• Journal of Communications and Networks
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• v.13 no.2
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• pp.132-141
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• 2011

IEEE 802.15.4 networks are a feasible platform candidate for connecting all health-care-related equipment dispersed across a hospital room to collect critical time-sensitive data about patient health state, such as the heart rate and blood pressure. To meet the quality of service requirements of health-care systems, this paper proposes a multi-priority queue system that differentiates between various types of frames. The effect of the proposed system on the average delay and throughput is explored herein. By employing different contention window parameters, as in IEEE 802.11e, this multi-queue system prioritizes frames on the basis of priority classes. Performance under both saturated and unsaturated traffic conditions was evaluated using a novel analytical model that comprehensively integrates two legacy models for 802.15.4 and 802.11e. To improve the accuracy, our model also accommodates the transmission retries and deferment algorithms that significantly affect the performance of IEEE 802.15.4. The multi-queue scheme is predicted to separate the average delay and throughput of two different classes by up to 48.4% and 46%, respectively, without wasting bandwidth. These outcomes imply that the multi-queue system should be employed in health-care systems for prompt allocation of synchronous channels and faster delivery of urgent information. The simulation results validate these model's predictions with a maximum deviation of 7.6%.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.2
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• pp.51-56
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• 2011

Recently, it is emerging in computing industry related ubiquitous. Also U-Healthcare system develops rapidly based on this trends. It is required system of health-status information to check user's health information on real-time and wireless network environment. Consequently, in this paper propose a health-Information system based on wireless and real-time environment. It can check a tremor pulse with method of photo-plethysmography. It convert pulse state information into 2-dimension bar code in order to confirm health information using mobile and also this system provide service of pulse visual record and explanation from specialist with MMS.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.12-14
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• 2021

For the past couple of years, the medical data has been stored in centralized systems which is not the ideal storage technique since all data can be altered, stolen, or even used for evil purposes and, furthermore, the data cannot be safely shared with other doctors and hospitals in case of patient's transfer, change of state or country, in addition, patient's health status cannot be tracked and the patient's medical history is unknown. Therefore, powerful decentralized technologies and expertise can help provide better health information and help doctors and patients to better understand the situations before and after treatment, and do more research based on immutable and trusted data. One of the proposed solutions is storing and securing data on the blockchain which is less scalable, slow and expensive. Introducing a scalable, robust medical data storage and sharing system based on AI/ML, IoT, IPFS, and blockchain.

• Communications of the Korean Institute of Information Scientists and Engineers
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• v.35 no.7
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• pp.9-25
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• 2017

In this paper, we surveyed state-of-the-art health and wellness platforms. The motivation of this paper is to review the state-of-the-art health and wellness platforms and their maturity with respect to adoption of latest enabling technologies. The is review is classified into four categories: healthcare systems, AI-assisted healthcare, wellness platforms, and open source health and wellness initiatives. From this comprehensive review, it can be stated that the contemporary healthcare systems are well-adopting wellness due to the concentration shift towards prevention. Thus, the gap between health and wellness is slowly yet carefully entering gray area. Where both the domains can freely invoke each other's services, and supporting enabling technologies. Furthermore, the biomedical researchers and physicians are no longer carrying the myopic views of trusting their knowledge for diagnosis. AI-assisted technologies based on machine learning and big data are influencing today's prognosis with trust and confidence.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.5
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• pp.1108-1130
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• 2013

Wireless Body Area Networks (WBANs) are becoming increasingly important to solve the issue of health care. IEEE 802.15.6 is a wireless communication standard for WBANs, aiming to provide a real-time and continuous monitoring. In this paper, we present our development of a modified Markov Chain model and a backoff model, in which most features such as user priorities, contention windows, modulation and coding schemes (MCSs), and frozen states are taken into account. Then we calculate the normalized throughput and average access delay of IEEE 802.15.6 networks under saturation and ideal channel conditions. We make an evaluation of network performances by comparing with IEEE 802.15.4 and the results validate that IEEE 802.15.6 networks can provide high quality of service (QoS) for nodes with high priorities.

• Journal of Preventive Medicine and Public Health
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• v.54 no.1
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• pp.22-30
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• 2021

