• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1918-1919
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• 2007

In this study, dynamic time warping(DTW) is utilized especially for automatically segmenting ECG(Electrocardiogram) signal to extract a periodic time information. For the possible medical application for diagnosing the abnormalities of ECG, the relative metric distance of the warped ECG signals are computed to decide whether the abrupt variations of ECG signal occur or not.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.920-923
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• 2003

An wearable electrocardiogram (ECG) monitoring system is a widely used non-invasive diagnostic tool for ambulatory patient who may be at risk from latent life-threatening cardiac abnormalities. In this paper, we have a portable ECG monitoring system with conductive fiber which was characterized by the small-size and the low power consumption. The system consists of conductive fibers, one-chip microcontroller, ECG preprocessing circuit, and monitoring software to be able to record and analyze in PC. ECG preprocessing circuit is made of pre-amplifier with gain of 10, band-pass filter with bandwidth of 0.5-120Hz and 2.5V offset circuit for A/D conversion. ECG signals obtained by sensor are included with corrupted noises such as a baseline wandering, 60 Hz power noise and interference noise by body movement. For cancellation corrupted noises in signals obtained by conductive fiber, we used the wavelet decomposition of wavelet transforms in MATLAB toolbox.

• 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.

• 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 Biomedical Engineering Research
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• v.35 no.6
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• pp.203-210
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• 2014

Wearable medical device has been a resurgence of interest thanks to the development of technology and propagation of smart phone in recent years. Various types of wearable devices have been introduced and available in market. Capacitive coupled electrode which measures electrocardiogram over cloth is able to be applied wearable device. In previous approaches of capacitive electrode, they need proper pressure for stable contact of the electrode to body surface. However, wearable device that gives pressure on body surface is not suitable for long-term monitoring. In this study, we proposed adhesive polyurethane-based capacitive electrode for patch-type wearable electrocardiogram (ECG) monitoring device. Self-adhesive polyurethane make the electrode and whole system be adhered to the surface of skin without any pressure. The patch-type system is consisted of analog filter, analog-to-digital converter and wireless transmission module and designed to be attached on the body as a patch. To validate the feasibility of the developed system, we measured ECG signal in stable and active state and extracted heart rate. Therefore, we observed skin response after long-term attachment for biocompatibility of the adhesive polyurethane and adhesive strength of it. The result shows the possibility of applying the developed system for ECG monitoring in real-life.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.05a
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• pp.512-515
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• 2001

The heifer electrocardiograph is a widely progressing research which is used in judgement to existence for a heart disease and analyzes electric potential changes of heart movement during continuous living of everyday after attaching to body portable holler recorder for twenty-four hours. In order to obtain electrocardiogram clearly, it must eliminate that 60Hz power line interference, baseline wandering, noise of muscle constriction. In holter electrocardiogram, the most big problem which is recorded signal of ECG(electrocardiogram) is a baseline wandering elimination, which is occurred by rhythm of respiration and muscle constriction of part from attaching to an electrode. Such baseline is roughly irregular wandering and shaking up and down therefore the part of baseline wandering elimination is very important because it is difficult of ECG diagnosis. In this study, it is stabilized baseline wandering in analog part as implementation f real-time signal processing digital filter so it is applicable to analyze patient's heart disease by way of design of baseline wandering elimination system.

• Korean Journal of Veterinary Research
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• v.52 no.3
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• pp.163-167
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• 2012

