• Journal of Institute of Control, Robotics and Systems
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• v.8 no.8
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• pp.691-697
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• 2002

Myocardial ischemia is a disorder of cardiac function caused by insuficient blood flow to the muscle tissue of the heart. We can diagnose myocardial ischemia by observing the change of ST-segment, but this change is temporary. Our primary purpose is to detect the temporary change of the 57-segment automatically In the signal processing, the wavelet transform decomposes the ECG(electrocardiogram) 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. Amplitude comparison method is adopted to detect QRS complex. Reducing the effect of noise to the minimum, we grouped ECG by 5 data and compared the amplitude of maximum value. To recognize the ECG .signal pattern, we adopted the polynomial approximation partially and statistical method. The polynomial approximation makes possible to compare some ECG signal with different frequency and sampling period. The ECG signal is divided into small parts based on QRS complex, and then, each part is approximated to the polynomials. After removing the distorted ECG by calculating the difference between the orignal ECG and the approximated ECG for polynomial, we compared the approximated ECG pattern with the database, and we detected and classified abnormality of ECG.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.518-521
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• 2007

The functional wireless sensor node for u-healthcare application was developed. The developed sensor node can check the abnormality of ECG in some simple software in ROM of microprocess in the sensor node. The ECG signal is one of very important health signal form human body, and wavelike signal which is sampled as a sampling frequency between 100 and 400 Hz for digitalization, so the wireless data dor ECG signal is some heavy in Zigbee communication. Thus the sensor send the ECG signal to other sensor nodes or base station when it find abnormality in ECG signal is key technology to reduce the traffic between sensor nodes in wireless sensor network for u-healthcare, The sensor node does not need to transmit ECG data all time in wireless sensor network and to server. Using these sensor nodes, the healthcare system can dramatically reduce wireless data packet overload, the power consumption of battery in the sensor nodes and thus increase the reliability of the wireless system.

• Journal of Biomedical Engineering Research
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• v.43 no.6
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• pp.424-433
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• 2022

As the proportion of non-contact telemedicine increases and the number of electrocardiogram (ECG) data measured using portable ECG monitors increases, the demand for automatic algorithms that can precisely analyze vast amounts of ECG is increasing. Since the P, QRS, and T waves of the ECG have different shapes depending on the location of electrodes or individual characteristics and often have similar frequency components or amplitudes, it is difficult to distinguish P, QRS and T waves and measure each parameter. In order to measure the widths, intervals and areas of P, QRS, and T waves, a new algorithm that recognizes the start and end points of each wave and automatically measures the time differences and amplitudes between each point is required. In this study, the start and end points of the P, QRS, and T waves were measured using six Deep Neural Networks (DNN) that recognize the start and end points of each wave. Then, by synthesizing the results of all DNNs, 12 parameters for ECG characteristics for each heartbeat were obtained. In the ECG waveform of 10 subjects provided by Physionet, 12 parameters were measured for each of 660 heartbeats, and the 12 parameters measured for each heartbeat well represented the characteristics of the ECG, so it was possible to distinguish them from other subjects' parameters. When the ECG data of 10 subjects were combined into one file and analyzed with the suggested algorithm, 10 types of ECG waveform were observed, and two types of ECG waveform were simultaneously observed in 5 subjects, however, it was not observed that one person had more than two types.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.4
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• pp.280-287
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• 2008

For the reduction of common-mode noise level in Indirect-contact ECG (IDC-ECG) measurement a driven-right-leg grounding method was a lied to the IDC-ECG. Because the IDC-ECG does not require any direct contact between the electrodes and the human skin. it is adequate for un-constraining long-term ECG measurement at home and its various applications are now under development. However, larger 60 Hz noise induced by power line a ears in IDC-BCG than in conventional ECG, that is a restriction of IDC-ECG a application. In this study, the driven-right-leg ground which has been used in conventional direct-contact ECG, was adapted to the IDC-ECG measurement by feedback of the inversion of amplified common-mode noise to the body through the conductive fertile laid on the chair seat By this study, indirect-contact driven-right-leg ground was developed and it was shown to work stably. It was shown that the level of 60Hz power line noise was reduced to about -40 dB when the driven-right-leg gain was 1000. This study shows that we can extend the upper limit of the frequency band of IDC-ECG to 100Hz from 30Hz which is conventional upper limit in IDC-ECG, and we can raise the ground impedance between the body and conductive textile. So it is expected that the application area of the IDC-ECG will be extended by the results of this study.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.1 no.1
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• pp.7-12
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• 2008

This paper studies a method to minimize the baseline wandering that make hard to extract R-wave in ECG. This method uses a difference signal between ECG and ascending slope tracing waves to minimize the baseline wandering. When the slope of ECG signal maintains the value or falls, the ascending slope tracing wave follows ECG signal directly, and this wave holds that value of ECG signal when the slope begins to rises in a certain time(=hold time). After this hold time, this wave traces ECG signal again. This method has been applied to MIT/BIH database to verify its efficacy and validity in practical applications.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.21 no.8
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• pp.776-781
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• 2008

