• 한국통신학회논문지
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• 제41권2호
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• pp.244-253
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• 2016

ECG 신호에서 QRS군은 매우 중요한 심실의 탈분극 상태 정보를 제공한다. 자동으로 심전도 신호를 분석하기 위해서는 $QRS_{onset}$ 과 $QRS_{offset}$ 에 대한 정확한 정보가 중요하다. 본 연구에서는 먼저 QRS군의 전위값 변화량 및 $R_{peak}$ 와의 거리를 이용하여 Q파와 R파의 접속 부분 그리고 R파와 S파의 접속 부분을 구하였다. 다음 단계에서는 이를 기준으로 적분연산을 이용하여 $QRS_{onset}$ 과 $QRS_{offset}$ 을 검출하였다. 알고리즘의 성능을 평가하기위해 PhysioNet QT database를 사용하여 심장 전문의가 수작업으로 표시한 결과에 대한 평균과 표준편차를 계산하였다. 실험결과에서 제안한 알고리즘의 표준편차는 전문의사가 수용할 수 있는 허용치 범위 안에 속하며, 다른 알고리즘보다 더 우수함을 나타낸다.

• 항공우주시스템공학회지
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• 제16권5호
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• pp.70-77
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• 2022

본 논문에서, 데이터베이스 생성 및 관리 시스템은 미소 픽셀 공중 표적 인식을 위해 제안된다. 제안된 시스템은 1)비행 테스트 비디오 프레임에 의한 직접 이미지 추출, 2) 자동 이미지 보관, 3) 이미지 데이터 레이블링 및 메타 데이터 주석, 4) 컬러 채널 변환, 5) HOG/LBP 기반 소화소 대상 증강 이미지 데이터 생성의 다섯가지 주요 기능으로 구성된다. 제안하는 프로그램은 파이썬 기반의 PyQt5와 OpenCV를 이용하여 구성하였고 공중 표적 인식을 위한 이미지 데이터셋은 제안한 시스템을 이용해 생성했으며 비행 실험으로 부터 수집된 영상을 입력영상으로 사용하였다.

• 한국전자통신학회논문지
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• 제10권4호
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• pp.521-526
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• 2015

개인의 신원을 확인하기 위해 인간의 생물학적 특성을 사용하는 방법에 대한 연구가 활발히 진행되고 있다. 심전도를 이용한 생체 인식 기술은 피험자에 피부자극을 일으키지 않고 위조가 어렵다. 기존의 생체 인식 시스템인 지문, 얼굴 등의 인식시스템과 쉽게 접목이 가능하여 다중 생체 인식 시스템으로 응용할 수 있다. 본 논문에서는 이산 웨이블릿 변환 계수를 사용한 심전도의 파형 특성분석법으로 개인을 식별하는 방법을 제안하였다. 심전도 신호의 특징추출은 총 9개의 이산 웨이블릿 변환 계수를 대상으로 상관 계수 분석으로 수행하였다. 식별은 각 클래스의 특징벡터를 입력으로 오류 역전파 신경망을 적용하여 수행하였다. MIT-BIH QT 데이터베이스내 24명의 심전도에 대해 98.88%의 식별율을 나타냈다.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2023년도 제68차 하계학술대회논문집 31권2호
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• pp.665-667
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• 2023

본 논문에서는 효율적인 쇼핑 경험을 제공하기 위해 숏카트라는 자동화된 쇼핑 카트 시스템을 제안한다. 숏카트는 사용자의 편의성을 높이기 위해 자동화 기술을 활용하며, 사용자가 상품을 선택하면 카메라를 통해 바코드를 인식하고, Python을 활용하여 바코드값을 읽어온다. 읽어온 바코드 값을 데이터베이스의 바코드 값들과 비교하여 동일한 값을 가진 상품을 사용자의 장바구니에 자동으로 추가한다. 이를 통해 사용자는 편리하게 상품을 선택하고, 계산 과정을 자동화하여 시간을 절약할 수 있다. 또한, GUI 프로그램을 PyQT로 개발하여 사용자에게 시각적으로 장바구니 내용을 표시해 준다.

• Genomics & Informatics
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• 제9권4호
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• pp.143-151
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• 2011

In this study, we propose a novel, intuitive method of constructing an expression quantitative trait (eQT) network that is related to the metabolic syndrome using LOD scores and peak loci for selected eQTs, based on the concept of gene-gene interactions. We selected 49 eQTs that were related to insulin resistance. A variance component linkage analysis was performed to explore the expression loci of each of the eQTs. The linkage peak loci were investigated, and the "support zone" was defined within boundaries of an LOD score of 0.5 from the peak. If one gene was located within the "support zone" of the peak loci for the eQT of another gene, the relationship was considered as a potential "directed causal pathway" from the former to the latter gene. SNP markers under the linkage peaks or within the support zone were searched for in the database to identify the genes at the loci. Two groups of gene networks were formed separately around the genes IRS2 and UGCGL2. The findings indicated evidence of networks between genes that were related to the metabolic syndrome. The use of linkage analysis enabled the construction of directed causal networks. This methodology showed that characterizing and locating eQTs can provide an effective means of constructing a genetic network.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.328-330
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• 2004

