• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.2
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• pp.233-242
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• 2018

Previous works for detecting arrhythmia have mostly used nonlinear method such as artificial neural network, fuzzy theory, support vector machine to increase classification accuracy. Most methods require higher computational cost and larger processing time. Therefore it is necessary to design efficient algorithm that classifies PVC(premature ventricular contraction) and decreases computational cost by accurately detecting feature point based on only R peak through optimal R wave. For this purpose, we detected R wave through optimal threshold value and extracted RR interval and R peak pattern from noise-free ECG signal through the preprocessing method. Also, we classified PVC in realtime through RR interval and R peak pattern. The performance of R wave detection and PVC classification is evaluated by using 9 record of MIT-BIH arrhythmia database that included over 30. The achieved scores indicate the average of 99.02% in R wave detection and the rate of 94.85% in PVC classification.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.33 no.6
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• pp.367-373
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• 2021

In this study, deep learning model was set up to predict the wave heights inside a harbour. Various machine learning techniques were applied to the model in consideration of the transformation characteristics of offshore waves while propagating into the harbour. Pohang New Port was selected for model application, which had a serious problem of unloading due to swell and has lots of available wave data. Wave height, wave period, and wave direction at offshore sites and wave heights inside the harbour were used for the model input and output, respectively, and then the model was trained using deep learning method. By considering the correlation between the time series wave data of offshore and inside the harbour, the data set was separated into prevailing wave directions as a pre-processing method. As a result, It was confirmed that accuracy and stability of the model prediction are considerably increased.

• Journal of the Korean Society of Safety
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• v.32 no.2
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• pp.98-104
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• 2017

The ultrasonic pulse velocities of pressure, shear, and Rayleigh waves ( P-, S-, and R- waves) have been used for the condition evaluation of various concrete structures, but the statistical distribution according to the wave type has not been studied clearly in view of data reliability and validity. Therefore, this study analyzed the statistical distribution of P-, S-, R-wave velocities in concrete wide beams of $800{\times}3100mm$ (width ${\times}$ length) with a thickness of 300 mm. In addition, we investigated an experimental consistency by the Kolmogorov-Smirnov goodness-of-fit test. The experimental data showed that the R-, S- and P- wave velocities in order have better statistical stability and reliability for in situ evaluation because R- and S-waves are less sensitive to confinement and boundary conditions. Also, good correlations between wave velocities and strength and modulus of elasticity were found, which indicate them as appropriate techniques for estimating the mechanical properties.

• Progress in Superconductivity
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• v.10 no.1
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• pp.6-11
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• 2008

Multi-channel magnetocardiography (MCG) has been proposed to detect ischemic heart disease because its sensitivity is quite high comparing with other conventional diagnostic tools. Especially, current map and magnetic field map of MCG provide crucial information on whether myocardiac muscles maintain the normal conduction pathway. In addition, MCG parameters derived from repolarization are useful to detect coronary artery disease. Recently, there was a study reporting that R- and T- wave amplitude are highly correlated with ischemic heart disease. In this study, we studied R- and T-wave amplitude and their ratio as well as MCG parameters. MCG data from 20 young, 20 age-matched controls, and 20 myocardial infarction (MI) patients were analyzed. As a result, MCG parameters showed significant change in MI patients comparing to those of controls. R- and T-wave amplitude of MI patients showed a feature of severe ischemic heart disease even though it was difficult to find consistent values. Further study is needed to reveal the relations between small T-wave amplitude and coronary artery disease.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.08a
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• pp.274-274
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• 2012

We have researched on controlling an electron temperature and a plasma collision frequency to study the effect of collisions on helicon plasmas. So, we have designed and constructed an electron cyclotron resonance (ECR) heating system in the helicon device as an auxiliary heating source. Since then, we have tried to optimize experimental designs such as a magnetic field configuration for ECR heating and 2.45GHz microwave launching system for its power transfer to the plasma effectively, and have characterized plasma parameters using a Langmuir probe. For improving an efficiency of the ECR heating with R-wave in the helicon plasma, we would understand an effect of R-wave propagation with ECR heating in the helicon plasma, because the efficiency of ECR heating with R-wave depends on some factors such as electron temperature, electron density, and magnetic field gradient. Firstly, we calculate the effect of R-wave propagation into the ECR zone in the plasma with those factors. We modify the magnetic field configuration and this system for the effective ECR heating in the plasma. Finally, after optimizing this system, the plasma parameters such as electron temperature and electron density are characterized by a RF compensated Langmuir probe.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.4
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• pp.33-40
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• 2016

