• Journal of information and communication convergence engineering
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• v.20 no.1
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• pp.31-40
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• 2022

Coronary heart disease (CHD) is a comorbidity of COVID-19; therefore, routine early diagnosis is crucial. A large number of examination attributes in the context of diagnosing CHD is a distinct obstacle during the pandemic when the number of health service users is significant. The development of a precise machine learning model for diagnosis with a minimum number of examination attributes can allow examinations and healthcare actions to be undertaken quickly. This study proposes a CHD diagnosis model based on feature selection, data balancing, and ensemble-based classification methods. In the feature selection stage, a hybrid SVM-GA combined with fast correlation-based filter (FCBF) is used. The proposed system achieved an accuracy of 94.60% and area under the curve (AUC) of 97.5% when tested on the z-Alizadeh Sani dataset and used only 8 of 54 inspection attributes. In terms of performance, the proposed model can be placed in the very good category.

• Journal of Internet Computing and Services
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• v.12 no.2
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• pp.135-147
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• 2011

As the number of elderly people living alone has been increasing in the recent years, systems for their safety have been required, and some related services or pilot systems have been operating. These systems provide the monitoring service for the activities of the elderly people living alone with indoor location tracking technology using the various sensors. However, most systems provide services on expensive infrastructure such as attached tags and mobile devices. In this point, this paper attempts to suggest a system based on low cost sensors to collect event data in home environment. And a main characteristic of the system is that people can monitor the results of provided services through web browser in real time and the system can provide related context information to guardians and health care managers through SMS of mobile phone.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.5
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• pp.141-150
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• 2014

In recent years, because of the development of ubiquitous technology in healthcare research is actively progress. Especially, healthcare service area is change to home for the elderly or patients from hospital. The technology to identify residents in a home is crucial for smart home application services. However, existing researches for resident identification have several problems. In this case, residents are needed to attach of various sensors on their body. Also relating private life, it is difficult to apply to resident's environment. In this paper, we used constraint-free sensor and unconscious sensor to solve these problems and we limited using of sensor and indoor environment in the way of working economical price systems. The way of multi-resident identification using only these limited sensors, we selected elements of personal identifications and suggested the methods in giving the weight to apply these elements to systems. And we designed the SABA mechanism to tract their location and identify the residents. It mechanism can distinguish residents through the sensors located each space and can finally identify them by using the records of their behaviors occurred before. And we applied the mechanism designed for applications to approve this location tracking system. We verified to the location tracking system performance according to the scenario.

• Journal of the Korea Society of Computer and Information
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• v.13 no.5
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• pp.117-124
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• 2008

It improves human being's life quality that all people can have mure convenient medical service under pervasive computing environment. For a pervasive health care application for cardiac patient, we've implemented a health care system, which is composed of three parts. Various sensors monitor outer as well as inner environment of human such as temperature, humidity, light and electrocardiogram, etc. These sensors form a network based on Zigbee. And medical information server accumulates sensing values and performs back-end processing. To simply transfer these sensing values to a medical team is a simple level's medical service. So, we've designed a new service model based on back propagation neural network for more improved medical service. Our experiments show that a proposed healthcare system can give high level's medical service because it can recognize human's context more concretely.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10a
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• pp.372-376
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• 2006

본 논문에서는 홈 내에서 헬스케어 상황정보 서비스를 제공하기 위한 모바일 프락시에 대해 기술한다. 모바일 프락시는 헬스케어 홈 서비스의 목적에 따라 분산자원의 통합 및 맞춤형 관리모델인 분산객체그룹 프레임워크를 기반으로 한다. 모바일 프락시의 주요 기능은 이동성을 지원 및 멀티미디어 스트림 동기화 그리고 그룹통신 지원한다. 특히, 클라이언트의 가용환경에 따라 수행객체에 대한 이동성을 제공한다. 이를 기반으로 헬스케어 상황정보 서비스를 제공하기 위해 사용되는 상황정보는 거주자의 위치, 홈 내에 설치된 센서/기기로부터 수집된 위치, 건강 그리고 쾌적환경 정보를 포함한다. 또한 헬스케어 상황정보 서비스를 위한 응용객체, 자원들의 그룹관리 지원 DOGF를 기반으로 이동성 지원 컴포넌트인 모바일프락시는 거주자 위치이동에 따라 적합한 헬스케어 상황정보 서비스를 제공한다. 모바일프락시를 이용한 헬스케어 상황정보 서비스는 헬스케어 지원 음악치료, 원격상담 서비스와 처방 주의 및 스케줄 알림서비스를 구현했다. 끝으로 제안한 환경에서 거주자의 위치, 시간 및 상황인식에 따라 구현하여 수행한 헬스케어 상황정보 서비스 결과를 보였다.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06d
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• pp.64-66
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• 2006

