• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.392-394
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• 2007

Healthcare word means that supports and manages services related to health for prevent, cure, manage disease and stabilize physically or mentally. This paper presents base technology that supports a remote medical service to people including elderly and asthmatics comfortably. To be done, we gathered information which was acquired from SaO2(Saturation of Oxygen) Sensors and built HMI System based on wireless environment using these information.

• ETRI Journal
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• v.41 no.4
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• pp.515-527
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• 2019

This paper discusses the design, implementation, and potential use of an ontology-based mobile pediatric consultation and monitoring system, which is a smart healthcare expert system for pediatric patients. The proposed system provides remote consultation and monitoring of pediatric patients during their illness at places distant from medical service areas. The system not only shares instant medical data with a pediatrician but also examines the data as a smart medical assistant to detect any emergency situation. In addition, it uses an inference engine to infer instant suggestions for performing certain initial medical treatment steps when necessary. The applied methodologies and main technical contributions have three aspects: (a) pediatric consultation and monitoring ontology, (b) semantic Web rule knowledge base, and (c) inference engine. Two case studies with real pediatric patients are provided and discussed. The reported results of the applied case studies are promising, and they demonstrate the applicability, effectiveness, and efficiency of the proposed approach.

• Journal of Sensor Science and Technology
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• v.32 no.6
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• pp.378-385
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• 2023

Human biosignals provide essential information for diagnosing diseases such as dementia and Parkinson's disease. Owing to the shortcomings of current clinical assessments, noninvasive solutions are required. Machine learning (ML) on wearable sensor data is a promising method for the real-time monitoring and early detection of abnormalities. ML facilitates disease identification, severity measurement, and remote rehabilitation by providing continuous feedback. In the context of wearable sensor technology, ML involves training on observed data for tasks such as classification and regression with applications in clinical metrics. Although supervised ML presents challenges in clinical settings, unsupervised learning, which focuses on tasks such as cluster identification and anomaly detection, has emerged as a useful alternative. This review examines and discusses a variety of ML algorithms such as Support Vector Machines (SVM), Random Forests (RF), Decision Trees (DT), Neural Networks (NN), and Deep Learning for the analysis of complex clinical data.

• Journal of Advanced Navigation Technology
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• v.12 no.4
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• pp.366-371
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• 2008

The IT communication technology including sensors, RFlD, wire/wireless communication, DBMS and motion picture transmission can be applied to industry and medical fields. In this paper, patient monitoring system which composed of excrements sensing, remind supporting and web-remote monitoring system has been designed and implemented. It has been shown that excrements sensing system had capabilities of monitoring a maximum of 64 patients, remind support system can be used for helping memory of the patients with Alzheimer's disease, and web remote motion picture monitoring system can monitor patients over the internet with 1 to 15 frames/sec.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.3
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• pp.3-12
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• 2015

Recently, various studies have been attempted to provide a biological information monitoring service through integrating with the web service. The medical information transmission standard ISO/IEEE 11073 PHD defines the optimized exchange protocol ISO/IEEE 11073-20601 based on the No-IP to exchange the biometric information between the ISO/IEEE 11073 agent and the manager. It's system structure based on the No-IP using ISO/IEEE 11073-20601 is not suitable for providing a remote biological information monitoring services. That is because it is difficult to provide to control and manage the biological information measurement devices, which have installed IP protocol stack at the remote. Furthermore, ACSE and CMDISE in ISO/IEEE 11073-20601 are not suitable to provide U-healthcare services based on IoT because they are complicated and difficult to implement it caused by the structural complexity. In order to solve the problems, in this paper, we propose the biological information monitoring architecture based on ISO/IEEE 11073 DIM/REST of IoT environment to provide the biological information monitoring service based on IoT. To do this, we designed biological information monitoring system architecture based on IoT and the message exchange protocol of ISO/IEEE 11073 DIM/REST between the ISO/IEEE 11073 agent and the ISO/IEEE 11073 manager. In order to verify the realistic possibility of the proposed system architecture, we developed the service prototype.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.3B
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• pp.275-286
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• 2011

As the 21st century paradigm of healthcare service changes from post-therapeutic treatment to disease prevention and management in advance, the M2M-based u-healthcare application service is increasingly important. M2M-based u-healthcare application service uses mobile handsets equipped with sensors to measure vital information, and the medical staff in remote locations can manage the health of the patient or the public in real time. In this paper, IEEE/HL7 translation gateway, utilizing the gateway based on M2M u-healthcare application service structure, which is based on international standards, has been designed and implemented. Specifically, the gateway between ISO/IEEE 11073 standards and ANSI HL7 has been developed. The former defines the protocol for the exchange of information between the agent device and the manger devices for measuring and handling biological signal, and the latter defines the application layer protocol for the exchange of various healthcare information systems. Finally, in order to demonstrate the functionality of the proposed architecture, the M2M-based U-healthcare application service based on IEEE/HL7 translation gateway, utilizing the gateway, has been developed which can measure, collect and process a variety of vital signs such as ECG or SpO2.

