• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.75-78
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• 1997

In this paper we present new sound spectral analysis methods or prosthetic heart valve sounds. Phonocardiograms(PCG) of prosthetic heart valve were analyzed in order to derive frequency domain feature suitable or the classification of the valve state. The fast orthogonal search method and MUSIC (MUltiple SIgnal Classification) method are described or finding the significant frequencies in PCG. The fast orthogonal search method is effective with short data records and cope with noisy, missing and unequally-spaced data. MUSIC method's key to the performance is the division of the information in the autocorrelation matrix or the data matrix into two vector subspaces, one a signal subspace and the other a noise subspace.

• The Journal of the Acoustical Society of Korea
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• v.26 no.4
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• pp.144-152
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• 2007

Conventional research works on the classification of the heart sound signal have been done mainly with the artificial neural networks. But the analysis results on the statistical characteristic of the heart sound signal have shown that the HMM is suitable for modeling the heart sound signal. In this paper, we model the various heart sound signals representing different heart diseases with the HMM and find that the classification rate is much affected by the clustering of the heart sound signal. Also, the heart sound signal acquired in real environments is a continuous signal without any specified starting and ending points of time. Hence, for the classification based on the HMM, the continuous cyclic heart sound signal needs to be manually segmented to obtain isolated cycles of the signal. As the manual segmentation will incur the errors in the segmentation and will not be adequate for real time processing, we propose a variant of the ergodic HMM which does not need segmentation procedures. Simulation results show that the proposed method successfully classifies continuous heart sounds with high accuracy.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.38 no.5
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• pp.59-69
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• 2001

Recently many researches concerning heart sound analysis are being processed with development of digital signal processing and electronic components. But there are few researches about recognition of heart sound, especially full cardiac cycled heart sound, In this paper, a new recognition methods about. full cardiac cycled heart sound was proposed. For the first, the database was built by principal components analysis on training heart sound set. This database is used to recognize new input of heart sound, Ilear sounds were classified into seven classes such as normal(NO) class, pre-systolic murmurr(PS) class, early systolic murmur(ES) class, late systolic murmurr(LS) class, early diastolic murmur(EI) class, late diastolic murmur(LD) class and continuous murmuru(CM) class. As a result, we could verify that our new method has better efficiencies for the recognition the characteristics of heart sound than any precedent research. The maximum recognition rates of the new method are 71% for NO, 80% for PS and ES, 78% for LS, 87% for ED, 60% for LD and 20% for CM. Although the present results aren't practically sufficient to use our new method in recognizing heart sound, the importance of this paper is for recognition of heart sound within full cardiac cycle. We can get a better result by building a more efficient database.

• Journal of Physiology & Pathology in Korean Medicine
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• v.22 no.3
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• pp.516-527
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• 2008

Sounds and music have been used in various ways in the East and the West, as it is well known that they influence the human mind and health a lot. Recently, there have been many studies regarding the remedy through sounds and music in the West and they have made good effects in the actual therapy. In the East, people knew that sounds and music would make great effects on human mind long time ago and they placed importance on sounds and music. Although there is a Sound Therapy in Oriental Medicine, it is not studied sufficiently in modern Oriental Medicine. It does not have clear standards for the clinical application and has not been frequently used. Accordingly, Yukjagyeol which has long been used in Korean Medicine and Younggamudo which was made by Kim Il-bu in late Chosun were compared from the perspective of acoustics and demonstrative treatment theory of Korean Medicine. Younggamudo by Kim il-bu allot the five sounds such as 'Eum, Ah, Eo, Ih and Uh' to 'spleen, lung, liver, heart and kidney' respectively. As the five sounds are all vowels and vibrate the vocal band as much as possible, they vibrate and resonant the respective organs to help them to function and promote circulation. In oriental medicine, there is 'Singing and Dancing Treatment'. They say songs and dances nurtures personality, supplement blood stream and comfort the mind. As the five sounds of Younggamudo take the melody while vibrating the vocal band sufficiently, when it passes from Youngto Ga(Songs) we may dance moving our bodies according to the rhythm. Therefore Gongbeop of Younggamudo helps the functionality of human organs and promotes blood circulation. As Yukjagyeol is Sabeop(discharging method), it should be used for those who have surplus Sagi and should not use for Heojeung. As Younggamudo is Bobeop(supplementing method), it is not for Shiljeung but for Heojeung which lacks of Jeonggi. It is considered that healthy people without specific disease can use it as a preventive method of 'Chimijeong' to maintain their physical and mental health. It is considered that we can have useful effects if we apply Yukjagyeol and Younggamudo dialectically with the concept of Bosa. It is considered that concrete application to Sound Gigong can be possible by searching for the methodology for empirical further study and clinical experiments and clinical application in the future.

