• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.11
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• pp.1605-1610
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• 2015

This study describes a new method to analyze phonocardiogram acquired from electronic stethoscope. The method uses the formant frequencies of linear prediction spectrum of the phonocardiogram and proposes a novel method for formant detection using the smoothing and the first and second derivatives. For this, stethoscope sounds are acquired in university hospital. The stethoscope signals are preprocessed and analyzed by the Burg algorithm, a kind of linear prediction analysis. Based on the linear prediction spectra, the formant frequencies are estimated. The proposed method has shown better performance in formant frequency detection than the conventional peak picking method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.237-240
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• 2009

We suggested the portable measurement system that estimate heart-condition for heart disease patients and healthy. We used informations of ECG and PCG in this system. The informations of ECG and PCG obtained by using electrodes and microphone, respectively.

• 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 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 the Institute of Electronics Engineers of Korea SC
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• v.47 no.1
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• pp.47-55
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• 2010

Although heart auscultation is an important tool for the diagnosis of heart disease, it is seen that the human ear is poorly suited for cardiac auscultation such as the paradoxical split of S2, the split of S2, and the summation of S2 and S3 gallop. In this paper, the analysis-synthesis method that is suitable for the characteristics of PCG is proposed to classify the heart sound. In analyzing the PCG according to matching pursuit method and synthesizing the PCG in each bandwidth based on the frequency characteristics, it sorts normal hearts with abnormal hearts that is difficult to classify as cardiac auscultation. The result shows that it qualifies the appearance of split in S2 and the paradoxical split of S2 and also can estimate the delay between the two components.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.12
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• pp.3001-3008
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• 2013

To diagnose the cardiac valve abnormalities using analysis of phonocardiogram, first of all, accurate detection of S1, S2 components is needed for heart sound segmentation. In this paper, a new method that uses the third moment characteristics of an envelope of the PCG is proposed for accurate detection of S1 and S2 components of the heart sound with cardiac murmurs. The envelope of the PCG is obtained from the short-time energy profile, and its third moment profile with slope information is used for accurate time gating of the S1, S2 components. Experimental results have shown that the proposed method is superior to the conventional second moment method for detection of S1 and S2 regions from the heart sound signals with cardiac murmurs.

• Korean Journal of Veterinary Research
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• v.48 no.4
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• pp.481-487
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• 2008

A 17-month-old intact male Cocker Spaniel was presented with primary complaints of severe ascites, exercise intolerance, and diarrhea. Diagnostic studies revealed tricuspid and pulmonic regurgitation on phonocardiogram, right ventricular enlargement on the electrocardiogram, typical right cardiac enlargement signs on the thoracic radiography and tricuspid valve malformation and marked enlargement of the right atrium and right ventricle on the echocardiography and tricuspid and pulmonary regurgitation on the color spectral echocardiography, suggesting tricuspid valve dysplasia and pulmonary hypertension. Using angiography and cardiac catheterization, pulmonary hypertension was ruled out. Further echocardiographic study revealed membranous valvular structures cranial to pulmonary annulus causing pulmonary regurgitation. Based on these findings on the diagnostic investigation, the case was diagnosed as tricuspid valve dysplasia complicated with pulmonic regurgitation. The dog was medically managed with furosemide, enalapril, nitroglycerine transdermal patch and pimobendan after the ascitic fluid removal.

• Korean Journal of Veterinary Research
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• v.53 no.4
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• pp.263-264
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• 2013

A 6 year-old, spayed female, Maltese dog was presented with precordial thrill and mild coughing. Thoracic auscultation revealed a grade V/VI systolic murmur with maximal intensity over the left apex characterized by musical murmur. Echocardiography revealed mild myxomatous degeneration of mitral valve and ruptured chordae tendineae. Musical murmur was produced due to the vibration of ruptured piece of chordae tendineae along with regurgitant flow. After treatment with furosemide and ramipril, clinical signs resolved and precordial thrill reduced. This case report describes typical clinical signs and phonocardiogram of musical murmur in a dog with acute chordae tendineae rupture.

• Journal of Electrical Engineering and Technology
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• v.10 no.5
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• pp.2126-2134
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• 2015

The present study suggests a localization method for the first (S₁) and the second (S₂) feature of heart sounds, based on an algorithm involving frequency filtering, energy detection, and interval regulation. Localization accuracy was evaluated by comparing the algorithm with the traditional Hilbert transform-based localization method. Results show that the sensitivity and the positive predictivity value of proposed method, respectively, were 97.27 % and 99.94 % in S₁ detection and 94.99 % and 100 % in S₂ detection.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.1045-1048
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• 2000

This paper presents the application of the wavelet transform analysis and the neural network method to the phonocardiogram (PCG) signal. Heart sound is a acoustic signal generated by cardiac valves, myocardium and blood flow and is a very complex and nonstationary signal composed of many source. Heart sound can be discriminated normal heart sound and heart murmur. Murmurs have broader frequency bandwidth than the normal ones and can occur at random position of cardiac cycle. In this paper, we classified the group of heart sound as normal heart sound(NO), pre-systolic murmur(PS), early systolic murmur(ES), late systolic murmur(LS), early diastolic murmur(ED). And we used the wavelet transform to shorten artifacts and strengthen the low level signal. The ANN system was trained and tested with the back- propagation algorithm from a large data set of examples-normal and abnormal signals classified by expert. The best ANN configuration occurred with 15 hidden layer neurons. We can get the accuracy of 85.6% by using the proposed algorithm.