• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2011년도 한국컴퓨터종합학술대회논문집 Vol.38 No.1(C)
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• pp.96-97
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• 2011

Heterogeneity in different Health Information Systems (HIS) processes persists to be the most demanded problem to be resolved in healthcare domain. The only way to resolve this problem is to practice health standards. One of such standards is Health Level Seven (HL7), used for the communication of medical information between healthcare systems. HL7 V3 has the aim to support all healthcare workflows. It defines series of electronic messages called interactions to support healthcare workflows. These interactions are part of the Interaction Model. Different healthcare organizations can conform to different process workflows based on their requirements. The heterogeneity in workflows results in communication blockade between sender and receiver healthcare organizations. We propose Interaction Ontology in order to cater the heterogeneity in workflows and provide process interoperability.

• Journal of Information Processing Systems
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• 제16권6호
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• pp.1238-1249
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• 2020

Throughout the world, aging populations and doctor shortages have helped drive the increasing demand for smart healthcare systems. Recently, these systems have benefited from the evolution of the Internet of Things (IoT), big data, and machine learning. However, these advances result in the generation of large amounts of data, making healthcare data analysis a major issue. These data have a number of complex properties such as high-dimensionality, irregularity, and sparsity, which makes efficient processing difficult to implement. These challenges are met by big data analytics. In this paper, we propose an innovative analytic framework for big healthcare data that are collected either from IoT wearable devices or from archived patient medical images. The proposed method would efficiently address the data heterogeneity problem using middleware between heterogeneous data sources and MapReduce Hadoop clusters. Furthermore, the proposed framework enables the use of both fog computing and cloud platforms to handle the problems faced through online and offline data processing, data storage, and data classification. Additionally, it guarantees robust and secure knowledge of patient medical data.

• 한국정보시스템학회:학술대회논문집
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• 한국정보시스템학회 2003년도 춘계학술대회
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• pp.271-285
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• 2003

In the conduct of this study, a web-enabled healthcare system for the management of hypertension was implemented through a hyperlink-based inference approach. The hyperlink-based inference platform implemented using the hypertext capacity of HTML which ensured accessibility, multimedia facilities, fast response, stability, ease of use and upgrade, and platform independency of expert systems. Many HTML documents, which are hyperlinked to each other based on expert rules, were uploaded beforehand to perform the hyperlink-based inference. The HTML documents were uploaded and maintained automatically by our proprietary tool called the Web-Based inference System (WeBIS) that supports a graphical user interface (GUI) for the input and edit of decision graphs. Nevertheless, the editing task of the decision graph using the GUI tool is a time consuming and tedious chore when the knowledge engineer must perform it manually. Accordingly, this research implemented an automatic generator of the decision graph for the management of hypertension. As a result, this research suggests a methodology for the development of Web-enabled healthcare systems using the hyperlink-based inference approach and, as an example, implements a Web-enabled healthcare system for hypertension, a platform which peformed especially well in the areas of speed and stability.

• 전자공학회논문지CI
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• 제45권4호
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• pp.64-72
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• 2008

현재 많은 연구자들이 저비용, 저 전력을 필요로 하는 센서 네트워크를 활용하여 사람의 건강 상태를 실시간으로 모니터링 할 수 있는 u-Healthcare(ubiquitous Healthcare) 시스템을 구축하는데 심혈을 기울이고 있다. u-Healthcare 시스템은 센서 네트워크로부터 수집된 대량의 생체신호를 신속히 처리 분석하여 의료진에게 전달함으로써 시간과 장소에 관계없이 환자에게 적절한 의료 서비스를 제공할 수 있다. 기존의 u-Healthcare 시스템을 통해 환자의 건강상태 모니터링이 가능하지만 수집된 생체 신호를 신속히 분석하여 의학적으로 의미 있는 결과를 도출하는 것은 아직 어려운 상황이다. 본 논문에서는 대량의 생체신호를 고속으로 연산할 수 있는 그리드 컴퓨팅 기술을 센서 네트워크와 결합하여 환자의 생체신호를 측정하여 의학적으로 의미 있는 결과를 도출하고자 한다. 서로 다른 프로토콜을 사용하는 두 네트워크의 연동을 위해 게이트웨이가 필요하며, 게이트웨이에는 효과적인 u-Healthcare서비스 제공을 위해 센서 네트워크의 효율적 관리 및 제어, 생체신호 실시간 모니터링, 그리드 네트워크와 연계된 통신 서비스 등의 기능이 포함되어야 한다. 본 논문에서는 진보된 u-Healthcare 시스템을 구축하기 위하여 센서 네트워크와 그리드 네트워크를 유연하게 연동할 수 있는 센서그리드 게이트웨이를 설계하고 구현된 결과를 제시한다.

• 의료ㆍ복지 건축 : 한국의료복지건축학회 논문집
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• 제8권1호
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• pp.37-43
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• 2002

Healthcare systems around the world are struggling to cope with the pressures of rising costs, aging populations, and decisions about how to allocate and pay for seemingly limitless advances in high-technology medical procedures. Today healthcare environments are also changing greatly in Korea. The United States healthcare is being reinvented by reducing the costs and bringing service close to the consumer, and multi-strategies are being used to strive in the market driven shift. This study is aiming to get the lesson and direction of the future healthcare facilities in Korea by analysing the past and current trends of healthcare facilities in U.S..

