• The Journal of Asian Finance, Economics and Business
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• v.7 no.8
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• pp.705-714
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• 2020

This study aims to investigate the main factors that affected the government health expenditures in Gulf Cooperation Council (GCC) countries (Kingdom of Saudi Arabia (KSA), United Arab Emirates (UAE), Oman, Qatar, Bahrain and Kuwait), during the period from 2005 to 2019. The study employs a panel data technique in order to monitor the pooled determinant variables of healthcare expenditures in these countries. The study's results indicate, by using FMOLS approach for panel data, that the average healthcare expenditures per capita in GCC countries have a positive and a significant relationship with the government revenues, the size of the population, and the governments' public debt. The positive and the significant relationships of governments' public debt may be explained even if the governments of the GCC countries suffer from a budget deficit; the GCC countries continue to increase the healthcare expenditure. The study suggests that the policymakers of the GCC countries must take into consideration those variables when they develop their healthcare policies. Also, the GCC countries urgently need to have high levels of foreign exchange reserves to maintain the expected level of spending on the healthcare sector, because their public revenues depend mainly on the oil revenues, which are fluctuating continuously.

• Research in Community and Public Health Nursing
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• v.27 no.4
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• pp.319-326
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• 2016

Purpose: The aim of this study is to identify factors affecting elders' intention to participate in healthcare programs. Methods: This secondary data analysis used data of 390 elderly people who lived alone and were enrolled in the Visiting Health Care Center of H-city. In 2014, questionnaires were used to collect data about demographics, social activity, depression, frailty, and intention to participate in healthcare programs. The data were analyzed by descriptive statistics and multivariate logistic regressions. Results: Among the participants, 51.8% intended to participate in the offered healthcare programs. The strongest factor affecting the intention was gender. Women were 4.85 times more likely to participate in the programs than men. The women's intention was associated positively with increased levels of frailty. The men tended to participate in the program as they got older and as the level of frailty and the number of chronic diseases increased. Conclusion: Gender-specific public healthcare programs for vulnerable elders living alone should be developed to maximize their participation in the programs and to promote good health. The healthcare programs must be tailored to the levels of the patients' physical functions.

• International journal of advanced smart convergence
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• v.9 no.2
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• pp.164-172
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• 2020

The interest and importance of the convergence services for healthcare expand more and more as the average life expectancy increases. Convergence of ICT and healthcare technology unfold efficient and quick health services. Recently, healthcare services provide to clients with apps over web. On-demand wireless data broadcast supports any number of clients to access their desired data items dynamically by responding the needs for data items from the clients. In this paper, we propose an on-demand system to broadcast FHIR bundles for efficient healthcare services. We use time-parameterized replacing policy for renewing the bundle items on the wireless broadcast channel. The policy lets the on-demand broadcasting dynamic by controlling the time duration for the bundles to reside over the wireless channel. With simulation studies using an implemented testbed, we evaluate the performances of the proposed system in access time and tuning time. For evaluation, we compare the time-parameterized replacing policy of the proposed system with regular-number replacing policy. The proposed time-parameterized replacing policy shows shorter access time than the regular-number replacing policy because the policy responds more actively and dynamically to the change of the needs of the clients for FHIR bundles.

• Journal of Technologic Dentistry
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• v.46 no.2
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• pp.42-48
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• 2024

Purpose: The purpose of this study is to investigate the applications and prospects of big data in digital dental healthcare. Methods: The study included 30 participants in the dental field (dentists, technicians, professors, and graduate students). From June 25 to 30, 2023, the contents of the study were thoroughly explained, consent was obtained from the research subjects, and a questionnaire was administered via an internet service. The questionnaires of 28 participants who responded completely were used for analysis. The collected data were statistically processed using IBM SPSS Statistics ver. 22.0 (IBM). Results: The use of big data in digital dental healthcare, digital dental health system, mobile dental health, dental health analysis, and telehealthcare were all heavily surveyed, with an average score of 3.97 or higher on a 5-point Likert scale. The areas where big data can be utilized in digital dental healthcare are as follows. The utilization rate for three-dimensional digital product development via linkage with big data systems and industrial field manufacturing technology was found to be 4.11±0.67, and the analysis of trends by age in the occurrence of various oral diseases was found to be 4.00±0.98. Conclusion: In the future, research into the viability of big data's success in the medical data field, which is directly related to human life, is needed. Additionally, social policies and regulations regarding big data-related information and standards in dental healthcare are necessary.