본 논문에서는 실내 거주자의 위치를 기반으로 분산객체그룹 프레임워크의 구성요소인 모바일 프락시(Mobile Proxy)를 이용하여 상황정보 지원 시스템 구축에 대해 기술하였다. 본 시스템은 가정 내 거주자의 이동을 고려하여 건강상태 및 상황정보를 제공하는 헬스케어 상황정보 서비스를 수행한다. 이를 위해 분산객체그룹 프레임워크의 그룹관리 서비스는 가정 내 위치 탐색 및 추적 센서와 서비스 수행객체 및 다양한 출력 장치들을 거실이나 침실과 같은 분할된 영역으로 그룹화하고, 모바일 프락시는 서비스를 요청하는 이동 사용자의 위치를 기반으로 헬스케어 서비스 수행의 연속성을 지원한다. 그리고 상황정보에 따라 헬스케어 맞춤형 정보 서비스가 지원되도록 했다. 상황정보 지원 시스템이 제공하는 서비스는 이동성을 고려한 멀티미디어 서비스와 시간 및 위치에 따라 처방 주의 정보 및 스케줄 알림 서비스로 구현했으며, 상황정보 지원 헬스케어 서비스의 수행 결과를 원격 데스크 탑과 상황정보 서비스 인터페이스를 통해 확인했다.

• Journal of Service Research and Studies
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• v.13 no.1
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• pp.76-95
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• 2023

As information and communications technology-based "smart hospitals" and "digital healthcare" have become a hot topic in the healthcare field, hospital mobile apps are gaining attention; but, the utilization rate is low due to lack of publicity, unstable systems, and late updates. In this situation, systematic research is needed to increase the utilization rate of hospital mobile apps, but related research has been rare. Therefore, this study integrates the information systems success model (ISSM) from the technical perspective and the expectation-confirmation model (ECM) from the cognitive perspective to demonstrate the influence mechanism on the continuous use intention of hospital mobile apps. For this purpose, an online survey was conducted among 181 Korean adults who have used hospital mobile apps. The results of the structual equation modeling showed that most of the quality factors have significant effects on expectation confirmation, perceived usefulness, and satisfaction. Additionally, expectation confirmation significantly affects perceived usefulness and satisfaction, and both perceived usefulness and satisfaction significantly affect the continuous use intention of hospital mobile apps. This study is of importance in that it integrates the ISSM and ECM and applies them to the context of using hospital mobile apps, which are underutilized in the healthcare field, and provides practical implications for increasing the utilization rate of hospital mobile apps and operating effective and efficient services through the findings.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.3
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• pp.734-741
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• 2008

The modern people effort to lead good life. Specially, the patients which prevention of a disease only is cure from this diabetes patient, the old and weak, the hospitals needing a treatment through exercises, and receive medical treatment in houses cure exercise according to exercise prescription. These papers developed a Ubiquitous Care Management system based on Zigbee. This is a system supporting so as accumulation manages the exercise history information that occurred when get exercises prescription, and exercise systematically, and to do preventive of a disease. Can confirm own exercise history and health information through web pages, and this system notifies contents about an exercise treatment to patients as use a cellular phone.

• Korea Journal of Hospital Management
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• v.8 no.1
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• pp.81-94
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• 2003

This paper aims at developing a prediction model and analyzing a sensitivity for the outpatient's overall satisfaction on utilizing hospital services by using data mining techniques within the context of customer satisfaction. From a total of 900 outpatient cases, 80 percent were randomly selected as the training group and the other 20 percent as the validation group. Cases in the training group were used in the development of the CHAID and Neural Networks. The validation group was used to test the performance of these models. The major findings may be summarized as follows: the CHAID provided six useful predictors - satisfaction with treatment level, satisfaction with healthcare facilities and equipments, satisfaction with registration service, awareness of hospital reputation, satisfaction with staffs courtesy and responsiveness, and satisfaction with nurses kindness. The prediction accuracy rates based on MLP (77.90%) is superior to RBF (76.80%).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.8
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• pp.1494-1502
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• 2016

With the increasing availability of medical sensors and Internet of Things(IoT) devices for personal use, considering the interaction with users, it is planned to add intelligent function design to the fashionable jewelry, and develop composite multi-function intelligent jewelry through sensors identification. By means of IoT technology, while possessing communication function of intelligent jewelry, the function of intelligent jewelry can be expanded to the linkage network. In order to rapidly manage the mass data produced by intelligent jewelry sensors based on IoT, an intelligent jewelry system for health management is designed and an ontology model of intelligent jewelry system based on IoT is worked out. After the state of the services through the smart phone application is shown. The application provides a personalized service to the user and to determine the risk to show the guide lines according to the disease.