• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.134-137
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• 2001

A variable bandwidth filter (VBF) is proposed for cleaning signals with known instantaneous bandwidth (IB). Also, the behaviors and the characteristics of the VBF are examined in time-frequency domain (TFD). The proposed VBF clips a noisy signal along the boundaries of IB and rejects noise in the outside of the IB of the signal in TFD. It is possible to construct four kinds of VBF that are low-pass VBF, high-pass VBF, band-pass VBF and band-stop VBF.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2727-2729
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• 2002

In an emergency telemedicine system such as High-quality Multimedia based Real-time Emergency Telemedicine(HMRET) service, it is very important to examine the status of the patient continuously using the multimedia data including the biological signals(ECG, BP, Respiration, $SpO_2$) of the patient. In order to transmit these data real time through the communication means which have the limited transmission capacity. It is also necessary to compress the biological data besides other multimedia data. For the HMRET service, we developed the lossless biological signal compression program in MSVC++ 6.0 using DPCM method and JPEG Huffman table, and tested in an internet environment.

• Proceedings of the KOSOMBE Conference
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• v.1993 no.05
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• pp.63-65
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• 1993

We have done a preliminary study on the detection of ventricular late potentials using high-resolution electrocardiography. We designed a battery powered low-noise ECG amplifier. We used the XYZ lead system and the amplifier provides 3 channels of X, Y, and Z signals with a conventional gain and another 3 channels of the amplitude-limited X, Y, and Z signals with high-gain. 12-bit data acquisition system interfaces the amplifiers to a personal computer for further signal analysis. Beat alignment algorithm was implemented on the low-gain signals to synchronize the signal averaging of the high-gain amplitude-limited signals. We suggest the use of the weighted vector sum of X', Y', and Z' signals based on the SNR of each channel. We speculate that this new method will increase the accuracy of the LP detector at the expense of more complicated hardware.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.343-344
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• 2006

In this paper, the biomedical signal compression method with multi-stage vector quantization is proposed. It utilizes characteristic of wavelet coefficients in which the energy is concentrated on approximation coefficients. The transmitted codebook index consists code vectors obtained by wavelet coefficients of ECG and Error signals from the 1024 block length, respectively. The proposed compression method showed 2.1298% in average PRD and 1.8 kbits/sec in CDR.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.05
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• pp.3-5
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• 1996

Electrogastrography(EGG) is the technique by which gastric myoelectrical activity is recorded noninvasively, from electrodes on the abdominal skin. This gastric myoelectrical activity consists of two type signals : 1) slow wave, which is gastric basal rhyemic activity and is not closely related to gastric contraction 2) spike wave, which is generated only during contraction of the stomach. Despite many attempts made over the decades, analysis of surface EGG has not led to identification of the spike wave (gastric contraction) that would help the clinician to diagnose functional or organic diseases of the stomach. In this paper, we propose a feasible methods to detect gastric contraction by frequency-domain signal analysis of surface ECG signal. Synchronous measurement of gastric pressure by the antropyloric manometry with surface EGG established feasibility of this method.

• The Journal of Information Technology
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• v.9 no.1
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• pp.9-19
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• 2006

Medications or conitive-behavior methods have been mainly used as a treatment of alcoholism. lately the virtualy technology has been applied to the kink of alcoholic disorders. A virtual environment makes him having avility to over come the drink. In this study, we were implemented by making panorama images and 3D object modules using 3D MAX, VRML, JAVA. And the BAR stimulator that composed with a position sensor, head mount display, and audio system, is suggested. To illustrate the physiological difference between a person who has a alcoholism and without a liquor bottle, heart rate was measured during experiment, and also measured a person's HR after the virtual reality training. The system measures the Physiological signals such as ECG, Temperature, analyzes those data automatically. The system has two parts, one is physiological data acquisition part which gets the body signal, and the other one is mobile nuit which includes signal processing and transmission functions, And Bluetooth allows two parts to communicate with each other. we demonstrated the subjective effectiveness of virtual reality psychotherapy through the clinical experiment.

