• 센서학회지
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• 제30권1호
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• pp.47-50
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• 2021

Human hearing sensitivity is frequency-dependent. The sensitivity is low at both ends of the audible frequency, and the sensitivity is the highest in the middle band at 3000 Hz. The heart sound of a healthy person is concentrated at a low frequency of 200 Hz or less, and despite using a stethoscope, the hearing sensitivity of the human body is low, and the stethoscope sound is low. Amplifying the sound of the stethoscope is not effective in distinguishing heart sounds in noisy environments because it maintains the same signal-to-noise ratio. In this study, a method of enhancing auditory stimulation was developed by applying a method of moving the spectrum of auscultation sounds into a high-frequency region where the human body is highly sensitive to hearing. The spectrum of the auscultation sound was moved up by 500 Hz in the frequency domain, and an inverse fast Fourier transform (FFT) was performed to reconstruct the auscultation sound. The heart sounds reconstructed by moving the spectra were divided into the first heart and second heart sound components, as in the original heart sound, and it was confirmed that the intensity was large in the cochleagram representing auditory stimulation. Therefore, this study suggested that spectral shift is a method to enhance auditory stimulation during auscultation without increasing the intensity of the auscultation sound.

• 융합신호처리학회논문지
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• 제2권1호
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• pp.108-112
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• 2001

Heart sound contains rich information regarding the dynamics of the heart and the auscultation has been a first choice of routine procedures for diagnosis of the heart. However, heart sounds captured using a conventional stethoscope are not often loud or clear enough for doctors to precisely classify their characteristics, especially, under the noisy environments of the hospital. A simple auscultation device that removed shortcomings of the conventional stethoscope was constructed in the study. The device employed a polymer based adherent differential output sensor which was on contact with skin through a coupling medium and appropriated electronic circuits for signal amplification and conditioning An ordinary headphone is taken to hear the captured heart sounds and the volume can be adjusted to hear well. It is also possible that the device sends the captured heart sound signals to a PC where the signals are further processed and viualized.

• 동의생리병리학회지
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• 제28권5호
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• pp.478-485
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• 2014

In order to the excellent differentiation of syndromes, we study on the individual characteristic factor by the inspection of face colour and tongue & the auscultation and olfaction. To the subject of diagnosis special books and diagnostics textbook of korean medicine, we arrange the individual characteristic factor by the inspection of face colour and tongue & the auscultation and olfaction. The inspection on the individual characteristic factor was analyzed the face colour, inspection of tongue. The auscultation and olfaction on the individual characteristic factor was analyzed the 25 types by the five-voice (五音) in Huang Di Nei Jing (黃帝內經). As the results, the individual characteristic factor is very important item of the four methods of diagnosis and the differentiation of syndromes. And Therefore the process on four methods of diagnosis and differentiation of syndromesis is necessary to divide the signs of individual characteristic factor and the signs of disease.

• Tuberculosis and Respiratory Diseases
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• 제86권4호
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• pp.251-263
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• 2023

The stethoscope has long been used for the examination of patients, but the importance of auscultation has declined due to its several limitations and the development of other diagnostic tools. However, auscultation is still recognized as a primary diagnostic device because it is non-invasive and provides valuable information in real-time. To supplement the limitations of existing stethoscopes, digital stethoscopes with machine learning (ML) algorithms have been developed. Thus, now we can record and share respiratory sounds and artificial intelligence (AI)-assisted auscultation using ML algorithms distinguishes the type of sounds. Recently, the demands for remote care and non-face-to-face treatment diseases requiring isolation such as coronavirus disease 2019 (COVID-19) infection increased. To address these problems, wireless and wearable stethoscopes are being developed with the advances in battery technology and integrated sensors. This review provides the history of the stethoscope and classification of respiratory sounds, describes ML algorithms, and introduces new auscultation methods based on AI-assisted analysis and wireless or wearable stethoscopes.

• 융합신호처리학회 학술대회논문집
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• 한국신호처리시스템학회 2000년도 하계종합학술대회논문집
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• pp.185-188
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• 2000

Heart sound contains rich information regarding the dynamics of the heart and the auscultation has been a first choice of routine procedures for diagnosis of the heart. However, heart sounds captured using a conventional stethoscope are not often loud or clear enough for doctors to precisely classify their characteristics, especially, under the noisy environments of the hospital. A simple auscultation device that removed shortcomings of the conventional stethoscope was constructed in the study. The device employed a polymer based adherent differential output sensor which was on contact with skin through a coupling medium and appropriated electronic circuits for signal amplification and conditioning. An ordinary headphone is taken to hear the captured heart sounds and the volume can be adjusted to hear well. It is also possible that the device sends the captured heart sound signals to a PC where the signals are further processed and viualized.

