• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.1176-1177
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• 2011

본 논문에서는 모바일 청진기로 언제 어디서나 고령자의 건강상태를 진단할 수 있는 건강 및 질환관리 시스템을 제안하며, 이를 통해 현재의 전문의 중심의 청진기 진료에서 누구나 쉽게 자가진단이 가능한 u-헬스케어 서비스를 제공하고자 한다. 본 시스템은 디지털 청진기와 스마트폰 모바일 어플리케이션을 연동하여 청진신호를 파형으로 시각화하여 사용자가 편리하게 건강상태를 자가진단 할 수 있도록 서비스하며 또한, 웹 서버를 통해 전문의의 상세진단을 받을 수 있다.

• Journal of Navigation and Port Research
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• v.28 no.3
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• pp.239-245
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• 2004

Electrocardiogram and phonocardiogram acquired from ECG and stethoscope by a non-invasive method are bio-signals which laue been a great role in patients diagnosis and used extensively by doctors. And these are mainly used at the examination room or first-and room of hospital. When the patients are located at some places far away from hospital like a car, an airplane and a vessel under way, there are some difficulties in confirming their cardiac sound Especially the patient of ocean going vessel might not have a medical treatment from the professional doctor at times. In this paper, we developed the digital ECG and stethoscope system based on personal computer which can easily measure the patient's cardiac sound and ECG signal, and this might shorten the appearance of the remote maritime telemedicine.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.6
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• pp.62-70
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• 2011

Smart-healthcare service is a health medical service which aims to provide an active consumer-directed service for both wellness and preventative health management upon the basis of rapid diffuse of smartphone which has been occurring recently. On this, this paper suggests a tele auscultation medicine smart-healthcare system based on digital stethoscope which is able through the use of the smart phone which is easy to approach anywhere. The suggested system consists of the digital stethoscope for patient's self auscultation and smart phone, the PC for doctor's examination, and the web server to connect those devices. A telemedicine can be performed between a doctor and a patient by the program which exchanges examine data and auscultation data among the devices. To sum up, by the system suggested in this paper, an easily and conveniently usable health medical service on an everyday basis could be provided without spatial and temporal limits.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.270-272
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• 2022

한의 복진은 복부를 검사하기 위해 수행되지만 정량화되지는 않았다. 이 연구의 목표는 소화불량의 주요 증상인 흉협고만이 있는 그룹과 아닌 그룹 사이에 유의하게 차이나는 복부 측정기기의 변수를 식별하는 것이다. 정량적인 진단을 위해 규칙에 따라 구획한 복부를 적외선 열화상 카메라, 디지털 압통기, 3D 카메라 및 디지털 청진기를 포함한 기기로 측정하였다. 연구방법으로 임상연구를 수행하여 한의사들이 진단한 복부 증상인 흉협고만과의 일치도를 조사하였다. 기기 측정 중 깊이, 압력, 깊이에 대한 압력의 비율은 흉협고만 그룹이 비 흉협고만 그룹보다 유의하게 작았다. 따라서 물리적 압통 특성이 감소하고, 복부 경직도가 감소하며, 민감도가 증가했다. 좌측과 우측 늑골 사이의 거리, 흉늑골 각도는 흉협고만 환자에서 유의하게 더 컸다. 또한, 깊이 차이, 표면 법선 벡터 및 깊이 값 사이의 각도 차이는 흉협고만 그룹에서 대부분 작았다. 복부 측정기기는 다양한 질환 및 증상에 사용될 것으로 기대한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.9
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• pp.722-727
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• 2013

Medical treatment for animals is very difficult as the opinions of pets' masters take priority over treatment regardless of the seriousness of pets' disease or the needs of medical treatment. In case that a pet has heart disease, especially, it is difficult to get the direct answer from the pet's master on the decision or confirmation of treatment. For those reasons, it is almost impossible to predict and treat the pet before an emergency like the heart failure or an unexpected death happens. Using stethoscope can be the first diagnosis method to check the heart or any kinds of disease inside the body. High-tech equipments like CT, X-ray or Ultrasound can be used, but they can only be used as a second choice of diagnosis method since it requires professional skills and its high price. That's why stethoscope is still the best diagnostic tool when one makes the first diagnosis. In this study, we give a detailed account of digital diagnosis system in which veterinarians can analyze the sound from stethoscope without bringing it to their ears and make a diagnosis wherever they are. And we suggest a new concept of diagnosis system surrounding, which shows the relativeness of disease through Level Crossing Rate(LCR) and energy level from the stethoscope sound made in this system.

