• Journal of Korea Society of Digital Industry and Information Management
• /
• v.17 no.1
• /
• pp.7-14
• /
• 2021

With the increased attention about healthcare and management of heart diseases, smart healthcare services and related devices have been actively developed recently. R wave is the largest representative signal among ECG signals. R wave detection is very important because it detects QRS pattern and classifies arrhythmia. Several R wave detection algorithms have been proposed with different features, but the remaining problem is their implementation in low-cost portable platforms for real-time applications. In this paper, we propose R wave detection based on optimal threshold and arrhythmia classification through QRS pattern considering complexity in smart healthcare environments. For this purpose, we detected R wave from noise-free ECG signal through the preprocessing method. Also, we classify premature ventricular contraction arrhythmia in realtime through QRS pattern. The performance of R wave detection and premature ventricular contraction arrhythmia classification is evaluated by using 9 record of MIT-BIH arrhythmia database that included over 30 premature ventricular contraction. The achieved scores indicate the average of 98.72% in R wave detection and the rate of 94.28% in PVC classification.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.3
• /
• pp.1014-1025
• /
• 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.

• Journal of Information Technology Services
• /
• v.22 no.1
• /
• pp.95-114
• /
• 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.

• Journal of Korean Society for Quality Management
• /
• v.46 no.4
• /
• pp.877-898
• /
• 2018

Purpose: This study empirically examines the effect of Communication Privacy Management(CPM) factors and Privacy Calculus factors to the intention to disclose Personal Health Information(PHI) in the context of healthcare ecosystem. Also, it investigates the moderating effects of CPM factors in the relationship between privacy calculus variables and the intention to disclose PHI. Methods: We conducted scenario-based repeated-measures quasiexperiment and used total 364 samples for analysis. Confirmatory factor analysis and repeated-measure ANOVA were employed using SPSS 24.0. Results: All CPM factors, such as type of information, requesting purpose, and requesting stakeholder, directly influence to the intention to disclose PHI, whereas only the medium trust out of the Privacy Calculus factors has direct influence on the intention to disclose PHI. With regard to the moderating effects, the requesting stakeholder is the most influential and the information type is the least influential construct. Conclusion: The findings suggest that healthcare system should be designed to provide more definite and personalized benefits to customers to enhance social and individual benefits by getting more participation from customers. Also, it is desirable that the requesting stakeholder of PHI would be non-profit organizations such as hospital, government or public agencies to secure more willingness of PHI from people. Furthermore, it is implied that extensive information gathering and utilization, instead of excluding sensitive information or critical patients' records, is recommended which is substantial to invigorate the healthcare industry.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.11A
• /
• pp.870-881
• /
• 2009

The rapid development of healthcare information management for 3D medical digital library, 3D PACS and 3D medical diagnosis has addressed security issues with medical IT technology. This paper presents multiple 3D medical image data for protection, authentication, indexing and diagnosis information hiding applied to healthcare information management. The proposed scheme based on POCS watermarking embeds the robust watermark for doctor's digital signature and information retrieval indexing key to the distribution of vertex curvedness and embeds the fragile watermark for diagnosis information and authentication reference message to the distance difference of vertex. The multiple embedding process designs three convex sets for robustness, fragileness and invisibility and projects 3D medical image data onto three convex sets alternatively and iteratively. Experimental results confirmed that the proposed scheme has the robustness and fragileness to various 3D geometric and mesh modifiers at once.

• The Journal of Industrial Distribution & Business
• /
• v.9 no.9
• /
• pp.35-44
• /
• 2018

Purpose - In endless competition, companies pursue cost reduction and work efficiency. So, entrepreneurs try to increase job intensity, which may lead to job stress and high turnovers because of job burnout. But, Information systems are acknowledged as a work support tool that secures work convenience and the productivity of employees. In this study, we aimed to confirm the effects of information systems in reduing the work overload of employees in a human resource intensive industry. Research design, data and methodology - This is based on the job demands-resources model, conducting an empirical analysis of surveys given to hospital employees working in a human resource intensive industry. Results - The research revealed that information systems reduced the work overload of employees in a human resource intensive industry. Conclusion - This study confirmed the effects of information systems as a job resource based on JD-R theory, and presentation of empirical results indicated that information systems alleviate employee job overload and increases job satisfaction in the medical services industry. In the medical services industry, using electronic health record system decreases in work overload, which results in employees gaining time for self-development and time management, reducing job stress, and leading to job satisfaction.

