• 한국컴퓨터정보학회논문지
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• 제18권1호
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• pp.93-101
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• 2013

심전도 신호에서 R-파는 다른 특징 점을 구하는데 중요한 역할을 할 뿐만 아니라 심장에 대한 많은 의학적인 정보를 가지고 있다. 지금까지의 연구는 심전도 신호 형태에 대한 분석을 통하여 R-파를 검출하였으나, R-파와 비슷한 형태의 P-파가 나타날 경우 정확한 R-파 검출이 어려웠다. 본 논문에서는 세포막이 흥분 후에 탈분극과 재 분극 기간인 불응기와 불응기내 파형의 첨도 형태를 이용하여 R-파를 검출하는 방식을 제시하였다. MIT-BIH 부정맥 데이터베이스에 있는 심전도 신호 대한 실험을 통하여 R-파와 유사한 형태의 P-파를 가진 105번과 108번 레코드뿐만 아니라 다른 레코드에서도 기존의 방식보다 비교적 우수한 검출율을 확인하였다.

• 디지털산업정보학회논문지
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• 제17권1호
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• pp.7-14
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• 2021

With the increased attention about healthcare and management of heart diseases, smart healthcare services and related devices have been actively developed recently. R wave is the largest representative signal among ECG signals. R wave detection is very important because it detects QRS pattern and classifies arrhythmia. Several R wave detection algorithms have been proposed with different features, but the remaining problem is their implementation in low-cost portable platforms for real-time applications. In this paper, we propose R wave detection based on optimal threshold and arrhythmia classification through QRS pattern considering complexity in smart healthcare environments. For this purpose, we detected R wave from noise-free ECG signal through the preprocessing method. Also, we classify premature ventricular contraction arrhythmia in realtime through QRS pattern. The performance of R wave detection and premature ventricular contraction arrhythmia classification is evaluated by using 9 record of MIT-BIH arrhythmia database that included over 30 premature ventricular contraction. The achieved scores indicate the average of 98.72% in R wave detection and the rate of 94.28% in PVC classification.

• 디지털산업정보학회논문지
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• 제13권4호
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• pp.91-98
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• 2017

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 minimal feature point based on only R peak through optimal R wave. We propose an optimal R wave detection and PVC classification method through extracting minimal feature point in IoT environment. 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 record of MIT-BIH arrhythmia database. The achieved scores indicate the average of 99.758% in R wave detection and the rate of 93.94% in PVC classification.

• Steel and Composite Structures
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• 제17권6호
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• pp.891-906
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• 2014

This study aims to present a three dimensional finite element model to investigate the wave propagation in a concrete filled steel tubular column (CFSC) due to transient impact load. Both the concrete and steel are regarded as linear elastic material. The impact load is simulated by a semi sinusoidal impulse. Besides the CFSC models, a concrete column (CC) model is established for comparing under the same loading condition. The propagation characteristics of the transient waves in CFSC are analyzed in detail. The results show that at the intial stage of the wave propagation, the velocity waves in CFSC are almost the same as those in CC before they arrive at the steel tube. When the waves reach the column side, the velocity responses of CFSC are different from those of CC and the difference is more and more obvious as the waves travel down along the column shaft. The travel distance of the wave front in CFSC is farther than that in CC at the same time. For different wave speeds in steel and concrete material, the wave front in CFSC presents an arch shape, the apex of which locates at the center of the column. Differently, the wave front in CC presents a plane surface. Three dimensional effects on top of CFSC are obvious, therefore, the peak value and arrival time of incident wave crests have great difference at different locations in the radial direction. High-frequency waves on the waveforms are observed. The time difference between incident and reflected wave peaks decreases significantly with r/R when r/R < 0.6, however, it almost keeps constant when $r/R{\geq}0.6$. The time duration between incident and reflected waves calculated by 3D FEM is approximately equal to that calculated by 1D wave theory when r/R is about 2/3.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 제13회 신호처리 합동 학술대회 논문집
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• pp.483-486
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• 2000

심전도에서 QRS complex와 R-wave의 검출은 부정맥 진단, 심전도의 특성점 검출 기준, heart rate variability(HRV) 측정에 있어서 중요하나, 시시각각 변화하는 생리적 변화와 여러 가지 노이즈로 인해 검출이 쉽지 않다 제안된 알고리듬에서는 wavelet filter banks를 이용하여 대칭적 enhanced 신호와 noise 와 같은 very high frequency 성분이 제거된 ECG에 근사화 된 approximated 신호를 얻는다. Enhanced 신호로부터 QRS complex의 위치를 검출하고, 검출된 위치의 주변에서 대칭적 wavelet의 특성이 반영된 dominant한 peak의 위치정보, 즉 R wave의 후보점을 얻는다. 이 위치 정보를 이용하여 enhanced 신호에서 각 peak에서의 크기, approxi-mated 신호에서 각 peak 주변에서의 기울기 변화, 기울기 부호 등을 고려하여 R-wave의 위치를 원래의 ECG 신호에서 얻는다. MIT/BIH database에 적용한 결과 99.6%의 QRS complex검출률과 92.9%의 R-wave 검출률을 보였다.