• Journal of Biomedical Engineering Research
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• v.34 no.4
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• pp.204-211
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• 2013

In this paper, an algorithm for suppressing acoustic noises contained in stethoscope sound is proposed and implemented in real-time using an embedded DSP system. Sound collected by stethoscope is down-sampled and band-pass filtered, and later an NLMS adaptive filter is used to cancel the acoustic noise induced from external noise sources. Also, the unpredictable impulsive noises due to fabric friction and instantaneous tapping are detected using the SD-ROM algorithm, and suppressed using an algorithm approximating the morphology filter. The proposed algorithm was tested using signals collected with a digital stethoscope mockup, and implemented on an ARM920T-based DSP system.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.6
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• pp.237-243
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• 2014

Heart sounds of patient's chest could be heard using an analog stethoscope. However, auscultation of a heart sound can be diagnosed differently by each doctor hearing it. Therefore the condition of each patient is determined by the subjective comments based on the hearing ability of a physician who has years of experience. In this paper, through analysis of heart sound and heart rate of the patient's condition, we will define minutely how to diagnose the condition of patient using a wireless digital stethoscope diagnostic system. And it is possible to perform an objective medical diagnosis by applying LCR (Level Crossing Rate) and to show the relationship of a disease using this system.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.3 no.1
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• pp.3-7
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• 2010

In this study, we developed a circuit device detecting korotkoff sounds of forearm electronic blood pressure monitor by digital signal. In order to test a circuit detecting signal from korotkoff sounds, systolic and diastolic pressure were compared our developed circuit device with the existing forearm electronic blood pressure monitor (Model: SE-7000, Korea). Devices for an experiment composed of a forearm cuff, a stethoscope, an amplifier, a PC with A/D board, etc. Results of korotkoff sounds was similar to a pattern of oscilometric signals from the existing forearm electronic blood pressure monitor. We thought it is possible to measure blood pressures, if blood pressures were detected precisely using signals of korotkoff sounds.

• Journal of Navigation and Port Research
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• v.28 no.5
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• pp.449-454
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• 2004

These days ships medical treatment is under unfavorable circumstances, because there is no professional doctor who can diagnose and treat the patients accurately on the ships. Therefore, ship's telemedicine should be urgently actualized to elevate the crew's my of boarding life and welfare. A purpose of this research is to develope the telemedicine system which can acquire the patient's informations like ECG and phonocardiogram used for the diagnosis and transmit those to the doctors of shore medical center. In this paper, we designed the communication part which could transmit the bio-signals acquired from the developed ship's digital ECG and stethoscope based on personal computer by the INMARSAT Also we inspected data errors through the comparison between the sent and received data And we confirmed the possibility and compatibility of the telemedicine using ship's communication system.

• Journal of Biomedical Engineering Research
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• v.45 no.3
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• pp.109-117
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• 2024

We developed a device that integrates digital otoscope and stethoscope for telemedicine. The integrated device was utilized for the collection of tympanic membrane images and cardiac auscultation data. Data accumulated on the platform server can support real-time diagnosis of heart and eardrum diseases using artificial intelligence. Public data from Kaggle were used for deep learning. After comparing with various deep learning models, the MobileNetV2 model showed superior performance in analyzing tympanic membrane data, and the VGG16 model excelled in analyzing cardiac data. The classification algorithm achieved an accuracy of 89.9% for eardrums data and 100% for heart sound data. These results demonstrate the possibility of diagnosing diseases without the limitations of time and space by using this platform.