• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.285-288
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• 2008

In ubiquitous computing environment the biological signal ECG (Electrocardiogram signal) is usually recorded with noise components. Adaptive interference (or noise) canceller do adaptive filtering of the noise reference input to maximally match and subtract out noise or interference from the primary (signal plus noise) input thereby adaptively eliminate unwanted interference from the ECG signal. Measured Stress ECG (or exercise ECG signal) signal have three major noisy component like baseline wander noise, motion artifact noise and EMG (Electro-mayo-cardiogram) noise. These noises are not only distorted signal but also root of incorrect diagnosis while ECG data are analyzed. Motion artifact and EMG noises behave like wide band spectrum signals, and they considerably do overlapping with the ECG spectrum. Here the multidimensional adaptive method used for filtering which is more effective to improve signal to noise ratio.

• Proceedings of the IEEK Conference
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• 2001.06e
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• pp.89-92
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• 2001

For the diagnosis of arrhythmia in the heart system, the QRS complex of ECG signals is used in many cases. The rejection of the noise in ECG signals is important to acquisition of exact QRS complex. This paper presents some experimental results about instantaneous bandwidth estimation and noise rejection of ECG signals with the purpose of rejection of the 60 Hz power noise and the motion artifacts such as EMG signals and contact noise. ECG signals corrupted by noise are cleaned by using the variable bandwidth filter. For the filtering of ECG signals with noise, the instantaneous bandwidth of the signals is estimated by analysis of time-frequency representation of ECG signal.

• Journal of Biomedical Engineering Research
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• v.13 no.2
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• pp.107-114
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• 1992

An adaptive filter for noise cancellation of ECG Is proposed. An adaptive noise canceller using the least mean squares algorithm Is used to reduce unwanted noise. An adaptive filter for nolse cancella lion minimizes the mean-square error between a primary input and a reference input. A primary input is the noisy ECG, and a reference input is a noise that Is correlated in some way with the noise in the primary input or a signal that is correlated only with ECG in the primary input.

• Journal of Biomedical Engineering Research
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• v.39 no.2
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• pp.103-108
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• 2018

This study reviews the common-mode noise model of indirect-contact ECG measurement which uses capacitive electrode and capacitive ground, and shows the reason of the large common-mode noise in indirect-contact ECG. And then, this study shows driven-right-leg ground in indirect-contact ECG measurement, and reviews how the driven-right-leg ground reduces the common-mode noise. This study then analyzes the relation between the effective area of the indirect-contact ground and the gain of the driven-right-leg circuit. This study introduces the output voltage saturation of the driven-right-leg circuit, which occurs frequently in indirect-contact ECG measurement with the condition of the high ground impedance. This study then shows the effect of the driven-right-leg circuit saturation on the common-mode noise.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.6
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• pp.302-308
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• 2001

SVD(Singular Value Decomposition) filter for the suppression of EMG in multi-lead stress ECG is studied. SVD filter consists of two parts. In the first part, the basis vectors were chosen from the averaged singular vectors obtained from the decomposed noise-free ECG. The singular vector is computed from the stress ECG and is compared itself with basis vectors to know whether the noise exist in stress ECG. In the second part, the existing elimination method is used, when one(or two) channels is(or are) contaminated by noise. But the proposed enhanced SVD filter is used in case of having the noise in the many channels. During signal decomposition and reconstruction, the noise-free channel or the least noisy channel have the weight of 1, the next less noisy channel has the weight of 0.8. In this way, every channel was weighted by decreased of 0.2 in proportion to the amount of the added noise. For the evaluation of the proposed enhanced SVD filter, we compared the SNR computed by the enhanced SVD filter with the standard average filter for the noise-free signal added with artificial noise and the patient data. The proposed SVD filter showed better in the SNR than the standard average filter. In conclusion, we could find that the enhanced SVD filter is more proper in processing multi-lead stress ECG.