In this paper, ECG based cardiac disease diagnosis models are developed. Conventionally, ECG monitoring equipments can only measure and store ECG signals and they always require medical doctor's diagnosis actions which are not desirable for continuous ambulatory monitoring and diagnosis healthcare systems. In this paper, two kinds of neural based self cardiac disease diagnosis engines are developed and tested for four kinds of diseases, sinus bradycardia, sinus tachycardia, left bundle branch block and right bundle branch block. For diagnosis engines, error backpropagation neural network (BP) and probabilistic neural network (PNN) were applied. Five signal features including heart rate, QRS interval, PR interval, QT interval, and T wave types were selected for diagnosis characteristics. To show the validity of proposed diagnosis engine, MIT-BIH database were used to test. Test results showed that BP based diagnosis engine has 71% of diagnosis accuracy which is superior to accuracy of PNN based diagnosis engine. However, PNN based diagnosis engine showed superior diagnosis accuracy for complex-disease diagnoses than BP based diagnosis engine.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.325-327
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• 2004

ECG limb lead II signal widely used to diagnosis heart diseases and it is essential to detect ECG events (onsets, offsets and peaks of the QRS complex P wave and T wave) and extract them from ECG signal for heart diseases diagnoses. However, it is very difficult to develop standardized feature extraction formulas since ECG signals are varying on patients and disease types. In this paper, simple feature extraction method from normal and abnormal types of ECG signals is proposed. As a signal features, heart rate, PR interval, QRS interval, QT interval, interval between S wave and baseline, and T wave types are extracted. To show the validity of proposed method, Right Bundle Branch Block (RBBB), Left Bundle Branch Block (LBBB), Sinus Bradycardia, and Sinus Tachycardia data from MIT-BIH arrhythmia database are used for feature extraction and the extraction results showed higher extraction capability compare to conventional formula based extraction method.

• Journal of information and communication convergence engineering
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• 제19권2호
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• pp.93-101
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• 2021

Cardiac arrhythmias are common heart diseases and generally cause sudden cardiac death. Electrocardiogram (ECG) is an effective tool that can reveal the electrical activity of the heart and diagnose cardiac arrhythmias. We propose detection of P waves based on QRST cancellation zero-one substitution. After preprocessing, the QRST segment is determined by detecting the Q wave start point and T wave end point separately. The Q wave start point is detected by digital analyses of the QRS complex width, and the T wave end point is detected by computation of an indicator related to the area covered by the T wave curve. Then, we determine whether the sampled value of the signal is in the interval of the QRST segment and substitute zero or one for the value to cancel the QRST segment. Finally, the maximum amplitude is selected as the peak of the P wave in each RR interval of the residual signal. The average detection rate for the QT database was 97.67%.

• 한국멀티미디어학회논문지
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• 제19권6호
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• pp.1034-1042
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• 2016

The detection of P-waves and T-wave in the electrocardiogram signal analysis is an important issue. But the accuracy of the boundary detection algorithm is an insufficient level in the change of slow transition in the signal compared to the QRS complex. This study proposes an algorithm to detect P-wave and T-wave sequentially after determining local baseline using QRS complex. First, we detected the peak points based on local baseline and determined the onset and offset through the calculation of the area of the section. After modifying the baseline using detected waveform, we detected the other waveform in the same way and separated the P-wave and the T-wave based on the location. We used the PhysioNet QT database to evaluate the performances of the algorithm, and calculate the mean and the standard deviations. The experiment results show that standard deviations are under the tolerances accepted by expert physicians, and outperform the results obtained by the other algorithms.

• Nuclear Engineering and Technology
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• 제55권10호
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• pp.3854-3859
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• 2023

Background: This study aims to develop an evaluator that can quickly and accurately evaluate the shielding of low-energy industrial radiation generators. Methods: We used PyQt to develop a graphical user interface (GUI)-based program and employed the calculation methodology reported in the National Council on Radiation Protection and Measurements (NCRP)-49 for shielding calculations. We gathered the necessary factors for shielding evaluation using two libraries designed for Python, pandas and NumPy, and processed them into a database. We verified the effectiveness of the proposed program by comparing the results with those from safety reports of six domestic facilities. Results: After verifying the effectiveness of the program using the NCRP-49 example, we obtained an average error rate of 1.73%. When comparing the facility safety report and results obtained using the program, we found that the error rate was between 1.09% and 6.51%. However, facilities that did not use a defined shielding methodology were underestimated by 31.82% compared with the program (the final barrier thickness satisfied the shielding standard). Conclusion: The developed program provides a fast and accurate shielding evaluation that can assist personnel that work in radiation generator facilities and government officials in reviewing safety.