• The Journal of the Acoustical Society of Korea
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• v.8 no.4
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• pp.53-59
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• 1989

A new proposed method can separate heart sounds and lung sounds by the realization of adaptive noise canceler using adaptive lattice Wiener filter in contrast to adaptive transversal LMS filter and high pass filter as before. Lung sounds and ECG signal are detected for this purpose, and especially the second heart sounds are reduced by finding T wave location with a T wave seeking algorithm. As a result, for heart sounds reduction It was found that adaptive transversal LMS filter required 100-200's orders, 75-100's orders In adaptive transversal MLMS filter, and only 10-20's orders in adaptive lattice Wiener filter. Adaptive filtering technique has shown greater accuracy than high pass filtering without loss of low frequency component.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.4
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• pp.715-720
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• 2017

This study tries to analyze morphology and formant frequencies of linear prediction spectra of stethoscope sounds for heart diseased children. For this object, heart diseased stethoscope sounds were collected in the pediatrics of an university hospital. The collected signals were preprocessed and analyzed by the Burg algorithm, a kind of linear prediction analysis. The linear prediction spectra and the formant frequencies of the spectra for the stethoscope sounds for the normal and the diseased children are estimated and compared. The spectra showed outstanding differences in morphology and formant frequencies between the normal and the diseased children. Normal children showed relatively low frequency of F1(the first formant) and small negative slope from F1. VSD children revealed stiff slope change around F1 to F3. Spectra of ASD children is similar with the normal case, but have negative values of F3. F1-F2 difference of the functional murmur children were relatively large.

• Journal of Sensor Science and Technology
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• v.30 no.1
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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.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.6
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• pp.57-63
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• 2012

Effective use of stethoscope is very important for primary clinical diagnosis for the increasing cardiovascular and respiratory disease. This study developed the contact vibration sensor using piezopolymer film which minimizes the ambient noise, and signal processing algorithm was applied for providing better auscultation sounds compare to the existing electronic stethoscopes. Especially, low frequency heart sounds were acquired without distortion, and the quality of lung sounds were improved. Also, auscultating sounds could be transmitted using bluetooth, which made possible to be used for the u-healthcare environment. Results of this study, auscultation of heart and lung sounds, could be applied to the convergence industry of medical and information communication technology through remote diagnosis.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.1
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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.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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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.

• The Journal of the Acoustical Society of Korea
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• v.25 no.3
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• pp.144-150
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• 2006

Clinicians usually use stethoscopic auscultation for the diagnosis of heart diseases. However, the heart sound signal has varying characteristics due to the noise and/or the conditions of the patients. Also, it is not easy for junior clinicians to find the acoustical differences between different kinds or heart sound signals. which may result in errors in the diagnosis. Thus it will be quite useful for the clinicians to make use of an automatic classification system using signal processing techniques. In this paper, we propose to use hidden Markov models in stead of artificial neural networks which have been conventionally used for the automatic classification of heart sounds. In the experiments classifying heart sound signals. we could see that the proposed methods were quite successful in the classification accuracy.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.252-255
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• 2016

The objective of this paper is to find an easier and non-invasive a way of diagnosing heart diseases based on the heart sound, rigidly heart murmurs, recordings from subjects. Although most of the heart sounds can be easily heard, analysis of the findings by auscultation strongly depends on skills and experience of the physician. Therefore, the heart murmur is require quantitative analysis for automatic diagnosis equipment. For a good sound analysis, the noisy component ware filtered. This can be done using Wiener filter. Once the signal is filtered, it can be segmented into its basic components by signal energy using FFT. After segment the heart sound signal, the relative positions of the different heart sound components will be identified and will be used for quantification purposes. We are using murmur energy ratio. The experimental results are fairly good in relation to automatic diagnosis.

• Child Health Nursing Research
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• v.16 no.3
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• pp.211-219
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• 2010

Purpose: The study was done to measure the effects of maternal heart sound on body weight, physiologic reactions (heart rate [HR] and cortisol) and behavioral states of preterm infants. Methods: Thirty-five preterm infants were recruited from a neonatal intensive care unit at a university hospital. Institutional Review Board approval and informed consent were obtained. The infants were assigned to an experimental group (n=18) with an auditory stimulation for 7 days of life, a continuous delivery of maternal heart sound using MP3 attached inside the incubator, or to a control (n=17) without any auditory stimulation. The outcome variables, daily variations in weight, HR and behavioral states, and differences in cortisol were analyzed. Results: There were differences in variations of daily weights (F=3.431, p=.011) and in cortisol (t=3.184, p=.006) between groups, but no difference in variations of daily HR (F=0.331, p=.933) and behavioral states (F=1.842, p=.323). Conclusion: The findings support the safety of continuous maternal heart sound as no changes in HR and behavioral states occurred, and the efficacy as weight increased and cortisol decreased. This auditory simulation may lead to more efficient utilization of energy in preterm infants by consistently providing familiar sounds from intrauterine life and blocking noxious sounds from NICU environments.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.4
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• pp.167-174
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• 2002

This study describes a fetal heart rate(FHR) estimation algorithm using phonogram. Using a phonogram amplifier, various fetal heart sounds are collected in a university hospital. The FHR estimation algorithms consists of a lowpass filter, decimation, envelop detection, pitch detection, and post-processing. The post-processing is the FHR decision procedure using all informations of fetal heart rates. Using the algorithm and other parameters of fetal heart sound, a fetal monitoring software was developed. This can display the original signals, the FFT spectra, FHR and its trajectory. Even though the fetal phonogram amplifier detects the fetal heart sounds well, the sound quality is not so good as the ultrasonography. In case of very week fetal heart sound, autocorrelation of it showed clear periodicity. But two main peaks in one period is an obstacle in pitch detection and peaks are not so vivid. The proposed FHR estimation algorithm showed very accurate and stable results. Since the developed software displays multiple parameters in real time and has convenient functions, it will be useful for the phonogram-style fetal monitoring device.