• Journal of Preventive Medicine and Public Health
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• v.34 no.4
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• pp.427-436
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• 2001

Objective : To estimate the prevalence of congenital heart disease from the 1990 student heart disease screening program. Methods : The heart disease screening program for elementary students was conducted in Kyonggi-do, in 1998. The subjects of the present study comprised the 40,402 students who attended the schools in the catchment area of a collaborative university hospital and who participated in the primary examination. The congenital heart disease (CHD) patients were initially identified through a questionnaire about prior medical history, and further through diagnostic tests & medical examinations in the secondary & the tertiary examinations. Certain assumptions were used in the estimation of the number of CHD cases among non-participants of the secondary & tertiary examinations. The overall prevalence of CHD was estimated by adding the CHD detection rates of the participants and the estimated prevalence of the non-participants. Results : Among the 40,402 primary participants, 1,655 were referred further, of whom 79.1% (1,309) participated in the secondary examination. Of these, 121 were referred to the tertiary examination, with a participation rate at this last stage of 80.2%. The positive predictive value (PPV) of the screening tools was the highest when the results of both EKG and the questionnaire were positive. Because 85.9% of the detected cases had a past history of CHD, PPV was higher when the selection criteria in the questionnaire included past CHD history than when it didnt. The CHD defection rate among the participants was 1.76 cases/1,000 and the presumed number of cases among the non-participants was 31; giving an estimated final CHD prevalence of 2.52 cases/1,000 (95% CI : 2.06-3.06). Among the identified cases of CHD, VSD (52.8%) was the most common, followed by PDA (9.7%), TOF (9.7%) & PS (9.7%). Conclusion : Because the characteristics of the non-participants differed from those of the participants, the estimation of prevalence was influenced by the participation rate. Of the detected cases, 85.9% had a past history of diagnosis or operation for CMD. These findings suggested that the prevalence estimated in this study may be an underestimation of the actual condition. Therefore, a birth cohort study is required in order to more accurately estimate the prevalence and the effects of the program.

• Sleep Medicine and Psychophysiology
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• v.11 no.2
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• pp.100-105
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• 2004

Objectives: Major depression is associated with an increased risk of cardiovascular mortality. One possible explanation for this association is that major depression influences autonomic neurocardiac regulation. However, previous studies on the relationship between heart rate variability (HRV) and major depression have revealed conflicting results. The purpose of this study is to clarify that major depressive patients compared to healthy controls show a reduction in HRV as an expression of reduced modulation of vagal activity to the heart. Methods: According to DSM-IV, the time and frequency domain HRV indices (5-min resting study) of 30 patients with major depressive disorder were compared with those of 30 healthy controls. Standardized HRV tests enable quantitative estimation of autonomic nervous system function. Results: After controlling for age and gender, subjects with major depression showed a higher heart rate and significantly lower modulation of cardiovagal activity compared to controls. The total power (TP) band, very low frequency (VLF: 0.003-0.04 Hz) band, low frequency (LF: 0.04-0.15 Hz) band, and high frequency (HF: 0.15-0.4 Hz) band were significantly reduced in subjects with major depression compared to control subjects. Conclusion: Patients with major depression may suffer from functional disturbances in the interaction between the sympathetic and parasympathetic autonomic systems.

• Journal of Sensor Science and Technology
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• v.22 no.1
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• pp.76-83
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• 2013

A real-time wireless monitoring and analysis methods using the wearable PPG sensor to estimate cardiovascular condition is studied for ubiquitous healthcare service. A small size and low-power consuming wearable photoplethysmogram (PPG) sensor is designed as a wrist type device and connected with the IP node assigned its own IPv6 address. The measured PPG waveform in the IP node is collected and transferred to a central server PC through the IP-enabled wireless network for storage and analysis purposes. A monitoring and analysis program is designed to process the accelerated plethysmogram (APG) waveform by applying the second order derivatives to analyze systolic waves as well as heart rate variability analysis from the measured PPG waveform. From our results, the features of cardiovascular condition from individual's PPG waveform and estimation of vascular compliance by the comparison of APG-aging index (AI) and ratio of LF/HF are demonstrated.

• Journal of Biomedical Engineering Research
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• v.16 no.2
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• pp.175-182
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• 1995

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 and studied the real time FHR monitoring system by high resolution pitch detection algorithm.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.3
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• pp.61-69
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• 2015

This study presents a probabilistic knowledge discovery method to interpret heart rate variability (HRV) based on time and frequency domain indexes, extracted using discrete wavelet transform. The knowledge induction algorithm was composed of two phases: rule generation and rule estimation. Firstly, a rule generation converts numerical attributes to intervals using ROC curve analysis and constructs a reduced ruleset by comparing consistency degree between attribute-value pairs with different decision values. Then, we estimated three measures such as rule support, confidence, and coverage to a probabilistic interpretation for each rule. To show the effectiveness of proposed model, we evaluated the statistical discriminant power of five rules (3 for atrial fibrillation, 1 for normal sinus rhythm, and 1 for both atrial fibrillation and normal sinus rhythm) generated using a data (n=58) collected from 1 channel wireless holter electrocardiogram (ECG), i.e., HeartCall$^{(R)}$, U-Heart Inc. The experimental result showed the performance of approximately 0.93 (93%) in terms of accuracy, sensitivity, specificity, and AUC measures, respectively.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.6
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• pp.395-402
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• 2016

