• Journal of Biomedical Engineering Research
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• v.24 no.2
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• pp.107-112
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• 2003

This paper describes a new simple QRS detection algorithm using index function based on resonance theory. The ECG signal can be modeled with several sinusoidal pulses and its first difference has some relations with the amplitude and frequency of sinusoidal pulse. Based on above fact, an index function, similar to the square of the imaginary part of a simple R-L-C circuit, was designed. A QRS complex is detected by applying the adaptive method to the response of index function. The algorithm showed a performance comparable to or higher than the other algorithms. Because it does not require any complicated preprocessing or postprocessing, it can be implemented in real time.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.07a
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• pp.355-356
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• 2013

심장의 활동을 전기적 변위로 표현되는 심전도 신호는 심장병 진단에 중요한 임상적 파라미터들을 제공한다. 특히 심전도 신호에서 P, QRS Complex,, T 특징점들로 대표되는 파형 변곡점들의 시간상 위치와 크기 및 형태학적 모양은 심장의 이상 리듬을 나타내는 부정맥여부를 검출하는데 핵심적인 역할을 한다. 본 연구에서는 특히 QRS complex 구간에 대한 첨도치의 연산 해석을 통하여 정상적인 심전도 리듬과 심실조기수축 부정맥 리듬을 구분하는 방법을 제시하고 또한 스마트폰을 기반으로 하는 심전도 모니터링 시스템에 적용하고자 하였다.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.55.4-55
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• 2001

Analyzing the ECG signal, we can find heart disease. Myocardial ischemia is a disorder of cardiac function caused by insufficient blood flow to the muscle tissue of the heart. Myocardial ischemia is inscribed on ST-segment of the ECG during and after patient takes exercise or is under stress, but after long time past, the ECG pattern is return to steady state. Therefore, it is necessary to monitor and analyze the ECG signal continuously for patient or aged people. Our primary purpose is the detection of temporary change of the ST-segment of ECG automatically. In the signal processing, the wavelet transform decomposes the ECG signal into high and low frequency components using wavelet function. Recomposing the high frequency bands including QRS complex, we can detect QRS complex more easily ...

• 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 information and communication convergence engineering
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• v.5 no.1
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• pp.7-11
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• 2007

The aim of this paper is to design and implement a new ECG signal monitoring and analysis method for the home care of elderly persons or patients, using wireless sensor network (WSN) technology. The wireless technology for home-care purpose gives new possibilities for monitoring of vital parameter with wearable biomedical sensors and will give the patient freedom to be mobile and still be under continuously monitoring. Developed platform for portable real-time analysis of ECG signals can be used as an advanced diagnosis and alarming system. The ECG features are used to detect life-threatening arrhythmias, with an emphasis on the software for analyzing the P-wave, QRS complex, and T-wave in ECG signals at server after receiving data from base station. Based on abnormal ECG activity, the server transfer diagnostic results and alarm conditions to a doctor's PDA. Doctor can diagnose the patients who have survived from arrhythmia diseases.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.213-216
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• 1996

In this research we would like to develop an exercise ECG signal analysis algorithm using the wavelet transform, which is possible to analyze the time and the frequency simultaneously. Wavelet transform has an advantage of dividing the nonstationary signals into the high frequency and low frequency band successively. Thus, it can separates the unnecessary noises from the frequency band of QRS complex and then using the selected frequency band we could detect the QRS complex and ST segment.

• Clinical and Experimental Pediatrics
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• v.51 no.11
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• pp.1232-1235
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• 2008

Imipramine, a tricyclic antidepressant (TCA), is used for the treatment of non-polar depression and nocturnal enuresis in children in whom an organic pathology has been excluded, anxiety disorders, and neuropathic pain. Clinical toxicity following the treatment of TCAs, including imipramine, is well known. The anticholinergic effects initially present include a dry mouth, ileus, dilated pupils, urinary retention, and mild sinus tachycardia. The central nervous system toxicity includes delirium, agitation, restlessness, hallucinations, convulsions, and CNS depression or coma. However, the most life-threatening toxicity remains the development of cardiac dysrhythmias. Conduction delays such as QRS and corrected QT prolongation, wide QRS complex tachycardia, and the Brugada electrocardiographic pattern have been reported. Sodium bicarbonate decreases QRS widening and suppresses dysrhythmias by providing excess sodium to reverse the TCA-induced sodium-channel blockade and possibly by binding directly to the myocardium. There are no pediatric case reports on imipramine or other TCA associated toxicity in Korea. Here, we describe a patient who presented with convulsions, tachycardia with a wide QRS complex, a Brugada electrocardiographic pattern, and anuresis associated with an accidental overdose of imipramine and the outcome of treatment with sodium bicarbonate.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.6
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• pp.1215-1221
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• 2009

A novel approach for electrocardiogram (ECG) analysis within a functional sensor node has been developed and evaluated. The main aim is to reduce data collision, traffic overload and power consumption in healthcare applications of wireless sensor networks(WSN). The sensor node attached on the patient's body surface around the heart can perform ECG analysis based on a QRS detection algorithm to detect abnormal condition of the patient. Data transfer is activated only after detected abnormality in the ECG. This system can reduce packet loss during transmission by reducing traffic overload. In addition, it saves power supply energy leading to more reliable, cheap and user-friendly operation in the WSN for ubiquitous health monitoring.

• Journal of Korea Multimedia Society
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• v.19 no.6
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• pp.1034-1042
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• 2016

The detection of P-waves and T-wave in the electrocardiogram signal analysis is an important issue. But the accuracy of the boundary detection algorithm is an insufficient level in the change of slow transition in the signal compared to the QRS complex. This study proposes an algorithm to detect P-wave and T-wave sequentially after determining local baseline using QRS complex. First, we detected the peak points based on local baseline and determined the onset and offset through the calculation of the area of the section. After modifying the baseline using detected waveform, we detected the other waveform in the same way and separated the P-wave and the T-wave based on the location. We used the PhysioNet QT database to evaluate the performances of the algorithm, and calculate the mean and the standard deviations. The experiment results show that standard deviations are under the tolerances accepted by expert physicians, and outperform the results obtained by the other algorithms.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.4
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• pp.406-412
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• 2009

ECG is used on purpose to keep good health or monitor cardiac function of aged person as well as on purpose to diagnose the disease of heart patients. The ambulatory ECG monitoring system under guarantee of safety and accuracy is very efficient to prevent the progress of heart disease and sudden death. These systems can detect the temporary change of ECG that is very significant to diagnose heart disease such as myocardial ischemia, arrhyamia and cardiac infarction. In this paper, we describe the ECG signal analysis algorithm and measurement device for ECG monitoring. The authors designed a small-size portable ECG device that consisted of instrumentation amplifier, micro-controller, filter and RF module. The device measures ECG with four electrodes on the body and detects QRS complex and ST level change in realtime. Also it transmits the measured signals to the personal computer. The developed software for ECG analysis in personal computer has the function to detect the feature points and ST level changes.