Mosapride stimulated dietary motility was introduced because of the arrhythmogenic effect of cisapride. Cisapride, 5-HT receptor agonist, induces prolongation of QT interval. Additionally, this condition can raise the possibility of acute, "malignant" arrhythmias such as torsade de pointes. It is hard to find any reports about effects of mosapride on cardiac parameters in dogs. By confirming electrocardiogram (ECG) parameters, the surface extremity leads ECG that was obtained from the four-limb electrodes and which was recorded by an ECG recorder after administration of mosapride 3 mg/kg PO b.i.d, and mosapride 3 mg/kg with itraconazole 5 mg/kg PO b.i.d, respectively. QT interval was shortened on the days of 3, 5, and post-day 1 in both mosapride 3 mg/kg administrated group and mosapride with itraconazole group. Heart rate increased significantly. QTc was slightly prolonged in mosapride administration group and mosapride with itraconazole group. However, all dogs of QTc were in normal variation (150~250 msec). Besides, the dogs showed no side effects reported in human medicine during the administration with these drugs. Although mosapride can increase the heart rate, this study suggest that mosapride may be useful for the dogs with disorders of gastrointestinal motility because of no fatal arrhythmogenic effect inspite of administration with itraconazole in dogs.

• Journal of the Korean Magnetics Society
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• v.23 no.4
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• pp.130-134
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• 2013

The clip-type pulsimeter equipped with a magnetic sensing Hall device and the most popular body sign of the electrocardiogram (ECG) were investigated in order to analyze the pulse wave velocity (PWV). The PWV simultaneously calculated by means of time difference between the maximum peak of ECG pulse wave and the starting point of radial artery pulse wave, and distance difference between the heart position and the radial wrist position. The PWV analyzed from the clinical data was a wider scope of 5~7 m/s with an average value of 6 m/s. By the prediction of blood vessel's elasticity from the analysis of PWV, it may be useful for developing an oriental-western diagnostic medical signal device for a U-health-care system in the future.

• Journal of the Korea Society of Computer and Information
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• v.15 no.12
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• pp.19-26
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• 2010

In this paper, we studied about the Embedded System of the biosignal measurement and analysis to sensibility evaluation in daily life for non-intrusive. This system is two kinds of measuring biosiganls(Electrocardiogram:ECG, Photoplethysmography:PPG) and analyzed by real-time wireless transmission to notebook PC using bluetooth for consistent and reliability of physiological way to assess continuously changing sensibility. Comparative studied of an autonomic nerve system activity ratio on characteristics frequency band of two kinds of biosignal analyzed frequency way using the Fast Fourier Transform(FFT) and Power Spectrum Density(PSD). Also the key idea of this system is to minimize computing of analysis algorithm for faster and more accurate to assess the sensibility, and the result of the visualization using graph. In this paper, we evaluated the analysis system to assess sensibility that measuring various situation in daily life using a non-intrusive biosignal measurement system, and the accuracy and reliability in comparison with difference of result by development analysis system.

• Korean Circulation Journal
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• v.53 no.11
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• pp.758-771
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• 2023

Background and Objectives: Paroxysmal atrial fibrillation (AF) is a major potential cause of embolic stroke of undetermined source (ESUS). However, identifying AF remains challenging because it occurs sporadically. Deep learning could be used to identify hidden AF based on the sinus rhythm (SR) electrocardiogram (ECG). We combined known AF risk factors and developed a deep learning algorithm (DLA) for predicting AF to optimize diagnostic performance in ESUS patients. Methods: A DLA was developed to identify AF using SR 12-lead ECG with the database consisting of AF patients and non-AF patients. The accuracy of the DLA was validated in 221 ESUS patients who underwent insertable cardiac monitor (ICM) insertion to identify AF. Results: A total of 44,085 ECGs from 12,666 patient were used for developing the DLA. The internal validation of the DLA revealed 0.862 (95% confidence interval, 0.850-0.873) area under the curve (AUC) in the receiver operating curve analysis. In external validation data from 221 ESUS patients, the diagnostic accuracy of DLA and AUC were 0.811 and 0.827, respectively, and DLA outperformed conventional predictive models, including CHARGE-AF, C2HEST, and HATCH. The combined model, comprising atrial ectopic burden, left atrial diameter and the DLA, showed excellent performance in AF prediction with AUC of 0.906. Conclusions: The DLA accurately identified paroxysmal AF using 12-lead SR ECG in patients with ESUS and outperformed the conventional models. The DLA model along with the traditional AF risk factors could be a useful tool to identify paroxysmal AF in ESUS patients.