• The Journal of Korean Medicine
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• v.40 no.1
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• pp.99-113
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• 2019

Objectives: This study is designed to identify the responses of autonomic nervous system and gastrointestinal function which are induced by acupuncture at abdominal anterior cutaneous nerve. Methods: This study is one group before and after pilot study. Subjects were treated once, after having been fasting six hours. They had before tests, labeling points for acupuncture, acupuncture, and after tests in order. The points of acupuncture were motor points of rectus abdominis where the abdominal anterior cutaneous nerve came to the skin from abdominal wall. Before and after tests were consisted of three things: Digital Infrared Thermographic Imaging(D.I.T.I.), Heart Rate Variability(HRV), and Recording of bowel sounds. Results: There were significant differences on the skin temperature of upper body and the frequency of bowel sounds(p<0.001, p<0.001). The HRV parameters and volume of bowel sounds had no significant differences(p>0.05, p>0.05). Conclusion: Even though no significant differences in HRV parameters, the significant differences of skin temperature of upper body and frequency of bowel sounds could mean acupuncture at abdominal anterior cutaneous nerve could affect the autonomic nervous system and gastrointestinal function. However, this study had no group to compare with. Future randomized project should address this issue.

• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.131-134
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• 1999

This paper considers the acoustical characteristics of the mechanical valve employed in the Korean type Artificial Heart. $Bj\"{o}rk-Shiley$ tilting disc valve was chosen for the study and acoustic measurements were performed for the artificial heart operated in a mock circulation system as well as implanted to an animal as a Bi Ventricular Assist Device (BVAD). In the mock system, three different conditions of the valve were examined which were normal, damaged (torn off), pseudothrombus attached. Microphone measurements for the BVAD were carried out at a regular time interval for 5 days after the implantation operation. Of the recorded acoustic emissions from the artificial heart, click sounds mainly originated from the valves were further analyzed using Multiple Signal Classification (MUSIC) for estimating their spectral properties. It was shown that the spectral peaks below 4 kHz and the optimal order number for MUSIC, equivalent to the number of the spectral component, might be the key parameters which were highly correlated to the physiological states of the valve like the mechanical damage of the valve or the formation of thrombus on the valves.

• 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.

• The Journal of the Acoustical Society of Korea
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• v.28 no.1
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• pp.32-43
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• 2009

In this paper, we improve the performance of cardiac disorder classification by continuous heart sound signals using automatic segmentation and extreme learning machine (ELM). The accuracy of the conventional cardiac disorder classification systems degrades because murmurs and click sounds contained in the abnormal heart sound signals cause incorrect or missing starting points of the first (S1) and the second heart pulses (S2) in the automatic segmentation stage, In order to reduce the performance degradation due to segmentation errors, we find the positions of the S1 and S2 pulses, modify them using the time difference of S1 or S2, and extract a single period of heart sound signals. We then obtain a feature vector consisting of the mel-scaled filter bank energy coefficients and the envelope of uniform-sized sub-segments from the single-period heart sound signals. To classify the heart disorders, we use ELM with a single hidden layer. In cardiac disorder classification experiments with 9 cardiac disorder categories, the proposed method shows the classification accuracy of 81.6% and achieves the highest classification accuracy among ELM, multi-layer perceptron (MLP), support vector machine (SVM), and hidden Markov model (HMM).

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.1
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• pp.14-19
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• 2018

Recently, the smart health care industry has been rising rapidly and interest and efforts for public health have been greatly increased. As a result, the public does not visit medical specialists and medical facilities, but the desire to check their health condition in everyday life is increased. Therefore, many domestic and foreign companies continuously research and develop wearable devices that can measure body activity information anytime and anywhere And the market. Especially, it is used for heart activity measurement device using pulse wave sensor and electrocardiogram sensor. However, in this study, a monitoring system that can detect cardiac activity using cardiac sounds, heart sound measurement rather than pulse wave measurement and electrocardiogram measurement, was performed and its performance was evaluated. Experimental results confirmed the predictability of cardiac heart rate and heart valve disease during daily living.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.8B
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• pp.830-838
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• 2009

Oriental medicine lacks diagnosis data in fixed quantity possible to express visually to patients by depending on clinician's intuition than Western medicine that continues to development by various diagnosis devices. For that, this paper intends to examine relation between heart and voice signal regarded as center organ and source of life and mind in order to implement objectification through the visualization of oriental diagnosis method above all. According to because the heart is related to the tongue among five organs, by thinking with sounds, we would design the way of identifying existence of heart diseases focused on the fact that lingual sound pronunciation of heart patient is inexact. For this, we achieved a comparison, analysis of statistical bandwidth and morphological modeling of the second formants frequency about a lingual sound for their voice constituted subject group of heart diseases and normal people. Finally, we analyzed interrelationship to the result of experiment by designed method.