• Journal of Communications and Networks
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• 제16권4호
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• pp.465-474
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• 2014

Wireless sensor network (WSN) is considered to be one of the most important research fields for ubiquitous healthcare (u-healthcare) applications. Healthcare systems combined with WSNs have only been introduced by several pioneering researchers. However, most researchers collect physiological data from medical nodes located at static locations and transmit them within a limited communication range between a base station and the medical nodes. In these healthcare systems, the network link can be easily broken owing to the movement of the object nodes. To overcome this issue, in this study, the fast link exchange minimum cost forwarding (FLE-MCF) routing protocol is proposed. This protocol allows real-time multi-hop communication in a healthcare system based on WSN. The protocol is designed for a multi-hop sensor network to rapidly restore the network link when it is broken. The performance of the proposed FLE-MCF protocol is compared with that of a modified minimum cost forwarding (MMCF) protocol. The FLE-MCF protocol shows a good packet delivery rate from/to a fast moving object in a WSN. The designed wearable platform utilizes an adaptive linear prediction filter to reduce the motion artifacts in the original electrocardiogram (ECG) signal. Two filter algorithms used for baseline drift removal are evaluated to check whether real-time execution is possible on our wearable platform. The experiment results shows that the ECG signal filtered by adaptive linear prediction filter recovers from the distorted ECG signal efficiently.

• 디지털융복합연구
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• 제15권11호
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• pp.251-259
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• 2017

최근 헬스케어 산업이 사물인터넷(Internet of Thing) 기술과 결합한 스마트 헬스케어 산업이 주목을 받고 있다. 스마트 헬스케어란 애플리케이션, 웨어러블 기기, 플랫폼 등 정보통신 기술은 기반으로 한 건강관리 및 의료 서비스를 말한다. 스마트 헬스케어 산업은 차세대 산업분야인 6T 중 가장 활발한 IT(Information Technology)와 BT(Bio Technology)간의 결합으로 차세대 스마트 헬스케어 기기들이 늘어나고 있다. 다양한 스마트 헬스케어 기기들이 나타남에 따라 스마트 헬스케어 시스템이 다른 유기적 연동 여부와 보안성 품질 여부가 중요한 평가요소가 되고 있다. 본 논문에서는 이를 위해 스마트 헬스케어 시스템의 특성 및 서비스 유형을 조사하고 스마트 헬스케어 시스템의 기술 및 산업 동향을 분석하였다. 이를 바탕으로 스마트 헬스케어 시스템 평가 요구사항을 도출하여 스마트 헬스케어 시스템의 보안성 평가방법과 품질평가기준을 개발하고자 한다. 이는 스마트 헬스케어 시스템의 품질 향상 및 신뢰도 높은 제품 개발을 유도 할 수 있으며, 기술보호 장벽에 대처 할 수 있는 핵심기술로 기대된다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2013년도 춘계학술발표대회
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• pp.470-471
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• 2013

Accuracy of mappings is the key for achieving true interoperability among different healthcare systems. The initial step towards interoperable healthcare systems is compliancy with healthcare standards (HL7, openEHR, CEN 13606). Ontologies for these standards are developed that require ontology matching to generate generalized ontology mappings. Organizations conform to specific concepts of different standards based on their requirements. This step is called as conformance claims and is based on Personalized-Detailed Clinical Model. It invalidates some of the generalized mappings because of non-conformed concepts and leads to the necessity of the proposed technique of customized ontology mappings. These customized ontology mappings compliment the generalized ontology mapping to increase the level of accuracy of mappings and thus achieving data interoperability. The proposed system ensures quality of care to patients by timely delivery of healthcare information.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권3호
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• pp.1014-1025
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• 2020

Cloud computing services changed the way the data are managed across the healthcare system that can improve patient care. Currently, most healthcare organizations are using cloud-based applications and related services to deliver better healthcare facilities. But architecting a cloud-based healthcare system needs deep knowledge about the working nature of these services and the requirements of the healthcare environment. The success is based on the usage of appropriate cloud services in the architecture to manage the data flow across the healthcare system.Cloud service providers offer a wide variety of services to ingest, store and process healthcare data securely. The top three public cloud providers- Amazon, Google, and Microsoft offers advanced cloud services for the solution that the healthcare industry is looking for. This article proposes a framework that can effectively utilize cloud services to handle the data flow among the various stages of the healthcare infrastructure. The useful cloud services for ingesting, storing and analyzing the healthcare data for the proposed framework, from the top three cloud providers are listed in this work. Finally, a cloud-based healthcare architecture using Amazon Cloud Services is constructed for reference.

• Healthcare Informatics Research
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• 제24권4호
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• pp.327-334
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• 2018

Objectives: The objective of this study was to investigate the relationship between the level of Electronic Medical Record (EMR) system adoption and healthcare information technology (IT) infrastructure. Methods: Both survey and various healthcare administrative datasets in Korea were used. The survey was conducted during the period from June 13 to September 25, 2017. The chief information officers of hospitals were respondents. Among them, 257 general hospitals and 273 small hospitals were analyzed. A logistic regression analysis was conducted using the SAS program. Results: The odds of having full EMR systems in general hospitals statistically significantly increased as the number of IT department staff members increased (odds ratio [OR] = 1.058, confidence interval [CI], 1.003-1.115; p = 0.038). The odds of having full EMR systems was significantly higher for small hospitals that had an IT department than those of small hospitals with no IT department (OR = 1.325; CI, 1.150-1.525; p < 0.001). Full EMR system adoption had a positive relationship with IT infrastructure in both general hospitals and small hospitals, which was statistically significant in small hospitals. The odds of having full EMR systems for small hospitals increased as IT infrastructure increased after controlling the covariates (OR = 1.527; CI, 1.317-4.135; p = 0.004). Conclusions: This study verified that full EMR adoption was closely associated with IT infrastructure, such as organizational structure, human resources, and various IT subsystems. This finding suggests that political support related to these areas is indeed necessary for the fast dispersion of EMR systems into the healthcare industry.