No abstract available.
Auscultation* ; Heart*

This research is about embodiment of system to support auscultation education more effectively. Cardiac sound data that is stored to PC made many learner deliver by wireless system. For this system we developed a special radio transmitter receiver and a program to manage and remake data. Because of selecting radio system, there is no limitation of establishment and education place. also through web server database and update of data are available. For this reason we can add cardiac sound data newly in education. In case of utilizing existent electron stethoscope in auscultation education, the biggest demerit is that do not deliver sense of sound of actuality stethoscope properly. But radio receiving apparatus that we developed is no difference with sense of sound of cardiac through actuality stethoscope and did so that heighten effect of auscultation education.
Auscultation ; Education ; Heart Sounds ; Stethoscopes

This research is about embodiment of system to support auscultation education more effectively. Cardiac sound data that is stored to PC made many learner deliver by wireless system. For this system we developed a special radio transmitter receiver and a program to manage and remake data. Because of selecting radio system, there is no limitation of establishment and education place. also through web server database and update of data are available. For this reason we can add cardiac sound data newly in education. In case of utilizing existent electron stethoscope in auscultation education, the biggest demerit is that do not deliver sense of sound of actuality stethoscope properly. But radio receiving apparatus that we developed is no difference with sense of sound of cardiac through actuality stethoscope and did so that heighten effect of auscultation education.
Auscultation ; Education ; Heart Sounds ; Stethoscopes

Artificial Intelligence ; Auscultation

We experienced a case of transient complete A-V block, which developed probably due to acute myocarditis of viral etiology. The patient was 13 year old boy, and was admitted to our ward with chief complaints of intermittent abdominal pain and chest discomfort. The auscultation of the heart revealed, the 1st heart sounds varied in intensity, and the E.K.G. findings, checked then, showed complete A-V block with atrial rate of 110/min and ventricular rate of 73/min. We recommended absolute bed rest and oral prednisolove(50mg/day). He discharged on 10th hospital day in good condition with normalized E.K.G. finding.
Abdominal Pain ; Adolescent ; Auscultation ; Bed Rest ; Heart ; Heart Sounds ; Humans ; Male ; Myocarditis ; Thorax

In order to discriminate normal and abnormal heart sounds accurately and effectively, a new method is proposed to analyze heart sounds, namely heart sound characteristic waveform (HSCW) method. Digital stethoscope is used to collect heart sound signals. The recorded data are transmitted to a computer by USB interface for analysis based on HSCW, which is extracted from an analytical model of single degree-of-freedom (SDOF). Furthermore, a case study on the normal and abnormal cardiac sounds is demonstrated to validate the usefulness and efficiency of the proposed HSCW method. Besides, in order to test the accuracy of discriminating normal and abnormal heart sounds, 40 normal and 20 abnormal heart sounds are collected and analyzed, the accuracy performances are achieved by 92.5% and 95.0%, respectively.
Algorithms ; Heart Auscultation ; instrumentation ; methods ; Heart Sounds ; physiology ; Humans ; Phonocardiography ; methods ; Signal Processing, Computer-Assisted

This paper is composed with the cardiac sound measurement and analysis system for in-home use of heart abnormality monitoring. The heart sound acquiring system is composed of a traditional chest-piece, earphone, microphone, and IC recorder. The recorded data is transmitted to a computer by USB interface for analysis based on the cardiac sound characteristic waveform (CSCW) method, which is extracted from an analytical model of single degree-of-freedom (SDOF). Furthermore, the characteristic parameters [T1, T2, T11, T12] are defined by the time intervals between the crossed points of the CSCW and a threshold value (THV), which are related to the first sound and the second sound and are used for discriminating normal and abnormal heart sounds. Also, an easy-understanding graphical representation for these parameters is considered, so that, even for an inexperienced user, he or she is able to monitor his or her cardiac status easily. Finally, a case study on the abnormal/normal cardiac sounds is demonstrated to validate the usefulness and efficiency of this proposed system and the cardiac sound characteristic waveform method.
Algorithms ; Heart Auscultation ; Heart Sounds ; physiology ; Humans ; Signal Processing, Computer-Assisted ; Software Design ; Stethoscopes

