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.

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 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 Adaptive Symlet filter based on ECG baseline wander removal

2020 ◽  
Vol 17 (2) ◽  
pp. 187-197
Author(s):  
Ali Nahar
Keyword(s):  
Wavelet Transform ◽  
Adaptive Filter ◽  
Reference Signal ◽  
Low Frequency ◽  
Noise Removal ◽  
Ecg Signal ◽  
Computing Technique ◽  
Ecg Signals ◽  
Computation Process ◽  
Approximation Coefficients

In this paper, proposed a new approach of combining the hybrid soft computing technique called Adaptive Symlet Wavelet Transform (ASWT) filter. The baseline wanders (BW) noise removal from an ECG signals to minimize distortion of the S-T segment of the ECG signal specially that have high sampling frequencies. Therefore, when using Symlet Wavelet Transform (SWT) to analysis the ECG signal can cause problems to analysis, exclusively when examining the content of the ECG signal at low-frequency such as S-T segment. The corresponding frequency components of the approximation coefficients at level number seven are (0-3.9) Hz. Since the BW frequency is below 0.5 Hz and ST segment frequency between (0.67-4) Hz. The adaptive filter with a unity reference signal used to remove the BW noise below 0.5 Hz from the lowest level of the approximation coefficient of the decomposed ECG signal. The denoising output from adaptive filter and the output from SWT (the other detail coefficients) will use as an input to ISWT for reconstruction ECG signals with the remove BW signal. This method represents a very effective filter for BW noise removal, as it does not need for any computation process of reference point.

scholarly journals Novel Stable Capacitive Electrocardiogram Measurement System

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3668
Author(s):  
Chi-Chun Chen ◽  
Shu-Yu Lin ◽  
Wen-Ying Chang
Keyword(s):  
Measurement System ◽  
Input Resistance ◽  
Voltage Divider ◽  
Motion Artifact ◽  
Guard Ring ◽  
Capacitive Sensing ◽  
Ecg Signals ◽  
Optimal Input ◽  
Electrocardiogram Ecg ◽  
Mode Interference

This study presents a noncontact electrocardiogram (ECG) measurement system to replace conventional ECG electrode pads during ECG measurement. The proposed noncontact electrode design comprises a surface guard ring, the optimal input resistance, a ground guard ring, and an optimal voltage divider feedback. The surface and ground guard rings are used to reduce environmental noise. The optimal input resistor mitigates distortion caused by the input bias current, and the optimal voltage divider feedback increases the gain. Simulated gain analysis was subsequently performed to determine the most suitable parameters for the design, and the system was combined with a capacitive driven right leg circuit to reduce common-mode interference. The present study simulated actual environments in which interference is present in capacitive ECG signal measurement. Both in the case of environmental interference and motion artifact interference, relative to capacitive ECG electrodes, the proposed electrodes measured ECG signals with greater stability. In terms of R–R intervals, the measured ECG signals exhibited a 98.6% similarity to ECGs measured using contact ECG systems. The proposed noncontact ECG measurement system based on capacitive sensing is applicable for use in everyday life.

scholarly journals Two Electrode ECG And EOG System For Monitoring Applications

2019 ◽  
Vol 8 (11) ◽  
pp. 262-265
Keyword(s):  
Reference Electrode ◽  
Cost Effective ◽  
Electrode System ◽  
Ecg Signal ◽  
Biomedical Signal ◽  
Ecg Signals ◽  
Arm Position ◽  
The Stability ◽  
Electrocardiogram Ecg ◽  
Total Gain

Heart and Eye are two vital organs in the human system. By knowing the Electrocardiogram (ECG) and Electro-oculogram (EOG), one will be able to tell the stability of the heart and eye respectively. In this project, we have developed a circuit to pick the ECG and EOG signal using two wet electrodes. Here no reference electrode is used. EOG and ECG signals have been acquired from ten healthy subjects. The ECG signal is obtained from two positions, namely wrist and arm position respectively. The picked-up biomedical signal is recorded and heart rate information is extracted from ECG signal using the biomedical workbench. The result found to be promising and acquired stable EOG and ECG signal from the subjects. The total gain required for the arm position is higher than the wrist position for the ECG signal. The total gain necessary for the EOG signal is higher than the ECG signal since the ECG signal is in the range of millivolts whereas EOG signal in the range of microvolts. This two-electrode system is stable, cost-effective and portable while still maintaining high common-mode rejection ratio (CMRR).

scholarly journals Use of Transforms in Biomedical Signal Processing and Analysis

2021 ◽  
Author(s):  
Ette Harikrishna ◽  
Komalla Ashoka Reddy
Keyword(s):  
Wavelet Transforms ◽  
Research Work ◽  
Reference Signal ◽  
Low Frequency ◽  
Motion Artifact ◽  
Motion Artifacts ◽  
Biomedical Signal Processing ◽  
Blood Oxygen Saturation ◽  
Biomedical Signals ◽  
Electrocardiogram Ecg

Biomedical signals like electrocardiogram (ECG), photoplethysmographic (PPG) and blood pressure were very low frequency signals and need to be processed for further diagnosis and clinical monitoring. Transforms like Fourier transform (FT) and Wavelet transform (WT) were extensively used in literature for processing and analysis. In my research work, Fourier and wavelet transforms were utilized to reduce motion artifacts from PPG signals so as to produce correct blood oxygen saturation (SpO2) values. In an important contribution we utilized FT for generation of reference signal for adaptive filter based motion artifact reduction eliminating additional sensor for acquisition of reference signal. Similarly we utilized the transforms for other biomedical signals.

