post amplification, filtering, notch filtering, and power amplification. Thus, ECG signal will be better collected and met the best demand.


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