• Journal of Digital Convergence
• /
• v.15 no.3
• /
• pp.221-228
• /
• 2017

With the recent development of IoT technology, medical services using IoT technology are increasing in many medical institutions providing health care services. However, as the number of IoT sensors attached to the user body increases, the healthcare information transmitted to the server becomes complicated, thereby increasing the time required for analyzing the user's healthcare information in the server. In this paper, we propose a deep learning based health care information management method to collect and process healthcare information in a server for a large amount of healthcare information delivered through a user - attached IoT device. The proposed scheme constructs a subnet according to the attribute value by assigning an attribute value to the healthcare information transmitted to the server, and extracts the association information between the subnets as a seed and groups them into a hierarchical structure. The server extracts optimized information that can improve the observation speed and accuracy of user's treatment and prescription by using deep running of grouped healthcare information. As a result of the performance evaluation, the proposed method shows that the processing speed of the medical service operated in the healthcare service model is improved by 14.1% on average and the server overhead is 6.7% lower than the conventional technique. The accuracy of healthcare information extraction was 10.1% higher than the conventional method.

• The KIPS Transactions:PartD
• /
• v.15D no.3
• /
• pp.411-420
• /
• 2008

This paper implemented the u-Healthcare Context Information System (HCIS) supporting ubiquitous healthcare by using location, health and titrating environment information collected from sensors/devices equipped in home for healthcare home service. The HCIS is based on the Distributed Object Group Framework (DOGF), a management model which can customize distributed resources, and manages various context information, applications and devices as a group in healthcare home environment, as one more logical units. Also, this system provides continuous healthcare multimedia service considering a resident's location using Mobile Proxy, and the healthcare context information through Context Provider to a resident in home. For verifying execution of our system, we implemented the seamless multimedia service based on resident's location and the prescription/advice and schedule notification/alarm service as healthcare applications in home. And we showed the executing results of healthcare home service by using service device existed in the residential space on which the resident is located according to the healthcare scenario.

• Health Policy and Management
• /
• v.33 no.3
• /
• pp.273-294
• /
• 2023

Background: Most developed countries are working to improve their universal health coverage systems. This study investigates regional disparities in unmet healthcare needs and their causes in South Korea. Additionally, it compares the unmet healthcare needs rate in South Korea with that of 33 European countries. Methods: The analysis incorporates information from 13,359 adults aged 19 or older, using data from the Korea Health Panel. The dependent variables encompass the experience of unmet healthcare needs and the three causes of occurrence: "burden of medical expenses," "time constraints," and "lack of care." The primary variable of interest is the region of residence, while control variables encompass 14 socio-demographic, health, and functional characteristics. Multivariable binary logistic regression analysis, accounting for the sampling design, is conducted. Results: The rate of unmet healthcare needs in Korea is 11.7% (95% confidence interval [CI], 11.0%-13.3%), which is approximately 30 times higher than that of Austria (0.4%). The causes of unmet healthcare needs, ranked in descending order, are "lack of care," "time constraints," and "burden of medical expenses." Predictive probabilities for experiencing unmet healthcare needs and each cause differ significantly between regions. For instance, the probability of experiencing unmet healthcare needs due to "lack of care" is approximately 10 times higher in Gangwon-do (13.5%; 95% CI, 13.0%-14.1%) than in Busan (1.3%; 95% CI, 1.3%-1.4%). The probability due to "burden of medical expenses" is approximately 14 times higher in Seoul (4.1%; 95% CI, 3.6%-4.6%) compared to Jeollanam-do (0.3%; 95% CI, 0.2%-0.4%). Conclusion: Amid rapid sociodemographic transitions, South Korea must make significant efforts to alleviate unmet healthcare needs and the associated regional disparities. To effectively achieve this, it is recommended that South Korea involves the National Assembly in healthcare policy-making, while maintaining a centralized financing model and delegating healthcare planning and implementation to regional authorities for their local residents-similar to the approaches of the United Kingdom and France.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.10B
• /
• pp.988-993
• /
• 2009

In recent years, the development of ubiquitous computing technology as vital information anytime, anywhere to monitor and manage the demand for U-healthcare services is increasing. Accordingly, remote blood sugar management, remote blood pressure management, and research on U-healthcare service have been very active. But, the existing U-healthcare service monitoring devices and services has been implemented in different operating platforms and programing languages which are provided by diverse application service providers. For this reason, the users have difficulty in receiving diverse U-healthcare services. In this paper, SOA-based U-healthcare monitoring system has been designed and implemented. Through implementation, it is confirmed that the proposed SOA based U-healthcare monitoring system can increase the reuse of each service component to make it easier to reconstruct the structure of the new services.