scholarly journals Capturing Electrocardiogram Signals from Chairs by Multiple Capacitively Coupled Unipolar Electrodes

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2835 ◽  
Author(s):  
Zhongjie Hou ◽  
Jinxi Xiang ◽  
Yonggui Dong ◽  
Xiaohui Xue ◽  
Hao Xiong ◽  
...  
Keyword(s):  
Printed Circuit Board ◽  
Experimental Tests ◽  
Circuit Board ◽  
Signal Acquisition ◽  
Ecg Signal ◽  
Capacitively Coupled ◽  
Ecg Signals ◽  
Printed Circuit ◽  
Electrocardiogram Signals ◽  
Electrocardiogram Ecg

A prototype of an electrocardiogram (ECG) signal acquisition system with multiple unipolar capacitively coupled electrodes is designed and experimentally tested. Capacitively coupled electrodes made of a standard printed circuit board (PCB) are used as the sensing electrodes. Different from the conventional measurement schematics, where one single lead ECG signal is acquired from a pair of sensing electrodes, the sensing electrodes in our approaches operate in a unipolar mode, i.e., the biopotential signals picked up by each sensing electrodes are amplified and sampled separately. Four unipolar electrodes are mounted on the backrest of a regular chair and therefore four channel of signals containing ECG information are sampled and processed. It is found that the qualities of ECG signal contained in the four channel are different from each other. In order to pick up the ECG signal, an index for quality evaluation, as well as for aggregation of multiple signals, is proposed based on phase space reconstruction. Experimental tests are carried out while subjects sitting on the chair and clothed. The results indicate that the ECG signals can be reliably obtained in such a unipolar way.

Accurate Detection of ECG Signals in ECG Monitoring Systems by Eliminating the Motion Artifacts and Improving the Signal Quality Using SSG Filter with DBE

2019 ◽  
Vol 29 (02) ◽  
pp. 2050024
Author(s):  
Mahesh B. Dembrani ◽  
K. B. Khanchandani ◽  
Anita Zurani
Keyword(s):  
Signal Analysis ◽  
Motion Artifact ◽  
Motion Artifacts ◽  
Signal Quality ◽  
Ecg Signal ◽  
Qrs Complex ◽  
Ecg Signals ◽  
Cardiac Disorders ◽  
Digital Processor ◽  
Ica Algorithm

The automatic recognition of QRS complexes in an Electrocardiography (ECG) signal is a critical step in any programmed ECG signal investigation, particularly when the ECG signal taken from the pregnant women additionally contains the signal of the fetus and some motion artifact signals. Separation of ECG signals of mother and fetus and investigation of the cardiac disorders of the mother are demanding tasks, since only one single device is utilized and it gets a blend of different heart beats. In order to resolve such problems we propose a design of new reconfigurable Subtractive Savitzky–Golay (SSG) filter with Digital Processor Back-end (DBE) in this paper. The separation of signals is done using Independent Component Analysis (ICA) algorithm and then the motion artifacts are removed from the extracted mother’s signal. The combinational use of SSG filter and DBE enhances the signal quality and helps in detecting the QRS complex from the ECG signal particularly the R peak accurately. The experimental results of ECG signal analysis show the importance of our proposed method.

scholarly journals An Analysis of the Effects of Noisy Electrocardiogram Signal on Heartbeat Detection Performance

2020 ◽  
Vol 7 (2) ◽  
pp. 53
Author(s):  
Ziti Fariha Mohd Apandi ◽  
Ryojun Ikeura ◽  
Soichiro Hayakawa ◽  
Shigeyoshi Tsutsumi
Keyword(s):  
Stress Test ◽  
Hospital Setting ◽  
Detection Performance ◽  
Cardiac Monitoring ◽  
Ecg Signal ◽  
Daily Life Activities ◽  
Detection Algorithms ◽  
Beat Detection ◽  
Electrocardiogram Ecg ◽  
The Relationship

Heartbeat detection for ambulatory cardiac monitoring is more challenging as the level of noise and artefacts induced by daily-life activities are considerably higher than monitoring in a hospital setting. It is valuable to understand the relationship between the characteristics of electrocardiogram (ECG) noises and the beat detection performance in the cardiac monitoring system. For this purpose, three well-known algorithms for the beat detection process were re-implemented. The beat detection algorithms were validated using two types of ambulatory datasets, which were the ECG signal from the MIT-BIH Arrhythmia Database and the simulated noise-contaminated ECG signal with different intensities of baseline wander (BW), muscle artefact (MA) and electrode motion (EM) artefact from the MIT-BIH Noise Stress Test Database. The findings showed that signals contaminated with noise and artefacts decreased the potential of beat detection in ambulatory signal with the poorest performance noted for ECG signal affected by the EM artefacts. In conclusion, none of the algorithms was able to detect all QRS complexes without any false detection at the highest level of noise. The EM noise influenced the beat detection performance the most in comparison to the MA and BW noises that resulted in the highest number of misdetections and false detections.

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