• Journal of Korea Multimedia Society
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• v.23 no.3
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• pp.402-411
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• 2020

Power line noise in electrocardiogram signals makes it difficult to diagnose cardiovascular disease. ECG signals without power line noise are needed to increase the accuracy of diagnosis. In this paper, it is proposed DNN(Deep Neural Network) model to remove the power line noise in ECG. The proposed model is learned with noisy ECG, and clean ECG. Performance of the proposed model were performed in various environments(varying amplitude, frequency change, real-time amplitude change). The evaluation used signal-to-noise ratio and root mean square error (RMSE). The difference in evaluation metrics between the noisy ECG signals and the de-noising ECG signals can demonstrate effectiveness as the de-noising model. The proposed DNN model learning result was a decrease in RMSE 0.0224dB and a increase in signal-to-noise ratio 1.048dB. The results performed in various environments showed a decrease in RMSE 1.7672dB and a increase in signal-to-noise ratio 15.1879dB in amplitude changes, a decrease in RMSE 0.0823dB and a increase in signal-to-noise ratio 4.9287dB in frequency changes. Finally, in real-time amplitude changes, RMSE was decreased 0.3886dB and signal-to-noise ratio was increased 11.4536dB. Thus, it was shown that the proposed DNN model can de-noise power line noise in ECG.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.589-592
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• 1998

One of the main techniques for diagnosing heart disease is by examining the electrocardiogram(ECG). The earlier noise reduction techniques can not effectively cancellation complex noise from the noisy ECG such powrline interference, baseline drift, muscle artifact. In this paper, we performed the extrude noise from and recovering the ECG signal using wavelets transform that has recently been applying to various fields.

• Journal of Sensor Science and Technology
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• v.23 no.1
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• pp.7-14
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• 2014

Noncontact electrocardiogram (ECG) measurement using capacitive-coupled technique is a very reliable long-term noninvasive health-care remote monitoring system. It can be used continuously without interrupting the daily activities of the user and is one of the most promising developments in health-care technology. However, ECG signal is a very small electric signal. A robust system is needed to separate the clean ECG signal from noise in the measurement environment. Noise may come from many sources around the system, for example, bad contact between the sensor and body, common-mode electrical noise, movement artifacts, and triboelectric effect. Thus, in this paper, the extended Kalman filter (EKF) is applied to denoise a real-time ECG signal in capacitive-coupled sensors. The ECG signal becomes highly stable and noise-free by combining the common analog signal processing and the digital EKF in the processing step. Furthermore, to achieve ubiquitous monitoring, android-based application is developed to process the heart rate in a realtime ECG measurement.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.1
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• pp.44-49
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• 2012

The indirect-contact ECG measurement is a newly developed method for unconstrained and nonconscious measurement in daily Life. This study is the first step to reducing the large background noise appearing in indirect-contact ECG. This study built the thermal noise model of capacitively coupled active electrode which is used in indirect-contact ECG. The results show that the level of thermal noise estimated by the thermal noise model is much the same as that of actual background noise for the capacitively coupled active electrode alone. By applying the actual electrical properties of a sample cotton cloth to the thermal noise model, the theoretical level of thermal noise in the indirect-contact ECG was estimated. The results also show that the level of op-amp's intrinsic noise is so small that it can be negligible in comparison with thermal noise of resistors. The relationship between the level of thermal noise and the resistance of the bias resistor was derived, and it is the base for the further study how to choice the optimal resistance for the bias resistor.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.11 no.2
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• pp.29-33
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• 2012

ECG widely used in cardiac function test is a graph that is recorded by measuring the electrical impulses occurred in the heart. Normal ECG has the form of similar sections that are repeated, and each section has the information occurred in a heart beat. Thus, In order to make the correct diagnosis, correct grasp of the sections and formed analysis must be done. In this research, a system that detects the sections of ECG is proposed. The system is based on ECG stored in the form of files. The ECG can easily have a noise caused by an outside factor. The noise of ECG is easily caused by external factors. Through a band-pass filter, it can be removed. and then, to get this ECG without a noise, interval detection algorithm using R-peak is applied. The clean, intuitive interface will help the above functions to be used without any difficulties.