scholarly journals PLI Cancellation in ECG Signal Based on Adaptive Filter by Using Wiener-Hopf Equation for Providing Initial Condition

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Anchalee Manosueb ◽  
Jeerasuda Koseeyaporn ◽  
Paramote Wardkein
Keyword(s):  
Adaptive Filter ◽  
Reference Signal ◽  
Ecg Signal ◽  
Initial Weight ◽  
Matlab Program ◽  
Analytical Response ◽  
Power Line Interference ◽  
Electrocardiogram Ecg ◽  
Frequency Power ◽  
Line Interference

This paper presents a technique for finding the optimal initial weight for adaptive filter by using difference equation. The obtained analytical response of the system identifies the appropriate weights for the system and shows that the MSE depends on the initial weight. The proposed technique is applied to eliminate the known frequency power line interference (PLI) signal in the electrocardiogram (ECG) signal. The PLI signal is considered as a combination of cosine and sine signals. The adaptive filter, therefore, attempts to adjust the amplitude of cosine and sine signals to synthesize a reference signal very similar to the contaminated PLI signal. To compare the potential of the proposed technique to other techniques, the system is simulated by using the Matlab program and the TMS320C6713 digital board. The simulation results demonstrate that the proposed technique enables the system to eliminate the PLI signal with the fastest time and gains the superior results of the recovered ECG signal.

scholarly journals Effect of adaptive line enhancement filters on noise cancellation in ECG signals

2021 ◽  
Vol 18 (3) ◽  
pp. 291-302
Author(s):  
George Karraz
Keyword(s):  
Adaptive Filter ◽  
Adaptive Filters ◽  
Reference Signal ◽  
Power Line ◽  
Ecg Signal ◽  
Ecg Signals ◽  
Filter Performance ◽  
Power Line Interference ◽  
Adaptive Line Enhancement ◽  
Line Interference

Power line interference is the main noise source that contaminates Electrocardiogram (ECG) signals and measurements. In recent years, adaptive filters with different approaches have been investigated to eliminate power line interference in ECG waveforms. Adaptive line enhancement filter is a special type of adaptive filter that, unlike other adaptive filters, does not require a reference signal and has potential application in ECG signal filtering. In this paper, a selflearning filter based on an adaptive line enhancement (ALE) filter is proposed to remove power line interference in ECG signals. We simulate the adaptive filter in MATLwith a noisy ECG signal and analyze the performance of algorithms in terms of signal-to-noise ratio (SNR) improvement. The proposed algorithm is validated with Physikalisch-Technische Bundesanstalt (PTB) ECG signals database. Additive white gaussian noise is added to the raw ECG signal. Influential parameters on the ALE filter performance such as filter delay, the convergence factor, and the filter length are analyzed and discussed.

scholarly journals Adaptive Noise Filter for Real-Time Stress ECG Signal Analysis

2020 ◽  
Vol 30.8 (147) ◽  
pp. 59-64
Author(s):  
Van Manh Hoang ◽  
◽  
Manh Thang Pham
Keyword(s):  
Adaptive Filter ◽  
Stress Test ◽  
Reference Signal ◽  
Motion Artifact ◽  
Ecg Signal ◽  
Step Size ◽  
Ecg Signals ◽  
Noise Filter ◽  
Adaptive Noise ◽  
Electrocardiogram Ecg

The stress Electrocardiogram (ECG) gives more efficient results for the diagnosis of cardiovascular diseases, which may not be apparent when the patients are at rest. However, the noise produced by the movement of the patient and the environment often contaminates the ECG signal. Motion artifact is the most prevalent and difficult type of interference to filter in stress test ECG. It corrupts the quality of the desired signal thus reducing the reliability of the stress test. In this work, we first describe a quantitative study of adaptive filtering for processing the stress ECG signals. The proposed method uses the motion information obtained from a 3-axis accelerometer as a noise reference signal for the adaptive filter and the optimal weight of the adaptive filter is adjusted by the Modified Error Data Normalized Step-Size (MEDNSS) algorithm. Finally, the performance of the proposed algorithm is tested on the stress ECG signal from the subject.

Enhancement of ECG Signal by Minimizing Power Line Interference Using FPGA Based Adaptive Filter

2019 ◽  
pp. 167-176
Author(s):  
A. M. Kasture ◽  
M. A. Deshmukh ◽  
J. S. Hallur ◽  
D. P. Narsale ◽  
Akshay A. Jadhav
Keyword(s):  
Adaptive Filter ◽  
Power Line ◽  
Ecg Signal ◽  
Power Line Interference ◽  
Line Interference

scholarly journals CANCELLATION OF MOTION ARTIFACT NOISE AND POWER LINE INTERFERENCE IN ECG USING ADAPTIVE FILTERS

2014 ◽  
pp. 297-299
Author(s):  
IMTEYAZ AHMAD ◽  
F. ANSARI ◽  
U.K. DEY
Keyword(s):  
Adaptive Filter ◽  
Motion Artifact ◽  
Power Line ◽  
Lms Algorithm ◽  
Recursive Least Squares ◽  
Ecg Signal ◽  
Least Mean Square ◽  
Rls Algorithm ◽  
Power Line Interference ◽  
Line Interference

Background: The electrocardiogram(ECG) has the considerable diagnostic significance, and applications of ECG monitoring are diverse and in wide use. Noises that commonly disturb the basic electrocardiogram are power line interference(PLI), instrumentation noise, external electromagnetic field interference, noise due to random body movements and respiration movements. These noises can be classified according to their frequency content. It is essential to reduce these disturbances in ECG signal to improve accuracy and reliability. The bandwidth of the noise overlaps that of wanted signals, so that simple filtering cannot sufficiently enhance the signal to noise ratio. It is difficult to apply filters with fixed filter co-efficients to reduce these noise. Adaptive filter technique is required to overcome this problem as the filter coefficients can be varied to track the dynamic variations of the signals. Adaptive filter based on the least mean square (LMS) algorithm and recursive least squares (RLS) algorithm are applied to noisy ECG to reduce 50 Hz power line noise and motion artifact noise. Method: ECG signal is taken from physionet database. A ECG signal (without noise) was mixed with constant 0.1 mVp-p 50 Hz interference and motion artifact noise processed with Adaptive filter based on the least mean square (LMS) algorithm and recursive least squares (RLS) algorithm. Simulation results are also shown. Performance of filters are analyzed based on SNR and MSE.

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