• Knowledge Management Research
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• v.19 no.4
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• pp.149-170
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• 2018

Healthcare lifelog, a personal record relating to disease treatment and healthcare, plays an important role in healthcare paradigm shifts in which medical and information technology converge. Healthcare services based on various healthcare lifelogs are being launched domestically by both large corporations and small and medium enterprises, however, they are being built on an individual platform that is dependent on each company. Therefore, the terms of lifelog data are different as well as the measurement specifications are not uniform. This study proposes a reference model for minimum common data required for sharing and utilization of healthcare lifelog. Literature study and expert survey derived 3 domain, 17 essential items, and 51 sub-items. The model provides definition, measurement data format, measurement method, and precautions for each detailed measurement item, and provides necessary guidelines for data and service design and construction for healthcare service. This study has its significance as a basic research supporting the activation of ecosystem by ensuring interoperability of data between heterogeneous healthcare devices linked to digital healthcare platform.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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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.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.261-269
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• 2023

We propose to design a Holochain-based security and privacy protection system for resource-constrained IoT healthcare systems. Through analysis and performance evaluation, the proposed system confirmed that these characteristics operate effectively in the IoT healthcare environment. The system proposed in this paper consists of four main layers aimed at secure collection, transmission, storage, and processing of important medical data in IoT healthcare environments. The first PERCEPTION layer consists of various IoT devices, such as wearable devices, sensors, and other medical devices. These devices collect patient health data and pass it on to the network layer. The second network connectivity layer assigns an IP address to the collected data and ensures that the data is transmitted reliably over the network. Transmission takes place via standardized protocols, which ensures data reliability and availability. The third distributed cloud layer is a distributed data storage based on Holochain that stores important medical information collected from resource-limited IoT devices. This layer manages data integrity and access control, and allows users to share data securely. Finally, the fourth application layer provides useful information and services to end users, patients and healthcare professionals. The structuring and presentation of data and interaction between applications are managed at this layer. This structure aims to provide security, privacy, and resource efficiency suitable for IoT healthcare systems, in contrast to traditional centralized or blockchain-based systems. We design and propose a Holochain-based security and privacy protection system through a better IoT healthcare system.

• Journal of information and communication convergence engineering
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• v.9 no.2
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• pp.235-243
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• 2011

With the recent trends and the adaptation of further advancement in personal healthcare system leads to develop some application which can work independent and user can operate that application without much interference of physician or any specialist user. To meet these needs, this paper proposes and implements a progressive architecture for the personal healthcare information system. This new architecture will not only play the role of middleware but also provide a analysis tool to process that different sensor data which is collected from different sensors implemented on patient body and environment. After collecting that data, with the help of various developed applications this data can be convert into useful information which will be stored in application server for further use and research. These features can be enabled by simple and effortless interactions of normal users and act autonomously to support their activities. This proposed personal healthcare architecture will also provide analysis report to the doctors and patient or various users for further instructions. The analysis report consists of healthcare data analysis results and history of patients. We are considering healthcare data like ECG, which is an important aspect for basic healthcare need.

• Journal of the Korea Convergence Society
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• v.6 no.4
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• pp.243-248
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• 2015

U-Healthcare is a convergence service with medical care and IT which enables to examine, manage and maintain the patient's health any time and any place. For communication conducted in U-Healthcare service, the transmission methods are used that patient's medical checkup analysis results or emergency data are transmitted to hospital server using wireless communication method. At this moment when the attacker who executes the malicious access makes DRDoS(Distributed Reflection DoS) attack to U-Healthcare devices or BS(Base Station), various damages occur that contextual information of urgent patients are not transmitted to hospital server. In order to deal with this problem, this study suggests DRDoS attack scenario and countermeasures against DRDoS and converges with Big Data which could process large amount of packets. When the attacker attacks U-Healthcare devices or BS(Base Station), DB is interconnected and the attack is prevented if it is coincident. This study analyzes the attack method that could occur in U-Healthcare devices or BS which are remote medical service and suggests countermeasures against the security threat using Big Data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.116-132
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• 2022