In this study, ubiquitous health care system attaching in chair to monitor ECG for health care was developed at the unconsciousness state. The system conveniently and simple measured ECG at non-consciousness. We measured the contact impedance to skin-electrode of metal mesh electrodes of the system. Contact impedance enable the electrode to use for ECG measurement. The results are that the impedance of the metal mesh electrodes according to sizes is low when the size is 4$cm^2$. As the result, when the size of the metal mesh electrode is 4$cm^2$, the electrode is fit for ECG measurement. We can acquired by positing the arm on the metal mesh electrode. The ECG signal was detected using a high-input-impedance bio-amplifier, and then passed filter circuitry. The measured signal transmitted to a PC through the bluetooth wireless communication and monitored. Data of the non-constrained ECG system attaching in chair is noise-data when comparing metal mesh electrode with the Ag/Agcl electrode but the data is significant to monitor ECG for check the body state.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.11
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• pp.1141-1148
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• 2016

This paper proposed a heart attack predictive monitoring system using QRS pattern of ECG for wearable healthcare. It detects abnormal heart pattern with a ECG (X, Y) coordinate pattern DB on wearable monitoring smart watch. We showed the acute heart failure prevention system and method with a proposed scheme. Especially, It proved the method which can do first aid in gold time through abnormal heart analysis with a digital ECG(X, Y) pattern information when acute heart failure occurs.

• Journal of Sensor Science and Technology
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• v.21 no.1
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• pp.39-45
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• 2012

Recently the convergence of healthcare technology is used for daily life healthcare monitoring. Cardiac arrhythmia is presented by the state of the heart irregularity. Abnormal heart's electrical signal pathway or heart's tissue disorder could be the cause of cardiac arrhythmia. Fatal arrhythmia could put patient's life at risk. Therefore arrhythmia detection is very important. Previous studies on the detection of arrhythmia in various ECG analysis and classification methods had been carried out. In this paper, an ECG signal processing techniques to detect abnormal ECG based on DTW minimum accumulation distance through the template matching for normalized data and variable threshold method for ECG R-peak detection. Signal processing techniques able to determine the occurrence of normal ECG and abnormal ECG. Abnormal ECG detection algorithm using DTW minimum accumulation distance method is performed using MITBIH database for performance evaluation. Experiment result shows the average percentage accuracy of using the propose method for Rpeak detection is 99.63 % and abnormal detection is 99.60 %.

• Journal of Sensor Science and Technology
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• v.16 no.5
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• pp.361-368
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• 2007

Small size real-time ECG signal analysis function by QRS-complex detection was put into sensor nodes. Wireless sensor nodes attached on the patient’s body transmit ECG data continuously in normal u-healthcare system. So there are heavy communication traffics between sensor nodes and gateways. New developed platform for real-time analysis of ECG signals on sensor node can be used as an advanced diagnosis and alarming system for healthcare. Sensor node does not need to transmit ECG data all the time in wireless sensor network and to server PC via gateway. When sensor node detects suspicion or abnormality in ECG, then the ECG data in the network was transmitted to the server PC for further powerful analysis. This system can reduce data packet overload and save some power in wireless sensor network. It can also increase the server performance.

• Journal of Chest Surgery
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• v.19 no.3
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• pp.363-373
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• 1986

Even though the pathogenesis is still controversial, electrocardiographic changes after congenital open heart surgery depend on various etiologic factors. Author reviewed 261 cases of congenital open heart surgery patient experienced in the Dept. of Thoracic & Cardiovascular Surgery, Pusan National University Hospital, since July, 1981 to Sept., 1985. The results were summarized as followed: 1. The age distribution was from 3 to 29 years old with mean age 10.8 years. And the most frequent congenital heart defect we had done operation was VSD. 2. Preoperatively, the most frequent ECG finding was abnormal QRS complex and postoperatively the most frequent ECG change was arrhythmia. 3. The most frequent arrhythmia before operation was intraventricular conduction disturbance. 4. Right ventriculotomy incision produced the more frequent abnormal ECG changes postoperatively than right atriotomy or pulmonary arteriotomy. 5. According to the operative technique, outflow patch graft of TOF repair produced the highest frequency of ECG changes after operation, and in comparing simple and patch closure of VSD, the latter was higher frequency of ECG changes, in valvotomy and infundibulectomy of PS, the latter was higher too. 6. The common symptom and signs in abnormally ECG changed patients after operation were palpitation, dyspnea, congestive heart failure and murmur in this order., 7. The longer the time of CPB, the more number of abnormally ECG changed patients had been developed after operation. 8. The most of postoperative ECG changed patients recovered spontaneously or with only medication and were clinically insignificant. And the rest other minor group recovered with temporary pacing. Eight cases out of 261 [3.1%], these with abnormal QRS complex and arrhythmia couldn`t recover in spite of every effort and eventually succumbed.