• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.627-628
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• 2017

Recently, the smart health care industry is showing great interest in health due to the rapid rise of the industry, and various devices capable of monitoring health status in daily life are being developed. In this study, we implemented a system to monitor cardiac activity and anomalous signals from cardiac activity measurement in a manner different from conventional electrocardiogram or pulse wave measurement. And, we performed the measurement evaluation on the subject using the implemented heart sound system. As a result, we confirmed the possibility of monitoring cardiac activity during daily life through heart sound measurement.

• Journal of Korea Multimedia Society
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• v.24 no.11
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• pp.1500-1507
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• 2021

Identification and analysis of the first and second heart sounds(S1, S2) is the easiest way for cardiovascular disease prevention and early diagnosis. However, accurate identification is difficult because the heart sound includes organ movement, blood vortex, user experience, and noise influenced by subjective judgment. Therefore, an algorithm to automatically identify the S1 and S2 heart sounds based on blood vessel transit time(VTT) is presented in this paper. According to the experimental results of comparing the algorithm developed for S1 and S2 heart sound analysis with the conventional Shannon energy algorithm in 10 volunteers, it has been proven that the proposed algorithm can automatically identify S1 and S2 heart sounds with higher accuracy than existing algorithms.

• Journal of Korea Multimedia Society
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• v.13 no.7
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• pp.973-982
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• 2010

In this paper, we proposed the single-channel adaptive noise canceller for the enhancement of heart sound (HS) in the auscultation signal. In case of either normal or emergency, a HS diagnosis is difficult due to the various signal source in the chest. Therefore, the HS enhancement is necessary. The conventional active noise canceller(ANC) has two channel, main signal and reference signal. For signal channel, the reference signal in ANC was generated by the proposed HS analyser and BS-Gate based on the characteristic of HS. This reference signal is suitable to the ANC condition. Experimental data were acquisited from MP36, SS30L in BIOPAC Inc., By the experiment, we confirmed that the proposed single-channel ANC was efficient for HS enhancement. And by the comparison with active linear enhancement, it was validate that the proposed ANC is not affected by the variation of a heartbeat.

• 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.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.4
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• pp.753-758
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• 2009

This paper is proposed the hardware structure and signal processing method of the RF-Tag based on heart sound to develop the mobile biomedical information device for the u-healthcare system. The RF-Tag in this study is consisted of a skin temperature sensor, a dynamic microphone for heart sound detection, Bluetooth communication to transmute healthcare data, and pulse period detection algorithm with adaptive gain controller. We experimented to evaluate performance of the RF-Tag in noisy environments. In addition, the RF-Tag has shown the good performance in the results of experiment. If the proposed methods in this study apply to design the u-healthcare device, we will be able to get the exact health data on real time in mobile environments.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.2051-2052
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• 2011

The structural defects of a heart often reflects the sounds that the heart produces. This paper describes heart sound analysis method using Wavelet transform and average Shannon energy. This can extract the features of heart sounds in various disease identify the heart sounds. Experimental results show that the presented method has potential application in detecting various heart diseases.

• The Journal of the Korea Contents Association
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• v.9 no.8
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• pp.158-165
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• 2009

Counselling between a patient and a doctor is crucial in telemedicine. In order for the doctor to examine the patient accurately, it needs an auscultation, at least. Currently, some video conference systems are implemented but it is hard to use them in the case of an cardiac disorder, because the patients suffering from cardiac disorder cannot be examined by a stethoscope over Internet. To solve this problem, the remote counselling service has to support real time transmission of the heart sound of the patient. In this paper, we present a remote counselling system with stethoscope. We also design and implement the system in order for health monitor to connect the patient with his attending physician for the environment of u-healthcare service. The proposed system supports a mobility for doctor and patient by exchanging IP addresses at an user authentication protocol. The system implemented by this paper can be used for cardiac patients in remote clinical setting in the future.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.905-907
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• 1991

One of the general methods to diagnose abnormalities of heart is stethoscopy. This method needs special skill and experiment of doctors and it lacks for objectivity. Electrocardiography(ECG) is another biomedical method which is commonly used to diagnoss abnormalities of heart. The development of PCG is required in recent years to improve objectivity of stethoscopy method. In this paper, PCG is implemented on personal computer and ECG is also included to help the analysis of PCG waveform. Time analysis is used so far, but in this paper the frequency analysis is also considered to improve the accuracy of disgonosis. As future research, recognition of PCG and ECG signal and the Expert System is required to improve the accuracy of diagnosis.

• Proceedings of the KOSOMBE Conference
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• v.1994 no.05
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• pp.96-99
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• 1994

Despite the simplicity of processing, a conventional autocorrelation function(ACF) method for the precise determination of fetal heart rate (FHR) has many problems. In case of weak or noise corrupted Doppler ultrasound signal. the ACF method is very sensitive to the threshold level and data window length. It is very troublesome to extract FHR when there is a data loss. To overcome these problems, the high resolution pitch detection algorithm was adopted to estimate the FHR. This method is more accurate, robust and reliable than the ACF method. With a lot of calculation, however, it is impossible to process real time FHR estimation. This paper is presented a new FHR estimation algorithm for real time processing.