Automated medical claims processing and billing is a popular application domain of information technology. Managing medical related data is a tedious job for healthcare professionals, which distracts them from their main job of healthcare. The technology used in data management has a sound impact on the quality of healthcare data. Most of Information Technology (IT) organizations use conventional software development technology for the implementation of healthcare systems. The objective of this experimental study is to devise a mechanism for use of rule-based expert systems in medical related edits and compare it with the conventional software development technology. A sample of 100 medical edits is selected as a dataset to be tested for implementation using both technologies. Besides empirical analysis, paired t-test is also used to validate the statistical significance of the difference between the two techniques. The conventional software development technology took 254.5 working hours, while rule-based technology took 81 hours to process these edits. Rule-based technology outperformed the conventional systems by increasing the confidence value to 95% and reliability measure to 0.462 (which is < 0.5) which is three times more efficient than conventional software development technology.

• Journal of The Korea Institute of Healthcare Architecture
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• v.16 no.4
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• pp.41-48
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• 2010

Since 1970s' many hospitals have been built due to the economic growth and change of social policy in Korea. But, we had no sufficient data and design guidelines of planning and designing to get good design solutions. From the first paper on the healthcare architecture issued in 1974, many researches have been performed. Researches could be one of the efforts to solve the problems and satisfy the needs of those periods. Researches could reflect the characteristics of healthcare architecture of those periods. So in this paper 267 papers issued between 1974-2009 were analyzed to get the characteristics patterns of research periodically. This paper aims to provide a basic data for studying of history of healthcare architecture in Korea.

• Journal of the Korean Applied Science and Technology
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• v.37 no.1
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• pp.76-82
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• 2020

Big data analysis in healthcare research seems to be a necessary strategy for the convergence of sports science and technology in the era of the Fourth Industrial Revolution. The purpose of this study is to provide the basic review to secure the diversity of big data and healthcare convergence by discussing the concept, analysis method, and application examples of big data and by exploring the application. Text mining, data mining, opinion mining, process mining, cluster analysis, and social network analysis is currently used. Identifying high-risk factor for a certain condition, determining specific health determinants for diseases, monitoring bio signals, predicting diseases, providing training and treatments, and analyzing healthcare measurements would be possible via big data analysis. As a further work, the big data characteristics provide very appropriate basis to use promising software platforms for development of applications that can handle big data in healthcare and even more in sports science.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.256-259
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• 2013

Data and network security for e-Healthcare Systems are a primary concern due to the easiest deployment area accessibility of the sensor devices. Furthermore, they are often interacting closely in cooperation with the physical environment and the surrounding people, where such exposure increases security vulnerabilities in cases of improperly managed security of the information sharing among different healthcare organizations. Hence, healthcare-specific security standards such as authentication, data integrity, system security and internet security are used to ensure security and privacy of patients' information. This paper discusses security threats on e-Healthcare Systems where an attacker can access both data and network using masquerade attack. Moreover, an efficient and cost effective approach for countermeasures is discussed for the delivery of secure services.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.2
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• pp.134-143
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• 2022

'Data' is the key component that leads Digital Healthcare. Most of the Healthcare Data is personal information of data subject and includes Sensitive Information. It is very important for companies to use data lawfully and safely during the lifecycle of data collection, use, provision, and destruction. However, small and medium-sized enterprises(SMEs), ventures, and startups, which account for 78% of the Healthcare Services Industry, have had difficulties in performing tasks related to personal information protection. The personal Information Protection Act's requirements depending on the purpose of using Personal Information are different. Also, the requirements for each personal information lifecycle are varied. Therefore, this study suggests six purposes for companies to use healthcare data. It examines the considerations during the lifecycle in which personal information is collected to be destroyed.