• Journal of the Korea Convergence Society
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• v.12 no.1
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• pp.369-377
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• 2021

Augmented reality smart-glass enables healthcare providers to use patient and their care related information without interference of workflow. In addition, augmented reality smart-glass simulation had advantages in improving competency via remote collaboration and real-time information sharing. This study investigated perception and attitude regarding augmented reality smart glass based healthcare simulation on three different groups of healthcare major students, computer major students, developers and faculties. Using convenience sampling method, data were obtained from 95 participants and statistical analysis were performed using SPSS 25.0. Developer and faculty group showed the highest scores, followed by healthcare major students. There was the high expectation on augmented reality smart-glass for skill acquisition and the high performance and big screen were essential features of device. The findings of this study revealed that differences between healthcare and computer major students exist and strategies to reduce those gaps are required to adopt augmented reality smart glass in healthcare settings.

• Journal of Biomedical Engineering Research
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• v.28 no.5
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• pp.657-664
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• 2007

Stroke patients need regular medical treatments and rehabilitation training from their doctors. However, severe aftereffects caused by stroke allow them minimum activities, which make it difficult for them to visit doctor. Recently, electric brain stimulation treatment has been found to be better way compared to conventional ones and many are interested in using this method for the treatment of stroke. In this study, we have developed a remote medical treatment system using wireless electric brain stimulator that can help the stroke patients to get a treatment without visiting their doctors. The developed remote medical treatment system connects the doctors to the brain stimulator implanted in the patients via the internet and ZigBee communication built in the brain stimulator. Also, the system receives personal information of the connected patients and cumulates the total records of electric stimulation therapy in a database. Doctors can easily access the information for better treatment planning with the help of graphical visualization tools and management software. The developed remote medical treatment system can be applied to the electric stimulation treatments for other brain diseases with a minor change.

• Research in Community and Public Health Nursing
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• v.33 no.3
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• pp.269-278
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• 2022

Purpose: This study analyzed the retention factors of Korean community health practitioners who sustained over 20 years based on a multi-dimensional framework. This study suggests global implications for nurses working in rural or remote areas, even during a worldwide pandemic. Methods: The participants were 16 Korean community health practitioners who worked in rural or remote locations for over 20 years. This study identified nurses' key retention factors contributing to long service in rural and remote areas. This is a qualitative study based on the narrative method and analysis was conducted using grounded theory. A semi-structured questionnaire was conducted based on the following: the life flow of the participants' first experience, episodes during the work experience, and reflections on the past 20 years. Results: First, personal 'financial needs' and 'callings' were motivation-related causal conditions. The adaptation of environment-work-community was the contextual condition leading to intervening conditions, building coping strategies by encountering a lifetime crisis. The consequences of 'transition' and 'maturation' naturally occurred with chronological changes. The unique factors were related to the 'external changes' in the Korean primary health system, which improved the participants' social status and welfare. Conclusion: Considering multi-dimensional retention factors was critical, including chronological (i.e., historical changes) and external factors (i.e., healthcare systems), to be supportive synchronously for rural nurses. Without this, the individuals working in the rural areas could be victimized by insecurity and self-commitment. Furthermore, considering the global pandemic, the retention of nurses is crucial to prevent the severity of isolation in rural and remote areas.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.10
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• pp.43-52
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• 2011

In this paper, we propose the architecture of the policy-based emergency bio data transmission for the smart healthcare service. the medical staff can quickly and accurately monitor the emergency bio data of the remote patient through the proposed architecture. The proposed system consists of three parts: IEEE 11073-based agents and managers performing the aggregation function and transmission function of the bio data; the emergency management server performing the converting function between IEEE 11073 and HL7 and auto-diagnosis function of the policy-based; HL7 medical system based on HL7. Finally, by implementing the proposed system, we shows that the aggregation of the bio data and management of the emergency bio data in the smart healthcare service are possible.