• 대한수의사회지
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• 제31권6호
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• pp.393-398
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• 1995

• 전자공학회논문지CI
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• 제48권6호
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• pp.62-70
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• 2011

스마트-헬스케어 서비스(smart-healthcare service)는 최근에 급속히 보급되고 있는 스마트폰(smart phone)을 기반으로 예방적 건강관리와 웰니스(wellness)를 위한 수요자 중심의 능동적 서비스 제공을 목표로 하는 보건의료서비스이다. 이에 본 논문에서는 언제, 어디서든 손쉽게 접근할 수 있는 스마트폰을 바탕으로 한 디지털청진기 기반의 원격청진진료 스마트-헬스케어 시스템을 제안한다. 제안하는 시스템은 환자가 자가 측정을 하기 위한 디지털청진기와 스마트폰, 환자를 진찰하기 위한 의사용 PC, 그리고 단말들을 연결해주기 위한 네트워크 웹서버로 구성되며, 단말들 간에 청진 데이터와 진찰 데이터를 주고받을 수 있는 프로그램을 통하여 환자와 의사간에 원격진료를 수행할 수 있다. 결과적으로 본 논문에서 제안한 시스템으로는 환자에게 시 공간적 제약 없이, 일상생활에 밀접히 접근하여 손쉽고 편리하게 이용할 수 있는 보건의료서비스를 제공 할 수 있었다.

• Computers and Concrete
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• 제4권3호
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• pp.243-257
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• 2007

A novel method for recognition, characterization, and quantification of deterioration in bridge components and laboratory concrete samples is presented in this paper. The proposed scheme is based on grey level co-occurrence matrix texture analysis using Haar's discrete wavelet transform on concrete imagery. Each image is described by a subset of band-filtered images containing wavelet coefficients, and then reconstructed images are employed in characterizing the texture, using grey level co-occurrence matrices, of the different types and degrees of damage: map-cracking, spalling and steel corrosion. A comparative study was conducted to evaluate the efficiency of the supervised maximum likelihood and unsupervised K-means classification techniques, in order to classify and quantify the deterioration and its extent. Experimental results show both methods are relatively effective in characterizing and quantifying damage; however, the supervised technique produced more accurate results, with overall classification accuracies ranging from 76.8% to 79.1%.

• 한국산학기술학회논문지
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• 제10권10호
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• pp.2708-2714
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• 2009

언어를 통한 의사 전달 능력이 부족한 영아나 소아들은 울음으로서 자신의 몸의 상태나 요구하는 것에 대한 의사 표시를 행한다. 이 중 중요한 것이 소아 상태를 나타내는 것인데 언어 전달 능력이 없는 소아들의 질병은 진단 시기를 놓치거나 정확한 진단 결과를 내리기 어려운 문제가 존재한다. 이를 위해 본 연구에서는 소아의 울음소리를 분석하여 몸의 어느 부위가 문제가 있는지를 판단해 내는 소아 청진 시스템을 개발하였다. 특히 본 논문에서는 울음소리의 피치, 강도 및 스펙트럼 분석을 통해 소아 선천성 심질환자에 대한 질병 진단을 수행하였다. 이를 위해 각각의 분석 요소를 통해 정상적인 아이와 소아 선천성 심질환을 앓고 있는 아이에 대한 울음소리의 비교, 분석을 수행하였다. 이와 같은 방법을 통해 의사표현 능력이 부족한 소아를 대상으로 편리하게 소아 선천성 심질환을 진단할 수 있으며 임상 자료의 추가 실험을 통해 울음소리 기반의 재택형 진단 시스템을 구축할 수 있다.

• 센서학회지
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• 제22권2호
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• pp.136-143
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• 2013

In the study, novel blood pressure estimation method was proposed to improve the accuracy of oscillometric method. The proposed algorithm estimated the blood pressure by comparing and analyzing the point variation aspect of dicrotic notch on pulsating waveform during each cardiac cycle. The waveforms of each cardiac cycle were extracted by maximum points. The extracted pulsating waveforms were applied by re-sampling, end-matching, and normalization. The systolic and diastolic blood pressures were estimated by point variation aspect of dicrotic notch. The blood pressures, which were estimated from proposed algorithm, were compared and analyzed by blood pressures from oscillometric methods and auscultation. The systolic blood pressure from oscillometric methods were +0.88 mmHg more than proposed algorithm, and 1.875 less than the diastolic blood pressures from proposed algorithm. The systolic and diastolic blood pressures from auscultation were 2.89 mmHg and 3.44 mmHg less than the blood pressures from proposed algorithm. As the errors between blood pressures from proposed algorithm, oscillometric method and auscultation were less than 5 mmHg, the proposed algorithm was effective.