• 제목/요약/키워드: Smart Diagnosis

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Liver Segmentation and 3D Modeling from Abdominal CT Images

  • Tran, Hong Tai;Oh, A Ran;Na, In Seop;Kim, Soo Hyung
    • 스마트미디어저널
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    • 제5권1호
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    • pp.49-54
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    • 2016
  • Medical image processing is a compulsory process to diagnose many kinds of disease. Therefore, an automatic algorithm for this task is highly demanded as an important part to construct a computer-aided diagnosis system. In this paper, we introduce an automatic method to segment the liver region from 3D abdominal CT images using Otsu method. First, we choose a 2D slice which has most liver information from the whole 3D image. Secondly, on the chosen slice, we enhanced the image based on its intensity using Otsu method with multiple thresholds and use the threshold to enhance the whole 3D image. Then, we apply a liver mask to mark the candidate liver region. After that, we execute the Otsu method again to segment the liver region from the chosen slice and propagate the result to the whole 3D image. Finally, we apply preprocessing on the frontal side of 3D images to crop only the liver region from the image.

심전도 신호기반 개인식별을 위한 텐서표현의 다선형 판별분석기법 (A Multilinear LDA Method of Tensor Representation for ECG Signal Based Individual Identification)

  • 임원철;곽근창
    • 스마트미디어저널
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    • 제7권4호
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    • pp.90-98
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    • 2018
  • 심전도 신호는 기본적으로 심장의 전기적 활동에 포함되며 이를 통해 심박수 측정, 심장 박동의 리듬 검사, 심장 이상 진단, 정서 인식 및 생체 인식과 같은 다양한 목적으로 분석 및 활용된다. 본 논문의 목적은 다차원 데이터 배열인 텐서 특성을 가진 다선형 판별분석(MLDA: Multilinear Linear Discriminant Analysis) 기법을 이용하여 개인식별을 수행하고자 한다. MLDA는 상위 차원의 텐서를 포함하는 분류 문제에 대해서 차원 문제를 해결 할 수 있으며, 상호 연관된 부분 공간은 서로 다른 클래스를 구별하기 위해 사용될 수 있다. 제시된 방법의 성능을 검증하기 위해 Physionet의 MIT-BIH데이터베이스를 적용하였다. 이 데이터베이스에 대해 실험한 결과, MLDA는 기존 PCA와 LDA와 비교하여 개인식별 성능이 우수함을 확인하였다.

개인의 건강신념이 모바일 헬스케어 앱 이용의도에 미치는 영향: m헬스 리터러시의 조절효과를 중심으로 (The Influence of Individual's Health Beliefs on the Intention to Use Mobile Healthcare Apps: Focusing on the Moderating Role of mHealth Literacy)

  • 왕진섭;송재민;양성병;윤상혁
    • 한국IT서비스학회지
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    • 제22권1호
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    • pp.95-114
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    • 2023
  • Smart healthcare, combining ICT (Information and Communications Technologies) and medical technologies, has been rapidly emerging. Accordingly, its market has also increased as interest in disease prevention, management, and diagnosis grows due to the COVID-19 pandemic. In particular, using mobile devices to support medical activities, mobile healthcare has been attracting attention as a leading service in the smart healthcare market. However, the intention to use mobile healthcare apps may vary depending on individual beliefs and attitudes. Many studies on the intention to use mobile healthcare apps have used the TAM (Technology Acceptance Model), but there is a lack of studies that have been verified from the perspective of users' health beliefs. This study aims to identify the factors that affect the intention to use mobile healthcare apps based on the HBM (Health Belief Model). Furthermore, it investigates how this influencing mechanism fluctuates based on the user's mHealth literacy, the ability to find and understand health information through mobile. This study contributes to the empirical examination of the intention to use mobile healthcare apps through the HBM. It also offers insights for app providers and public health officials to increase the use of mobile healthcare apps.