Objectives: The coronavirus disease 2019 (COVID-19) pandemic is a public health emergency posing unprecedented challenges for health authorities. Social media may serve as an effective platform to disseminate health-related information. This study aimed to assess the extent of social media use, its impact on preventive behavior, and negative health effects such as cyberchondria and information overload. Methods: A cross-sectional observational study was conducted between June 10, 2020 and August 9, 2020 among people visiting the outpatient department of the authors' institution, and participants were also recruited during field visits for an awareness drive. Questions were developed on preventive behavior, and the Short Cyberchondria Scale and instruments dealing with information overload and perceived vulnerability were used. Results: The study recruited 767 participants with a mean age of about 45 years. Most of the participants (>90%) engaged in preventive behaviors, which were influenced by the extent of information received through social media platforms (β=3.297; p<0.001) and awareness of infection when a family member tested positive (β=29.082; p<0.001) or a neighbor tested positive (β=27.964; p<0.001). The majority (63.0%) of individuals often searched for COVID-19 related news on social media platforms. The mean±standard deviation scores for cyberchondria and information overload were 9.09±4.05 and 8.69±2.56, respectively. Significant and moderately strong correlations were found between cyberchondria, information overload, and perceived vulnerability to COVID-19. Conclusions: This study provides evidence that the use of social media as an information- seeking platform altered preventive behavior. However, excessive and misleading information resulted in cyberchondria and information overload.

• International journal of advanced smart convergence
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• v.5 no.3
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• pp.27-31
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• 2016

High-tech industries in a state well enough to troubleshoot hacking information introduction a big barrier to delay the growth of the market related to IoT(Internet of Things) as is likely to be on the rise. This early on, security issues introduced in the solution, a comprehensive solution, including the institutional laws/precautions needed. Recent examples of frequent security threats while IoT is the biggest issue of introducing state-of-the-art industry information due to the vulnerable security hacking. This high-tech industries in order to bridge the information responsible for the target attribute, target range, and the protection of security and how to protect the subject, IoT environment (domestic industrial environment) considering the approach is needed. IoTs with health care and a wide variety of services, such as wearable devices emerge. This ensures that RFID/USN-based P2P/P2M/M2M connection is the implementation of the community. In this study, the issue on the high-tech industrial information and the vulnerable security issues of IoT are described.

• The Transactions of the Korean Institute of Power Electronics
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• v.25 no.5
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• pp.376-384
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• 2020

An energy storage system is composed of lithium-ion batteries in modern applications. Batteries are regarded as storage devices for renewable and residual energy. The failure of batteries can cause the performance reduction and explosion of battery systems. High maintenance cost is essential when dealing with the problem of battery safety. Therefore an accurate health diagnosis is required to ensure the high reliability of battery systems. A battery pack is a combination of single cells in series and parallel connections. A battery pack has to consider various factors to assess battery health. Battery health involves conventional factors and additional factors, such as cell-to-cell imbalance. For large applications, state-of-health (SOH) can be inaccurate because of the lack of factors that indicate the state of the battery pack. In this study, six characterization factors are proposed for improving the SOH estimation of battery packs. The six proposed characterization factors can be regarded as health indicators (HIs). The six HIs are applied to the principal component analysis (PCA) algorithm. To reflect information regarding capacity, voltage, and temperature, the PCA algorithm extracts new degradation factors by using the six HIs. The new degradation factors are applied to a multiple regression model. Results show the advancement and improvement of SOH estimation.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.8
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• pp.4057-4062
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• 2012

Objective: To study the level of awareness and knowledge about cancers and associated risk factors among households in selected states of India. Methods: In the study 3070 households were interviewed from six states viz, West Bengal, Kerala, Madhya Pradesh, Rajasthan and Mizoram. Results: Knowledge of cancers other than those related to tobacco was very low (prostate 8%, colon 11% ) among the communities, with a poor awareness of warning signs and symptoms. The knowledge varied from state to state. It is found that the major source of information related to cancers was television (38%) followed by friends and relatives (36%). Only about 15 % of respondents had knowledge about cancer awareness camps organized in their districts but they did not have knowledge about the organizers of the camp. Findings suggested a strong need for strengthening of DCCP. Conclusion: It is important to create awareness among community through educational programs on cancer prevention, preventable cancer risk factors, benefits of early diagnosis, and availability of screening facilities. Integration of District Cancer Control activities with NRHM could be the most cost-effective strategy to prevent cancers and rural population.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.3
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• pp.387-396
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• 2022

Recently, e-Mobility, which is a personal mobility device such as an electric bicycle or an electric scooter, is rapidly emerging. However, since E-Mobility has various voltage systems due to the characteristics of its products, it is essential for companies that operate them to use multiple dedicated chargers. A universal charger capable of charging batteries of various voltage systems with one charger is required to reduce the cost of purchasing and managing multiple dedicated chargers. For this, information on the EOC(End of Charge) is essential. In order to know the EOC, it is necessary to detect the internal impedance of the battery. However, the internal impedance of the battery changes according to various conditions such as SOH(State Of Health), SOC(State Of Charge), and ambient temperature. By observing the change in these parameters, the state of the battery can be diagnosed and the EOC can be predicted. In this paper, we propose an algorithm to analyze the battery's internal impedance and to predict the EOC, in order to acquire information on the EOC of the battery, which is an essential requirement of a universal charger.