• Fashion & Textile Research Journal
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• v.22 no.5
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• pp.607-616
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• 2020

Health care wearables are devices that are attached to or combined with the human body to improve the health care capabilities of the human body that can be safely and adjustable according to preference. This study provided direction for future research on healthcare wearables in the field of clothing science, considering trends observed in this field from 2010 to 2019. Over the last 10 years, 812 studies have been conducted on healthcare wearables in Korea. Research has increased significantly since 2015, with a large number of articles published in this field. The research for this study was broken down into the following categories: technology development, marketing analysis, and technology analysis. The results according to the research method demonstrated that development and production methods were used most frequently, followed by trend analysis, experiment and evaluation, and survey. An analysis of keywords in the articles studied revealed that device, healthcare, big data (biometric data and database), and healthcare convergence technologies were trending. Similarly, detailed research on healthcare wearable devices and related technologies was actively being conducted. However, focusing on fiber, textiles, design, and clothing articles, in relation to the field of clothing in healthcare wearables, only 81 articles were found on this topic (10.0%), which was low compared to other studies. Therefore, it was determined that more research on healthcare wearables is necessary in the field of clothing.

• Journal of Korea Multimedia Society
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• v.19 no.5
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• pp.808-817
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• 2016

Recently, the wearable computing technology with bio-sensors has been rapidly developed and utilized in various areas such as personal health, care-giving for senior citizens who live alone, and sports activities. In particular, the wearable computing equipment to measure vital signs by means of digital yarns and bio sensors is noticeable. The wearable computing devices help users monitor and manage their health in their daily lives through the customized healthcare service. In this paper, we suggest a system for monitoring and analyzing vital signs utilizing smart healthcare clothing with bio-sensors. Vital signs that can be continuously acquired from the clothing is well-known as unstructured data. The amount of data is huge, and they are perceived as the big data. Vital sings are stored by Hadoop Distributed File System(HDFS), and one can build data warehouse for analyzing them in HDFS. We provide health monitoring system based on vital sings that are acquired by biosensors in smart healthcare clothing. We implemented a big data platform which provides health monitoring service to visualize and monitor clinical information and physical activities performed by the users.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.2
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• pp.479-484
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• 2010

Researches of Healthcare have been fulfilled lively with an advanced age and change of lifestyles. Especially, medical field has focused on researches of Healthcare due to that reasons. The Healthcare service requires the foundation technologies, such as sensor aggregating, data saving and data transmitting/analysis. In this research, we proposed the unrestricted equipment which can save a lot of aggregated patient's medical data to guarantee the patient's movement in Healthcare service. Moreover, we research the method which can transmit the aggregated data as soon as possible. Also, we implemented the system which can transmit the patient's medical data automatically for convenient use.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.6
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• pp.127-134
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• 2011

Recently, the wireless data communication infrastructure appearing before the footlights crosses the limit in the wire and develop into the fast speed. Particularly, the issue about the u-Healthcare service using this increases. And the investigation of the quality guarantee of the wireless data network is important for the smooth service providing. However, the quality control research about the wireless network is insufficient because the existing research performs the quality control between the termination about the wired network continually. This paper presented the mobile service quality measurement reference considering the radio environment,that is the method for satisfying the quality guarantee of the wireless data network user offered the u-Healthcare service as the research about this and user needs. For this purpose, wireless data quality measurement indicator and standard was selected. The quality measure evaluation plan was presented according to the service. And each service presented the quality index especially.

• Journal of the Korea Convergence Society
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• v.13 no.4
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• pp.25-37
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• 2022

The government and private companies are endeavoring to help the digital healthcare industry grow. This includes easing regulations on the big data industry such as the amendment of the Data 3 Act. Despite these efforts, however, there have been constant demands for the amendment of laws related to the medical field and for securing medical data transmissions. In this paper, the Data 3 Act of Korea and the legal system related to healthcare are examined. Then the legal, institutional, and technical aspects of the strategies are compared to understand the issues and implications. Based on this, a legal and institutional strategy suitable for the digital healthcare industry in Korea is suggested. Additionally, a direction to improve social perception along with technical measures such as safe de-identification processing and data transmission are also proposed. This study hopes to contribute to the spread of various convergent industries along with the digital healthcare industry.

• Journal of information and communication convergence engineering
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• v.19 no.3
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• pp.166-174
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• 2021

A large volume of patient data is generated from various devices used in healthcare applications. With increase in the volume of data generated in the healthcare industry, more wellness monitoring is required. A cloud-enabled analysis of healthcare data that predicts patient risk factors is required. Machine learning techniques have been developed to address these medical care problems. A novel technique called the radix-trie-based Tanimoto kernel regressive infomax boost classification (RT-TKRIBC) technique is introduced to analyze the heterogeneous health data in the cloud to predict the health risks and send alerts. The infomax boost ensemble technique improves the prediction accuracy by finding the maximum mutual information, thereby minimizing the mean square error. The performance evaluation of the proposed RT-TKRIBC technique is realized through extensive simulations in the cloud environment, which provides better prediction accuracy and less prediction time than those provided by the state-of-the-art methods.