IoT data analytics architecture for smart healthcare using RFID and WSN

  • Ogur, Nur Banu;Al-Hubaishi, Mohammed;Ceken, Celal
    • ETRI Journal
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    • 제44권1호
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    • pp.135-146
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    • 2022
  • The importance of big data analytics has become apparent with the increasing volume of data on the Internet. The amount of data will increase even more with the widespread use of Internet of Things (IoT). One of the most important application areas of the IoT is healthcare. This study introduces new real-time data analytics architecture for an IoT-based smart healthcare system, which consists of a wireless sensor network and a radio-frequency identification technology in a vertical domain. The proposed platform also includes high-performance data analytics tools, such as Kafka, Spark, MongoDB, and NodeJS, in a horizontal domain. To investigate the performance of the system developed, a diagnosis of Wolff-Parkinson-White syndrome by logistic regression is discussed. The results show that the proposed IoT data analytics system can successfully process health data in real-time with an accuracy rate of 95% and it can handle large volumes of data. The developed system also communicates with a riverbed modeler using Transmission Control Protocol (TCP) to model any IoT-enabling technology. Therefore, the proposed architecture can be used as a time-saving experimental environment for any IoT-based system.

스마트 설진 전자챠트 시스템 (Smart Tongue Electronic Chart System)

  • 홍유식
    • 한국인터넷방송통신학회논문지
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    • 제12권2호
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    • pp.243-249
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    • 2012
  • 요즈음 전자의무기록시스템을 구축하는 한방 병원이 많아지고 있다. 특히 질병을 과학적으로 진단하기위해서, 한방 병원에서는 맥진기가 개발되고 있다. 그러나, 한방 진료 체제는 아직까지 정확한 병명을 유추하기가 매우 어려운 실정이다. 이러한 문제점을 해결하기 위해서, 본 논문에서는 맥진 및 설진을 동시에 사용 가능한 EMR 챠트 시스템을 제안하였다. 그러므로 본 논문에서는 이러한 문제점을 해결하기위해서, 지능형 전자 챠트 시스템을 이용한 EMR 시스템을 제안하였다. 컴퓨터 모의실험 결과 EMR을 설치한 병원이 기존의 병원보다 편리하고 정확한 진단을 할 수 있음을 확인 하였다.

Calculus of the defect severity with EMATs by analysing the attenuation curves of the guided waves

  • Gomez, Carlos Q.;Garcia, Fausto P.;Arcos, Alfredo;Cheng, Liang;Kogia, Maria;Papelias, Mayorkinos
    • Smart Structures and Systems
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    • 제19권2호
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    • pp.195-202
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    • 2017
  • The aim of this paper is to develop a novel method to determine the severity of a damage in a thin plate. This paper presents a novel fault detection and diagnosis approach employing a new electromagnetic acoustic transducer, called EMAT, together with a complex signal processing method. The method consists in the recognition of a fault that exists within the structure, the fault location, i.e. the identification of the geometric position of damage, and the determining the significance of the damage, which indicates the importance or severity of the defect. The main scientific novelties presented in this paper is: to develop of a new type of electromagnetic acoustic transducer; to incorporate wavelet transforms for signal representation enhancements; to investigate multi-parametric analysis for noise identification and defect classification; to study attenuation curves properties for defect localization improvement; flaw sizing and location algorithm development.

Fiber optic smart monitoring of concrete beam retrofitted by composite patches

  • Kim, Ki-Soo;Chung, Chul;Lee, Ho-Joon;Kang, Young-Goo;Kim, Hong
    • Structural Engineering and Mechanics
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    • 제17권3_4호
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    • pp.347-356
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    • 2004
  • In order to extend the lifetime of buildings and civil infrastructure, patch type fibrous composite retrofitting materials are widely used. Retrofitted concrete columns and beams gain stiffness and strength, but lose toughness and show brittle failure. Usually, the cracks in concrete structures are visible to the naked eye and the status of the structure in the life cycle is estimated through visual inspections. After retrofitting of the structure, crack visibility is blocked by retrofitted composite materials. Therefore, structural monitoring after retrofitting is indispensable and self diagnosis method with optical fiber sensors is very useful. In this paper, we try to detect the peel out effect and find the strain difference between the main structure and retrofitting patch material when they separate from each other. In the experiment, two fiber optic Bragg grating sensors are applied to the main concrete structure and the patching material separately at the same position. The sensors show coincident behaviors at the initial loading, but different behaviors after a certain load. The test results show the possibility of optical fiber sensor monitoring of beam structures retrofitted by the composite patches.