Previous works for detecting arrhythmia have mostly used nonlinear method to increase classification accuracy. Most methods require accurate detection of ECG signal, higher computational cost and larger processing time. But it is difficult to analyze the ECG signal because of various noise types. Also in the healthcare system based IOT that must continuously monitor people's situation, it is necessary to process ECG signal in realtime. Therefore it is necessary to design efficient algorithm that classifies different arrhythmia in realtime and decreases computational cost by extrating minimal feature. In this paper, we propose R wave detection considering complexity and arrhythmia classification based on binary coding. For this purpose, we detected R wave through SOM and then RR interval from noise-free ECG signal through the preprocessing method. Also, we classified arrhythmia in realtime by converting threshold variability of feature to binary code. R wave detection and PVC, PAC, Normal classification is evaluated by using 39 record of MIT-BIH arrhythmia database. The achieved scores indicate the average of 99.41%, 97.18%, 94.14%, 99.83% in R wave, PVC, PAC, Normal.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.5
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• pp.242-250
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• 2013

In this paper, R-wave detection algorithm using refractory period to reflect the depolarization and repolarization of the myocardial cells of the heart is proposed. The proposed algorithm detects R-peaks using the features of R-wave and variable refractory period. First, the proposed algorithm extracts candidate R-peaks that have a relatively high potential and calculates the refractory period based on the kurtosis and potential for candidate R-peaks. Next, R-peak is determined by morphological features of the R-wave within the refractory period. In addition, due to less computation in the proposed algorithm, real-time processing is possible. The algorithm is applied to all records of the MIT-BIH arrhythmia database and the obtained results show a competitive detection rate of over 99.7%.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.7
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• pp.1331-1338
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• 2007

A new method for detecting and eliminating the Electrocardiogram(ECG) artifact from the scalp Electroencephalogram(EEG) is proposed. Based on the single channel EEG, the proposed method consists of 4 procedures: emphasizing the R-wave of ECG artifact from EEG using the least squares acceleration(LSA) filter, detecting the R-wave from the LSA filtered EEG using the phase space method and R-R interval, generating the delayed impulse synchronized to the R-wave and elimination of the ECG artifacts based on the adaptive digital filter using the impulse and raw EEG. The performance of the proposed method was evaluated in the two separating parts of R-wave detection and, ECG estimation and elimination from EEG. In the R-wave detection, the proposed method showed the mean error rate of 6.285(%). In the ECG estimation and elimination using simulated and/or real EEG recordings, we found that the ECG artifacts were successfully estimated and eliminated in comparison with the conventional multi-channel techniques, in which independent component analysis and ensemble average method are used. From this we can conclude that the proposed method is useful for the detecting and eliminating the ECG artifact from single channel EEG and simple for ambulatory/portable EEG monitoring system.

• Journal of Korea Water Resources Association
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• v.45 no.12
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• pp.1275-1292
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• 2012

This study investigates the characteristics of stem waves along a vertical structure under overtopping conditions through laboratory experiments in a wave basin. The uni-directional random waves with Bretschneider-Mitsuyasu frequency spectrum as incident waves were used. This study is focused on the reduction of wave height due to the variation of relative freeboard height (R) and the results for wave overtopping conditions are compared with those for non-overtopping conditions. Though the relative wave height along a vertical structure decreases with the decrease of relative freeboard, the variation of stem width is not significant. For the relative freeboard is greater than 1, the reduction effect of stem wave height by overtopping can be ignored in this experiments. The reduction effect of wave height along the structure for R =0.5 is about 10% comparing with R =1.5.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.20 no.3
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• pp.255-267
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• 2008

Using the commercial CFD code FLOW-$3D^{(R)}$ which has an implicit General Moving Object (GMO) method, the ship-induced wave has been simulated. In the implicit GMO method of the FLOW-$3D^{(R)}$, a rigid body's motion which is either user-prescribed (prescribed motion) or dynamically coupled to fluid flow (coupled motion) can be computed with six degrees of freedom (DOF). The simulated horizontal wave patterns are agree with the wave patterns represented by depth Froude number. The model has been well-simulated to generate the depth-dependent wave transformation in comparison of uniform depth case to complicated depth case. Additionally, it shows that ship-induced waves have been reasonably generated by two ships passing each other and by a ship moving in a curve. Therefore, it is suggested that the FLOW-$3D^{(R)}$ model calibrated with observed data should provide more accurate prediction for the ship-induced wave in a certain fairway or harbor.