• Journal of information and communication convergence engineering
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• v.19 no.2
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• pp.93-101
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• 2021

Cardiac arrhythmias are common heart diseases and generally cause sudden cardiac death. Electrocardiogram (ECG) is an effective tool that can reveal the electrical activity of the heart and diagnose cardiac arrhythmias. We propose detection of P waves based on QRST cancellation zero-one substitution. After preprocessing, the QRST segment is determined by detecting the Q wave start point and T wave end point separately. The Q wave start point is detected by digital analyses of the QRS complex width, and the T wave end point is detected by computation of an indicator related to the area covered by the T wave curve. Then, we determine whether the sampled value of the signal is in the interval of the QRST segment and substitute zero or one for the value to cancel the QRST segment. Finally, the maximum amplitude is selected as the peak of the P wave in each RR interval of the residual signal. The average detection rate for the QT database was 97.67%.

• Journal of the Korea Fashion and Costume Design Association
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• v.12 no.2
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• pp.119-129
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• 2010

오늘날 인간의 수명이 연장되고, 웰빙과 건강에 대한 관심이 증가됨에 따라서 언제 어디서나 건강을 모니터링 할 수 있는 건강 스마트 의류 시스템이 개발되고 있다. 이를 위하여 최근에는 생체신호의 모니터링이 가능하도록 디자인된 의류에 통합된 형태의 직물 전극이 개발되고 있다. 혁신적으로 의류 시스템에 통합되어 착용 가능한 니트, 우븐, 자수방식의 텍스타일 전극에 대한 다양한 연구가 개발 제시되고 있으며, 이의 일부는 상용화되어 있다. 이에 본 연구는 경위사의 일정한 직조제어 자동화 시스템이 가능한 컴퓨터 자카드 직기의 캐드(CAD) 직조디자인 방식을 통하여 생체신호 센싱 기능이 향상된 새로운 텍스타일 전극디자인을 연구하고자 하였다. 이를 위하여 본 연구에서는 기존 생체신호 센싱 전극의 개발 및 연구 동향, 비직물/전극 타입에 대한 단점과 장점에 대한 비교 분석을 이론적으로 살펴보고, 자카드 직조 직물 기반으로 심전도 센싱용 텍스타일 전극을 디자인하여 실험 연구하였다. 자카드 직조 방식의 심전도 센싱용 직물 전극은 전극 인터페이스 디자인 방식, 이중직물형 직조 디자인 방식, 사가공 등의 요인들을 고려하여 개발하였다. 본 연구에서 도출된 최종 자카드 직조 직물 기반의 텍스타일 전극은 스마트 의류에 통합시킨 텍스타일 전극 모듈로서 적용되여 향후 상용화 방안을 모색할 수 있다.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.3
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• pp.87-93
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• 2015

The accidents caused by drivers while driving are considered as the major causes along with other causes such as conditions of roads, weather and cars. In this study, we investigated the driver's workloads under three different driving conditions (Weather, Driving time zone, and Traffic density) through analyzing biological signals obtained from a car driving simulator system. The proposed method is able to detect R waves and R-R interval calculation in the ECG. Heart rate variability (HRV) was investigated for the time domain to determine the changes in driver's conditions.

• Journal of Biomedical Engineering Research
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• v.30 no.4
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• pp.294-305
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• 2009

The bio signals essentially have different characteristics in each person. And the main purpose of automatic diagnosis algorithm based on bio signals focuses on discriminating differences of abnormal state from personal differences. In this paper, we propose automatic ECG diagnosis algorithm which discriminates normal heart beats from premature ventricular contraction using optimization of wavelet parameterization to solve that problem. The proposed algorithm optimizes wavelet parameter to let energy of signal be concentrated on specific scale band. We can reduce the personal differences and consequently highlight the differences coming from arrhythmia via this process. The proposed algorithm using ELM as a classifier show high discrimination performance between normal beat and PVC. From the experimental results on MIT-BIH arrhythmia database the performances of the proposed algorithm are 98.1% in accuracy, 93.0% in sensitivity, 96.4% in positive predictivity, and 0.8% in false positive rate. This results are similar or higher then results of existing researches in spite of small human intervention.