• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.18 no.4
• /
• pp.825-832
• /
• 2014

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 accurate detection of P-QRS-T point, higher computational cost and larger processing time. Even if some methods have the advantage in low complexity, but they generally suffer form low sensitivity. Also, it is difficult to detect PVC accurately because of the various QRS pattern by person's individual difference. Therefore it is necessary to design an efficient algorithm that classifies PVC based on QRS pattern in realtime and decreases computational cost by extracting minimal feature. In this paper, we propose PVC classification based on QRS pattern using QS interval and R wave amplitude. For this purpose, we detected R wave, RR interval, QRS pattern from noise-free ECG signal through the preprocessing method. Also, we classified PVC in realtime through QS interval and R wave amplitude. The performance of R wave detection, PVC classification is evaluated by using 9 record of MIT-BIH arrhythmia database that included over 30 PVC. The achieved scores indicate the average of 99.02% in R wave detection and the rate of 93.72% in PVC classification.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.20 no.2
• /
• pp.437-444
• /
• 2016

Most methods for detecting arrhythmia require pp interval, diversity of P wave morphology, but it is difficult to detect the p wave signal because of various noise types. Therefore it is necessary to use noise-free R wave. In this paper, we propose algorithm for premature contraction arrhythmia classification through ECG pattern analysis and template threshold. For this purpose, we detected R wave through the preprocessing method using morphological filter, subtractive operation method. Also, we developed algorithm to classify premature contraction wave pattern using weighted average, premature ventricular contraction(PVC) and atrial premature contraction(APC) through template threshold for R wave amplitude. The performance of R wave detection, PVC classification is evaluated by using 6 record of MIT-BIH arrhythmia database that included over 30 PVC and APC. The achieved scores indicate the average of 99.77% in R wave detection and the rate of 94.91%, 95.76% in PVC and APC classification.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.4 no.3
• /
• pp.161-167
• /
• 1992

We consider the preparation of long finite amplitude nondispersive waves over a step bottom between two regions of finite different depths. Two dimensional motion is assumed. with the wave crests parallel to the step, and irrotational flow in the inviscid fluid is considered. To describe the transformation of finite amplitude waves we use the finite-amplitude shallow-water equations, the conditions of mass flow conservation and pressure continuity at the cut above the step in Riemann's variables. The equations define four families of curves-characteristics on which the values of the Riemann's invariants remain constant and a system of two nonlinear equations that relates the amplitudes of incident reflected and transmitted waves. The system obtained is difficult to analyze in common form. Thus we consider some special cases having practical usage for tsunami waves. The results obtained are compared with the long wave theory and significant nonlinear effects are found even for quite small amplitude waves.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.18 no.7
• /
• pp.1531-1539
• /
• 2014

Premature ventricular contraction(PVC) is the most common disease among arrhythmia and it may cause serious situations such as ventricular fibrillation and ventricular tachycardia. Nevertheless personalized difference of ECG signal exist, performance degradation occurs because of carrying out diagnosis by general classification rule. In other words, the design of algorithm that exactly detects abnormal signal and classifies PVC by analyzing the persons's physical condition and/or environment and variable QRS pattern is needed. Thus, PVC classification by personalized abnormal signal detection and QRS pattern variability is presented in this paper. For this purpose, we detected R wave through the preprocessing method and subtractive operation method and selected abnormal signal sets. Also, we classified PVC in realtime through QS interval and R wave amplitude. The performance of abnormal beat detection and PVC classification is evaluated by using MIT-BIH arrhythmia database. The achieved scores indicate the average of 98.33% in abnormal beat classification error and 94.46% in PVC classification.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
• /
• v.1 no.1
• /
• pp.40-54
• /
• 1990

The author studied EEG differences among normal, children, children with emotional behavioral problems determined by Rutter's questionnaire and children with attention-deficit hyperactivity disorder according to DSM-III-R. The results are as follows ; There were no differences in incidence and pattern of abnormal EEG between normal control children and children with emotional behavioral problems. But children with attention-deficit hyperactivity disorder tend to show lower average amplitude, and less wave percentage time of alpha wave in occipital area than normal did, furdermore wave percentage time of alpha wave appeared more in left occipital area than in right occipital area, These results demonstrated that emotional behavioral problems in elementary school children may not be related to EEG abnormality, Where as children with attention deficit hyperactivity disorder showed underdeveloped alpha waves as compared with normal control children.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.17 no.4
• /
• pp.945-952
• /
• 2013

The R wave of QRS complex is the most prominent feature in ECG because of its specific shape; therefore it is taken as a reference in ECG feature extraction. But R wave detection suffers from the fact that frequency bands of the noise/other components such as P/T waves overlap with that of QRS complex. ECG signal processing must consider efficiency for hardware and software resources available in processing for miniaturization and low power. In other words, the design of algorithm that exactly detects QRS region using minimal computation by analyzing the person's physical condition and/or environment is needed. Therefore, efficient QRS detection based on SOM(Subtractive Operation Method) is presented in this paper. For this purpose, we detected R wave through the preprocessing method using morphological filter, empirical threshold, and subtractive signal. Also, we applied dynamic backward searching method for efficient detection. The performance of R wave detection is evaluated by using MIT-BIH arrhythmia database. The achieved scores indicate the average of 99.41% in R wave detection.