• Steel and Composite Structures
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• 제46권1호
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• pp.133-141
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• 2023

Based on the third-order shear deformation theory, the wave propagations in doubly curved spherical- and cylindrical- panels reinforced by carbon nanotubes (CNTs) are firstly investigated in present work. The coupled equations of wave propagation for the carbon nanotubes reinforced composite (CNTRC) doubly curved panels are established. Then, combined with the harmonic balance method, the eigenvalue technique is adopted to simulate the velocity-wave number curves of the CNTRC doubly curved panels. In the end, numerical results are showed to discuss the effects of the impact of key parameters including the volume fraction, different shell types (including spherical (R₁=R₂=R) and cylindrical (R₁=R, R₂=→∞)), wave number as well as modal number on the sensitivity of elastic waves propagating in CNTRC doubly curved shells.

• 센서학회지
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• 제22권5호
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• pp.338-345
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• 2013

Premature ventricular contractions are the most common of all arrhythmias and may cause more serious situation like ventricular fibrillation and ventricular tachycardia in some patients. Therefore, the detection of this arrhythmia becomes crucial in the early diagnosis and the prevention of possible life threatening cardiac diseases. Most methods for detecting arrhythmia require pp interval, or the diversity of P wave morphology, but they are difficult to detect the p wave signal because of various noise types. Thus, it is necessary to use noise-free R wave. So, the new approach for the detection of PVC is presented based on the rhythm analysis and the beat matching in this paper. For this purpose, we removed baseline wandering of low frequency band and made summed signals that are composed of two high frequency bands including the frequency component of QRS complex using the wavelet filter. And then we designed R wave detection algorithm using the adaptive threshold and window through RR interval. Also, we developed algorithm to classify PVC using RR interval. The performance of R wave and PVC detection is evaluated by using MIT-BIH arrhythmia database. The achieved scores indicate average detection rate of 99.76%, sensitivity of 99.30% and specificity of 98.66%; accuracy respectively for R wave and PVC detection.

• 한국정보통신학회논문지
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• 제20권2호
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• pp.437-444
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• 2016

일반적인 부정맥 분류 방법의 경우 심방 박동 수와 관련한 PP간격, P모양의 다양성과 같은 조건을 이용하는데, 잡음으로 인해 정확한 P파의 검출이 어렵기 때문에 잡음의 영향을 비교적 적게 받는 R파를 이용하는 것이 유리하다. 따라서 본 연구에서는 R파 중심의 ECG(electrocardiography) 패턴 분석과 템플릿 문턱치를 도입하여 조기수축 부정맥 분류 방법을 제안한다. 이를 위해 형태 연산을 통한 전 처리 과정과 차감 동작 기법을 통해 R파를 검출하였다. 이후 RR 간격의 평균 가중치와 변화율을 이용하여 먼저 조기수축 파형의 패턴을 분류하고, R파의 진폭에 대한 템플릿 문턱값을 통해 조기심실수축과 조기심방수축을 분류하는 알고리즘을 개발하였다. 제안한 방법의 우수성을 입증하기 위해 조기 심방과 심실수축이 30개 이상 포함된 MIT-BIH 6개의 레코드를 대상으로 한 R파의 평균 검출율은 99.77%의 성능을 나타내었고, 조기심실수축과 심방수축 부정맥은 각각 94.91%와 95.76%의 평균 분류율을 나타내었다.

• 한국통신학회논문지
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• 제34권11B호
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• pp.1289-1295
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• 2009

조기심실수축(premature ventricular contractions, PVC)은 가장 보편적인 부정맥으로 심실세동, 심실빈맥 등과 같은 위험한 상황을 유발할 수 있는 가능성을 가지고 있기 때문에 이의 조기 검출은 매우 중요하다. 특히 일반인들의 건강상태를 지속적으로 모니터링 해야하는 헬스케어 시스템에서는 이를 위한 ECG 신호의 실시간 처리가 필요하다. 즉, 최소한의 연산량으로 정확한 R파를 검출하고, 이를 이용하여 PVC를 분류할 수 있는 적합한 알고리즘의 설계가 필요하다. 따라서 본 연구에서는 PVC 실시간 분류를 위한 적응형 문턱치와 윈도우 기반의 R파 검출 알고리즘을 제안한다. 이를 위해 전처리 과정과 적응가변형 문턱치를 통해 R파를 검출하였으며, 검출의 효율성을 위하여 R-R 간격을 이용한 적응가변형 윈도우를 적용하였다. 제안한 알고리즘의 R파 검출 및 PVC 분류 성능을 평가하기 위해서 MIT-BIH 부정맥 데이터베이스를 사용하였다. 성능평가 결과, R파는 평균 99.33%, PVC는 평균 88.86%의 검출결과가 나타났다.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2006년도 정기 학술대회 논문집
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• pp.97-103
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• 2006

A modified one-sided measurement technique is proposed for Rayleigh wave (R-wave) velocity measurement in concrete. The scattering from heterogeneity may affect the waveforms of R-waves in concrete, which may make the R-waves dispersive. Conventional one-sided techniques do not consider the scattering dispersion of R-waves in concrete. In this study, the maximum energy arrival concept is adopted to determine the wave velocity by employing its continuous wavelet transform. Experimental study was performed to show the effectiveness of the proposed method. The present method is applied to monitor the strength development of early-age concrete. A series of experiments were performed on early-age concrete specimens with various curing conditions. Results reveal that the proposed method can be effectively used to measure the R-wave velocity in concrete structures and to monitor the strength development of early-age concrete.