In these days, the wearable devices have been developed for measuring biological data effectively. However, wearable devices have tissue allege and noise problem. Also, it is impossible for a remote center to identify the person whose data are measured by wearable devices, which could trigger a communication problem over treatment. To solve these problems, biometric measurement based on a non-contact method, such as face image sequencing is necessary. This makes it possible to measure biometric data without any operation and side effects. This system can monitor the biological signals of people in real time without allege and noise and simultaneously identify them. In this paper, we propose an authentication process while measuring biometric data, through a non-contact method.

• Proceedings of the KOSOMBE Conference
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• v.1993 no.05
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• pp.81-85
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• 1993

Despite the simplicity of processing, conventional autocorrelation function (ACF) method for the precise determination of fetal heart rate (FHR) has many problems. In the case of weak or noise corrupted Doppler ultrasound singnals, the ACF method is very sensitive to the threshold level and data window length. It is real troublesome to extract FHR when there is a data loss. To overcome these problems, the high resolution pitch detection algorithm is adapted to estimate the FHR. The FHR is determined from the correlation of two interconnected segments by its maximum correlation value. FHR is compensated with a constant correlation threshold in a greatly smeared noise signal. This method yields more accurate, robust and reliable than the ACF method.

• Journal of Oriental Neuropsychiatry
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• v.19 no.3
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• pp.45-54
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• 2008

Objective: To treat psychogenic headache patients, doctors have to amplify on the headache caused by emotional stress to patients, and assist the patients to cope with difficulties. So, we investigated HRV of the headache patients caused by Chiljungsang and would like to apply to the clinical treatment. Method: Our study measured time and frequency domain HRV indicies(5-min resting study) of 123 headache patients caused by emotional stress. Standardized tests of HRV allow a quantitative estimation of autonomic nervous system function. Results & Conclusions: 1. The study classed as aspects of the head pain showed the differences in RMS-SD(square root of mean squared difference of successive NN intervals) band, HF(high frequency) band significantly. 2. The male headache patients showed higher all the indicies except heart rate compared to the female patients, significantly in SDNN(standard deviation of NN interval), TP(total Power), HF band. 3. As the patients grow older, SDNN, RMS-SD band was lower and LF(low frequency) band, LF/HF ratio higher significantly. The beginning age lower, SDNN, RMS-SD band was higher significantly. The duration of the disease longer, LF band, LF/HF ratio was higher significantly.

• Korean Journal of Exercise Nutrition
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• v.25 no.1
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• pp.35-41
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• 2021

[Purpose] This pilot study aimed to develop a regression model to estimate the excess post-exercise oxygen consumption (EPOC) of Korean adults using various easy-to-measure dependent variables. [Methods] The EPOC and dependent variables for its estimation (e.g., sex, age, height, weight, body mass index, fat-free mass [FFM], fat mass, % body fat, and heart rate_sum [HR_sum]) were measured in 75 healthy adults (31 males, 44 females). Statistical analysis was performed to develop an EPOC estimation regression model using the stepwise regression method. [Results] We confirmed that FFM and HR_sum were important variables in the EPOC regression models of various exercise types. The explanatory power and standard errors of estimates (SEE) for EPOC of each exercise type were as follows: the continuous exercise (CEx) regression model was 86.3% (R²) and 85.9% (adjusted R²), and the mean SEE was 11.73 kcal, interval exercise (IEx) regression model was 83.1% (R²) and 82.6% (adjusted R²), while the mean SEE was 13.68 kcal, and the accumulation of short-duration exercise (AEx) regression models was 91.3% (R²) and 91.0% (adjusted R²), while the mean SEE was 27.71 kcal. There was no significant difference between the measured EPOC using a metabolic gas analyzer and the predicted EPOC for each exercise type. [Conclusion] This pilot study developed a regression model to estimate EPOC in healthy Korean adults. The regression model was as follows: CEx = -37.128 + 1.003 × (FFM) + 0.016 × (HR_sum), IEx = -49.265 + 1.442 × (FFM) + 0.013 × (HR_sum), and AEx = -100.942 + 2.209 × (FFM) + 0.020 × (HR_sum).

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.415-419
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• 1997

The left ventricular relaxation rate is used as a golden standard which describes the left ventricular diastolic unction. So far, to get the rate of relaxation one should calculate the data after full recording, that is, off-line method. Therefore one cannot get the rate of relaxation in real-time while changing loading condition or infusing drug. But real time monitoring of the relaxation rate is necessary while changing loading condition or infusing drug to control the mechanics of heart and to get more information. We propose a new criterion to get the left ventricular relaxation rate and a real time algorithm. By comparison, it was turned out that our criterion outperforms others criterion.