• The Journal of Engineering Geology
• /
• v.4 no.1
• /
• pp.29-42
• /
• 1994

Discrimination studies between microearthquakes and underground explosions are carried out in the pure-continental path of north-south within the Korean Peninsula. The characteristic waveforms for explosions and microearthquakes are investigated in the light of observation and synthetic seismograms. The characteristic waveform generation is minnly a function of source mechanism and ray-path and former influences more strongly than the latter.A double-couple source mechanism for microeatthquakes and a single-couple(force) mechanism for explosions are presented in this study. It is found for very shallow events to have outstanding of $L_g$ waves in the transverse components that pass through the upper crust with period of 1 - 6 seconds and fundamental modes of Rayleigh waves, $R_g$ in the vertical component with period 8-12 seconds. Furthermore it is pointed out that the first arrival amplitudes of SH waves for explosions are always srnall regardless of azimuth of stations since there is non-existence of nodal lines for the explosion mechanism. Theoretical seismograms for explosions show the first motions of compression with short wavelengths as well as mostly fundamental modes of Rayleight waves, $R_g$ waves and $L_g$ waves, whereas those of micro-earthquakes give either compression or dilatation according to the ack azimuth epicenter to stations and poor or non $R_g$ waves and complicated $L_g$ waves, depending on the focal depth.

• Journal of Korean Ophthalmic Optics Society
• /
• v.8 no.2
• /
• pp.135-151
• /
• 2003

This study compared the effect of Polaroid$^{(R)}$ lenses on binocular vision by assessing visual acuity, stereopsis, and visual evoked potential(VEP), through Polaroid$^{(R)}$, CR 39 and sunglass lenses. The spectral absorptions of Polaroid$^{(R)}$, CR 39 and sunglass lenses were measured using a spectrophotometer (Hitachi. U-3501). The VEP were recorded by the Nicolet system. Thirty normal adult(fifteen males, fifteen females, mean=21.9 years, range=20 to 25) subjects were recorded. The subjects were provided a history including : general health, family health, medication, genetics, allergy and disease. All had normal or corrected to normal acuity with no history of visual disorders. Corrected visual acuity, colour vision and stereopsis were recorded for each subject monocularly and binocularly. Each test was repealed through the sunglass, CR 39, and Polaroid$^{(R)}$ lenses. Subjects viewed the VEP stimulus both monocularly and binocularly through the test lenses while the VEPs were recorded. The results suggest that the binocular visual acuity and stereoacuity is better than with monocular vision. On other hand, the analysis of VEP suggests that the amplitude of wave is smaller when the monocular eye receives the VEP stimulus compared with that when the binocular eye is stimulated by the VEP target with the sunglass, CR 39, and Polaroid$^{(R)}$ lens. But, the latency period of each eye was similar to results between the dominant eye and the non-dominant eye by the CR 39, sunglass, and polaroid lens. In conclusion, this study indicates that the binocular vision appears to be better through the brown Polaroid$^{(R)}$ lens than through the other test lenses.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.32 no.6
• /
• pp.434-445
• /
• 2020

In this study, the minimization of harbor oscillation using permeable breakwater was applied to the actual harbor and investigated an effect of minimization by computer simulation in order to take into account the water quality problems and measures of harbor oscillation by infragravity waves at the same time. The study site is Mukho harbor located at East coast of Korea that harbor oscillation has been occurred frequently. The infragravity waves obtained by analyzing the observed field data for five years focused on the distribution between wave periods of 40 s and 70 s and wave heights in less than 0.1 m was 94% of analyzing data. The target wave periods was 68.0 s. The most effective method of minimization of harbor oscillation by infragravity waves was to install a detached permeable breakwater with transmission coefficient of 0.3 on the outside harbor and replace some area of the vertical wall in the harbor with wave energy dissipating structure to achieve a reflectivity of 0.9 or less. The amplitude reduction rate of this method shown in 27.4%. And the effect of the difference in transmission coefficient of permeable breakwater on the reduction rate of the amplitude was not significant.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.7
• /
• pp.1728-1736
• /
• 2015

Several algorithms have been developed to classify arrhythmia which either rely on specific ECG(Electrocardiogram) database. Nevertheless personalized difference of ECG signal exist, performance degradation occurs because of carrying out diagnosis by general classification rule. Most methods require accurate detection of P-QRS-T point, higher computational cost and larger processing time. But it is difficult to detect the P and T wave signal because of person's individual difference. Therefore it is necessary to design efficient algorithm that classifies different arrhythmia in realtime and decreases computational cost by extracting minimal feature. In this paper, we propose arrhythmia classification method using QRS Pattern of ECG signal according to personalized type. For this purpose, we detected R wave through the preprocessing method and define QRS pattern of ECG signal by QRS feature Also, we detect and modify by pattern classification, classified arrhythmia duplicated QRS pattern in realtime. Normal, PVC, PAC, LBBB, RBBB, Paced beat classification is evaluated by using 43 record of MIT-BIH arrhythmia database. The achieved scores indicate the average of 99.98%, 97.22%, 95.14%, 91.47%, 94.85%, 97.48% in PVC, PAC, Normal, BBB, Paced beat classification.