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

• Economic and Environmental Geology
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• v.31 no.1
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• pp.21-29
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• 1998

Broadband receiver functions are developed from teleseismic P waveforms recorded at Wonju (KSRS), Inchon (IRIS), and Pohang (PHN), and are analyzed to examine the crustal structure beneath the three stations. The teleseismic receiver functions are inverted in the time domain to the vertical P wave velocity structure beneath the stations. Clear P-to-S converted phases from the Moho interface are observed in teleseismic seismograms recorded at the three stations. We estimated the crustal velocity structures beneath the stations using the receiver function inversion. The general features of inversion results are as follows: (1) For Pohang station, there is a high velocity gradient at a 4~5 km deep for SE and NW back azimuth and a low velocity zone at around 10 km deep. The Moho depth is 28 km for NW direction. (2) The shallow crustal structure beneath Wonju station is somewhat complex and there is a high-velocity zone ($V_p{\simeq}6.8km/sec$) at 3 to 4 km deep. The average crustal thickness is 33 km, and a transition zone exists at a 30~33 km deep of lower crust, of which velocity is abruptly changed 6.4 to 7.9 km/sec. (3) For Inchon station, the crustal velocity gradient monotonously increases up to the Moho discontinuity and the velocity is abruptly changed from 6.2 km/sec to 7.9 km/sec at 29 km deep.

• Tunnel and Underground Space
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• v.25 no.1
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• pp.56-67
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• 2015

In this study, a source locating technique applicable to transversely isotropic media was developed. Wave velocity anisotropy was considered based on the partition approximation method, which simply enabled AE source locating. Sets of P wave arrival time were decided by the two-step AIC algorithm and they were later used to locate the AE sources when having the least error compared with the partitioned elements. In order to validate the technique, pencil lead break test on artificial transversely isotropic mortar specimen was carried out. Defining the absolute error as the distance between the pencil lead break point and the located point, 1.60 mm ~ 14.46 mm of range and 8.57 mm of average were estimated therefore it was regarded as thought to be 'acceptable' considering the size of the specimen and the AE sensors. Comparing each absolute error under different threshold levels, results showed small discrepancies therefore this technique was hardly affected by background noise. Absolute error could be decomposed into each coordinate axis error and through it, effect of AE sensor position could be understood so if optimum sensor position was able to be decided, one could get more precise outcome.

• 한국지구물리탐사학회:학술대회논문집
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• 2008.10a
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• pp.107-112
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• 2008

In the case of the deep reservoirs like the gas reservoirs in the East-sea, it is often difficult to observe AVO responses in CMP gathers. Because the reservoir becomes more consolidated as its depth deepens, P-wave velocity does not decrease significantly when the pore fluid is replaced by the gas. In this study, we analyzed the effects of Poisson's ratio difference on AVO response with a variety of Poisson's ratios for the upper and lower layers. The results show that, as the difference in Poisson's ratio between the upper and lower layers decreases, the change in the reflection amplitude with incidence angle decreases. To consider the limitation of AVO responses shown in the gas reservoir in East-sea, the velocity model was made by simulation Gorae V structure with seismic data and well logs. The results of comparing AVO responses observed from the synthetic data with theoretical AVO responses calculated by using material properties show that the amount of the change in reflection amplitude with increasing incident angle is very small when the difference in Poisson's ratio between the upper and lower layers is small. In addition, the characteristics of AVO responses were concealed by noise or amplitude distortion arisen during preprocessing. To overcome such limitations of AVO analysis of the data from deep reservoirs, we need to acquire precisely reflection amplitudes in data acquisition stage and use processing tools which preserve reflection amplitude in data processing stage.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.8
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• pp.1947-1954
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• 2013

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. 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 extrating minimal feature. In this paper, we propose arrhythmia detection based on binary coding using QRS feature varibility. For this purpose, we detected R wave, RR interval, QRS width from noise-free ECG signal through the preprocessing method. Also, we classified arrhythmia in realtime by converting threshold variability of feature to binary code. PVC, PAC, Normal, BBB, Paced beat classification is evaluated by using 39 record of MIT-BIH arrhythmia database. The achieved scores indicate the average of 97.18%, 94.14%, 99.83%, 92.77%, 97.48% in PVC, PAC, Normal, BBB, Paced beat classification.

• Geophysics and Geophysical Exploration
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• v.11 no.3
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• pp.242-249
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• 2008

Recently, AVO analysis has been widely used in oil exploration with seismic subsurface section as a direct indicator of the existence of the gas. In the case of the deep reservoirs like the gas reservoirs in the East-sea, it is often difficult to observe AVO responses in CMP gathers even though the bright spots are shown in the stacked section. Because the reservoir becomes more consolidated as its depth deepens, P-wave velocity does not decrease significantly when the pore fluid is replaced by the gas. Thus the difference in Poisson's ratio, which is a key factor for AVO response, between the reservoir and the layer above it does not increase significantly. In this study, we analyzed the effects of Poisson's ratio difference on AVO response with a variety of Poisson's ratios for the upper and lower layers. The results show that, as the difference in Poisson's ratio between the upper and lower layers decreases, the change in the reflection amplitude with incidence angle decreases and AVO responses become insignificant. To consider the limitation of AVO responses shown in the gas reservoir in East-sea, the velocity model was made by simulation Gorae V structure with seismic data and well logs. The results of comparing AVO responses observed from the synthetic data with theoretical AVO responses calculated by using material properties show that the amount of the change in reflection amplitude with increasing incident angle is very small when the difference in Poisson's ratio between the upper and lower layers is small. In addition, the characteristics of AVO responses were concealed by noise or amplitude distortion arisen during preprocessing. To overcome such limitations of AVO analysis of the data from deep reservoirs, we need to acquire precisely reflection amplltudes In data acquisition stage and use processing tools which preserve reflection amplitude in data processing stage.