• Journal of Sensor Science and Technology
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• v.20 no.2
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• pp.118-123
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• 2011

Heart related diseases mainly caused by heavy work load and increasing stress in human daily life. Therefore, researches on mobile healthcare monitoring for daily life has been carried out. Notably, wearable healthcare monitoring system which has least restriction has been tried to provide an emergency alert of abnormal heart rate. In this study, we developed chair type unconstrained BCG measurement system which able to perform continuous heart status monitoring at the office and daily life in the unconstrained way. Furthermore, adaptive threshold is used to detect the heart rate from BCG signals. The HRV(heart rate variability) is calculated from heart rate interval. ECG signal measured using conventional method and BCG signal measured using unconstraint system are carried out simultaneously for the purpose of performance evaluation. From the comparison result, BCG signal shows a similar heart beat characteristic as ECG signal. This proves the possibility of practical implementation of unconstraint healthcare monitoring system. In addition, medical examination like valsalva maneuver is performed to observe the changes in HRV due to stress. By performing valsalva maneuver, heart is said to be placed under an artificial physical stress condition. Under this artificial physical stress condition, the time and frequency domain of HRV parameters are evaluated.

• Journal of Digital Convergence
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• v.18 no.8
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• pp.231-242
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• 2020

The thesis presents a system that continuously collects the human body's physiological vital information at rest with sensors and ICT information technology and predicts diabetes using the collected information. it shows the artificial neural network machine learning method and essential basic variable values. The study method analyzed the correlation between heart rate measurements of BCG and ECG sensors in 20 DM- and 15 DM+ subjects. Artificial Neural Network (ANN) machine learning program was used to predictability of diabetes. The input variables are time domain information of HRV, heart rate, heart rate variability, respiration rate, stroke volume, minimum blood pressure, highest blood pressure, age, and sex. ANN machine learning prediction accuracy is 99.53%. Thesis needs continuous research such as diabetic prediction model by BMI information, predicting cardiac dysfunction, and sleep disorder analysis model using ANN machine learning.

• Proceedings of the KOSOMBE Conference
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• v.1992 no.05
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• pp.123-126
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• 1992

In this paper, a numerical simulation of steady laminar and turbulent flow in a two dimensional model for the total artificial heart is presented. A trileaflet polyurethane valve was simulated at the outflow orifice while the inflow orifice had a trileaflet or a flap valve. The numerical solutions of the simulated model show that regions of relative stasis and trapped vortices were smaller wi thin the ventricular chamber wi th the flap valve at the inflow orifice than that with the trileaflet valve. The predicted Reynolds stresses distal to the inflow valve within the ventricular chamber were also found to be smaller with the flap valve than with the trileaflet valve. Analysis of the numerical solutions suggests that geometries similar to the flap valve(or a tilting disc valve) results in a better flow dynamics within the total artificial heart chamber compared to a trileaflet valve.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1317-1321
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• 1987

A new type of motor-driven Total Artificial Heart(TAH) system with rolling cylinder mechanism has been developed. Brushless DC motor was chosen as energy converter and controlled by PI controller according to the given velocity profile under the highly time-varying load. Computer simulation was also performed to calculate the optimal gains of PI controller which minimize the input power, one of the most important parameter in artificial heart system.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.3
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• pp.38-47
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• 1995

A new automatic cardiac output control algorithm for the motor-driven electromechanical total artificial heart(TAH) was developed based on the motor current waveform analysis without using any extra transducer. The basic control requirements of artificial heart can be described in terms of three features : preload sensitivity, afterload insensitivity, and balanced ventricular outputs. In the previous studies, many transducers were utilized to obtain informations of hemodynamic states for the automatic cardiac output control, But such automatic control systems with sensors have had reliability problems. We proposed a new sensorless automatic cardiac output control algorithm providing adequate cardiac output to the time-varying physiological demand without causing right atrial collapse, which is one of the critical problem in an active-filling type device. In-vitro tests were performed on a mock circulation system to evaluate the performance of the developed algorithm and the results show that the new algorithm satisfied the basic control requirements on the cardiac output response and the possibility of application of the developed algorithm to in vivo experiments.