The electronic stethoscope combined with artificial intelligence (AI) technology has realized the digital acquisition of heart sounds and intelligent identification of congenital heart disease, which provides objective basis for heart sound auscultation and improves the accuracy of congenital heart disease diagnosis. At the present stage, the AI based cardiac auscultation technique mainly focuses on the research of AI algorithms, and the researchers have designed and summarized a variety of effective algorithms based on the characteristics of cardiac audio data, among which the mel-frequency cepstral coefficients (MFCC) is the most effective one, and widely used in the cardiac auscultation. However, the current cardiac sound analysis techniques are based on specific data sets, and have not been validated in clinic, so the performance of algorithms need to be further verified. The lack of heart sound data, especially the high-quality, standardized, publicly available heart sound database with disease labeling, further restricts the development of heart sound diagnostic analysis and its application in screening. Therefore, expert consensus is necessary in establishing an authoritative heart sound database and standardizing the heart sound auscultation screening process for congenital heart disease. This paper provides an overview of the research and application status of auscultation algorithm and hardware equipment based on AI in auscultation screening of congenital heart disease, and puts forward the problems to be solved in clinical application of AI auscultation screening technology.
Algorithms ; Artificial Intelligence ; Heart Auscultation/trends* ; Heart Defects, Congenital/diagnosis* ; Humans ; Mass Screening/methods*

Heart sound signals acquisition is the primary basis for achieving non-invasive diagnosis of coronary heart disease. In this paper, a digital signal processor (DSP)-based on miniaturized circuit of heart sound signals acquisition and analysis platform was designed to achieve the functions of filtering, collecting, processing, displaying and the communicating with PC. With the self-developed experimental platform, we collected 228 cases of heart sounds of clinical data, and processed the signals using de-noising method with wavelet transform. These experimental results indicated that the db6 wavelet has the most obvious de-noising effect among the four most commonly used wavelets, i.e., haar, db6, sym8, and coif5. One wavelet at different levels possessed different de-noising effects, with level-5 db6 decomposition obtaining the most desirable result.
Algorithms ; Auscultation ; Heart Sounds ; Humans ; Phonocardiography ; methods ; Signal Processing, Computer-Assisted ; Wavelet Analysis

OBJECTIVE: The heart diseases are known as a major cause of sudden death, as well as a cause of poor life-quality of school-age children. But there have been few mass screening of heart diseases in these children in Korea. This study was done to estimate the prevalence of heart diseases of these population. METHODS: We screened all elementary students(grade 1) in 12 cities and 16 counties(Gun) in Kyonggi province from 1992 to 1995. The first screening was done by auscultation of doctors and simultaneously by checking using 'auto-interpreter of EKG-cardiac sound'(Fukuda Densi ECP 50A). We conducted futher examinations to whom classified as being abnormal condition in first screening, by using EKG, chest x-ray, doppler echocardiograpy(if needed). RESULTS: The total number of examined students was 161,308(92% of the population), the male were 83,238 and female were 78,070. The congenital heart diseases(CHD) patients were 290(18 per 10,000) - male 155(18.6 per 10,000) and female 135(17.3 per 10,000). The most frequent disease was ventricula septal defect(VSD, 45.5%), Atrial septal defect(ASD, 14.8%), Tetralogy of Follot(TOF, 11.7%), and Patent Dutus Arteriosis(PDA, 7.6%) in order. In female, the order was VSD(48.1%), ASD(13.3%), TOF(11.1%), and PDA(10.4%). The total number of EKG abnormality were 433(62.7 per 10,000) among 69,056 screened children in 1995. The complete right bundle branch block(CRBBB) and paroxymal ventricular contraction(PVC) were frequent(26.6%, 26.3% in each), and incomplete right bunddle branch block(IRBBB,14.6%), paroxymal atrial contraction(PAC, 6.7%), abnormal Q(5.8%), Wolf-Pakinson-White syndrom (5.5%) in order. In female, the most frequent abnormality was PVC(29.8%), and CRBBB(19.9%) in order. CONCLUSION: We could present the stable prevalence of the rare heart disease. The prevalence of congenital heart diseases was 18.0 per 10,000 and of EKG abnormality was 62.7 per 10,000 among school children.
Auscultation ; Child* ; Death, Sudden ; Electrocardiography ; Female ; Gyeonggi-do* ; Heart Diseases* ; Heart* ; Humans ; Korea ; Male ; Mass Screening ; Prevalence* ; Thorax