Application of principal component analysis and wavelet transform to fatigue crack detection in waveguides

  • Cammarata, Marcello;Rizzo, Piervincenzo;Dutta, Debaditya;Sohn, Hoon
    • Smart Structures and Systems
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    • 제6권4호
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    • pp.349-362
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    • 2010
  • Ultrasonic Guided Waves (UGWs) are a useful tool in structural health monitoring (SHM) applications that can benefit from built-in transduction, moderately large inspection ranges and high sensitivity to small flaws. This paper describes a SHM method based on UGWs, discrete wavelet transform (DWT), and principal component analysis (PCA) able to detect and quantify the onset and propagation of fatigue cracks in structural waveguides. The method combines the advantages of guided wave signals processed through the DWT with the outcomes of selecting defect-sensitive features to perform a multivariate diagnosis of damage. This diagnosis is based on the PCA. The framework presented in this paper is applied to the detection of fatigue cracks in a steel beam. The probing hardware consists of a PXI platform that controls the generation and measurement of the ultrasonic signals by means of piezoelectric transducers made of Lead Zirconate Titanate. Although the approach is demonstrated in a beam test, it is argued that the proposed method is general and applicable to any structure that can sustain the propagation of UGWs.

디지털 선박 추진 시스템을 위한 임베디드 원격 모니터링 진단 (The Embedded Remote Monitoring Diagnosis for Integration Vessel System)

  • 박세현;노석호
    • 한국정보통신학회논문지
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    • 제17권11호
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    • pp.2708-2716
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    • 2013
  • 본 논문에서는 지능형 디지털 선박의 추진 시스템에서 요구되는 임베디드 원격 모니터링 진단 시스템 개발에 관하여 기술하였다. 원격 모니터링 진단 시스템은 크게 선박 통합 관리시스템, 서버, 원격 모니터링을 담당하는 전용 휴대용 단말기와 상용 스마트폰으로 구성되며, 이를 위하여 사용자 중심의 UI 환경을 가진 통신 프로토콜을 설계하였다. 제안된 시스템은 효율적인 이중구조 통신채널로서 원격 모니터링 시스템에서 간편하면서도 효율적인 통신 프로토콜을 제공하며, 오작동하는 무선통신 채널은 즉시 교체된다. 본 시스템에서는 LCD 화면을 위해 효율적인 임베디드 리눅스 UI를 개발하였으며, 개발된 무선 모니터링 시스템을 평가하기 위하여 실제로 디지털 선박에서 성능을 검증하였다.

자기진단 CPGFRP의 파괴예측기능 평가를 위한 콘크리트 적용실험 (Evaluation of Fracture Detection Function for the Concrete by Self-Diagnosis CPGFRP)

  • 최현수;박진섭;정민수;강병희
    • 한국건축시공학회:학술대회논문집
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    • 한국건축시공학회 2003년도 학술.기술논문 발표회
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    • pp.27-31
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    • 2003
  • To maintain serviceability of concrete structure more than proper it is necessary not only predict service life through periodical monitor but also need monitoring system to recognize optimal time and method for repair. Recently, CPGFRP, replacing some GFRP with CF, is developed and used for monitoring concrete fraction. But dramatic resistance change of CPGFRP is showed below 0.5% strain and it is not small strain in terms of monitoring micro crack in concrete. In other word, monitoring with CF is not suitable in low stress hut hight stress. In this study, we accessed applicable possibility and reliability of CPGFRP composite as monitoring sense that is proved very sensitive to stress through domestic and oversea previous study. CPGFRP composite plays a role in specimen like steel and increases flexural strength. CPGFRP composite shows resistance increasement in micro crack. In particular, CPUFRP is more sensitive than strangage in low stress. Resistance change ratio curve is very similar to strain curve so sensitivity and reliability is very excellent to monitor concrete fracture.

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