• Journal of Biomedical Engineering Research
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• v.19 no.2
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• pp.153-162
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• 1998

It is needless to say that the nonlinear hemodynamic variables estimation is a very important study for the artificial heart. Even though it is important, there have not been satisfactory results which can be applied to the real world situations, In this paper, the problem of hemodynamic variables estimation for the moving-actuator type total artificial heart(MA-TAH) was studed. Multidimensional linear interpolation(MDI)scheme was used for the estimation. Proposed method was verified by in vitro test and showed good performance.

• Journal of Digestive Cancer Research
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• v.12 no.1
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• pp.31-37
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• 2024

Pancreatic cancer is a highly fatal malignancy with a 5-year survival rate of < 10%. Endoscopic ultrasound (EUS) is a useful noninvasive tool for differential diagnosis of pancreatic malignancy and treatment decision-making. However, the performance of EUS is suboptimal, and its accuracy for differentiating pancreatic malignancy has increased interest in the application of artificial intelligence (AI). Recent studies have reported that EUS-based AI models can facilitate early and more accurate diagnosis than other preexisting methods. This article provides a review of the literature on EUS-based AI studies of pancreatic malignancies.

• The Korean Journal of Physiology
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• v.8 no.2
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• pp.33-44
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• 1974

The electrocardiogram of frogs were obtained in winter (January), spring (April), summer (July) and autumn (September and November). Electrocardiograms were recorded applying electrodes to the atria, ventricle and apex of the heart by unipolar or bipolar leads. V wave was recorded prior to P wave, for the presence of the sinus venosus which controls the automaticity of the frog heart, in four seasons. Regardless of the leads or the position of the electrodes P wave was diphasic and wide. According to the rise of temperature the rate of heart beat was increased, and V-P and P-R interval were shortened. Two regression line between R-R interval and both V-P interval and P-R interval were drawn. These were calculated as V-P interval=1 0.276R-R $interva1+0.067{\pm}0.15$ (sec.) and P-R interval=0.179R-R $interva1+0.155{\pm}0.1$ (sec). From these calculation the larger gradient of V-P interval than P-R interval was suggestive that the heart rate is more dependent on the changes of V-P interval than that of P-R interval. Changes of the heart rate were also measured in four seasons and artificial temperatures. Two regression lines between the heart rate (H.H.) and both seasonal temperature (T) and artificial temperature, were drawn. These two lines were calculated as H.R.=20+3.71 (T-10) and H.R.=32+1.425 T respectively. From two gradients of the above equations it is considered that the changes of the heart rate in artificial temperature were milder than that in seasonal temperature. The number of RBC and WBC of frogs were measured in four seasons and a tendency of the changes was observed according to the seasonal variation.

• 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 Chest Surgery
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• v.28 no.6
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• pp.533-541
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• 1995

We recently developed a new model of moving actuator type totally implantable artificial heart[TIAH , based on the reverse position of the aortic and pulmonary conduits. This concept was proposed by one of surgeons in our team[Joon-Ryang Rho, M.D. to facilitate anatomical fitting of TIAHs. The moving actuator type electromechanical TIAH consisted of the left and right blood sacs, and the moving actuator including a motor. The inverted umbrella type polyurethane valves were used in the blood pumps. The aortic conduit was positioned anterior to the pulmonary conduit, which was the opposite relation to the conventional configuration of other total artificial hearts. We also adapted slip-in connectors for the aortic and pulmonary conduits. Two sheep , weighing 60-69 kg, were used for implantation. After small cervical incision and trans-sternal bilateral thoracotomy, cardiopulmonary bypass [CPB was administered using an American Optical 5-head pump and a membrane oxygenator[Univox-IC, Bentley . The anterior and posterior vena cavae were drained separately for venous return. An arterial return cannula was inserted into the right common carotid artery. During CPB, almost all of the ventricular myocardium was excised down to the atrioventricular groove and the artificial heart was implanted. We achieved 3-day survival in the first sheep and 2-day survival in the second. The day after operation the first sheep was successfully extubated and the second sheep was weaned from a respirator with good condition. After extubation, the first sheep walked around in the cage and fed herself. Serial laboratory and hemodynamic examinations were done during the experiments. In both sheep, pulmonary dysfunction was gradually developed, which was accompanied by acute renal failure. The animals were sacrificed and autopsy was done. Unexpected pregnnacy was incidentally found in both sheep. To our knowledge this is the first report of significant survival cases in the orthotopic implantation of electric TIAH using sheep.