• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.650-651
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• 2023

반려동물의 건강 상태를 파악하기 위해서 수면 패턴을 모니터링하는 것은 중요하다. 본 논문에서는 6축 센서 데이터를 활용하여 수면 패턴을 모니터링하고, 이를 바탕으로 설계된 헬스케어 시스템을 제안한다. 이 시스템은 크게 데이터 수집, 행동 분류, 수면 패턴 모니터링으로 구성된다. 6축 센서 데이터와 ResNet-LSTM을 통해 반려동물의 행동(두 발로 서다, 네 발로 서다, 걷다, 킁킁대다, 뒷다리만 앉다, 엎드리다, 모든 발이 앉다, 놀다, 빠르게 걷다)을 분류하고, 분류된 행동을 활용하여 수면패턴을 분석한다. 이를 통해 수면 이상을 확인하고 반려동물의 건강 상태를 간접적으로 평가하여 적절한 처치 및 관리하고자 한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.147-149
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• 2020

코로나바이러스의 세계 확산, 발병 이후 사람들의 실내활동 증가와 건강, 면역에 대한 관심은 많이 증가했다. 이에 맞춰 더욱 정교하고 바른 정보에 의한 스마트헬스케어 역시 관심이 증대되고 있다. 여기서 이야기하는 스마트헬스케어의 범위는 영상 장치를 비롯해 다양한 센서를 활용해 신체활동을 모니터링하고 분석하며 기존의 방식보다 더 객관적인 정보를 제공해 주는 것을 말한다. 위 기술과 대중의 관심을 바탕으로 하여 본 연구에서는 다중 모드 센서를 신체에 부착하여 신체활동을 모니터링 하는 시스템 개발을 목적으로 한다. 하드웨어 설계 부분에서 설계가 완성된 Arduino nano 33 Sense를 이용하여 스마트 헬스 실험 시간을 대폭 줄였다. 또한 운동과 같은 시계열 데이터를 분석하기 좋은 LSTM 기법을 채택하였으며, 개발된 모델을 추후 활용할 방안에 대해 논하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.381-383
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• 2015

We are entering a phase of an aged society. The societal expense on health care for the so called "silver generation", which refer to as those over the age of 65 is increasing. Although many companies provide various services based on information technology for the health of the silver generation, many have pointed out the limits of them, preventing the activation of services. This study tries to develop a new smart health band business model, which is the most common form of healthcare service that reflects the user's desire. To do this, the study will cover the smart health band and the technical functions related to it, as well as the elements of the business model and its content.

• 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.

• Journal of the Korea Convergence Society
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• v.10 no.6
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• pp.235-242
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• 2019

Recently, the use of artificial intelligence technology including deep learning has become active in various fields. In particular, several algorithms showing superior performance in object recognition and detection based on deep learning technology have been presented. In this paper, we propose the proper direction for the implementation of mobile healthcare application that user's convenience is effectively reflected. By effectively analyzing the current state of use satisfaction research for the existing fitness applications and the current status of mobile healthcare applications, we attempt to secure survival and superiority in the fitness application market, and, at the same time, to maintain and expand the existing user base.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.511-513
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• 2022

Digital Health Care is the convergence of ICT and (non)medical technology, emphasizing the importance of prevent and monitoring health management in terms of new challenging medical paradigm: predictive, preventive, personalized and participatory. Beyond the limited medical industry of long-term care insurance, it is emerging that AI, IoT, Big Data related new services with new technologies in the 4^th revolution era. It is also noted that business field based on test bed is emergent; Caring Robot, wearable devices need to be launched in the market. Diverse service is possible with Big Data and AI etc.

• Korea Journal of Hospital Management
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• v.26 no.4
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• pp.12-28
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• 2021

Purposes: The convenience of smartphones have lead to people's overdependence on devices, which may cause obstacles in daily life. It is useful to manage smartphone overdependence by using mobile health applications. We aimed to investigate the acceptance of mobile health applications designed to help in the management of smartphone overdependence. Methodology/Approach: We developed the extended model based on the Unified Theory of Acceptance and Use of Technology 2. The modified model had six hypotheses with six variables: result demonstrability, performance expectancy, effort expectancy, social influence, perceived risk, and behavioral intention to use. We randomly included 425 smartphone users in an online survey in 2020. A structural equation model was used to estimate the significance of the path coefficients. Findings: Performance expectancy and social influence had a very strong direct positive association with behavioral intention to use. Result demonstrability had a direct positive association with performance expectancy. Perceived risk had a strong direct negative association with performance expectancy. Performance expectancy and social influence were the main factors directly influencing the acceptance of mobile health applications for the management of smartphone overdependence. Practical Implications: We demonstrated smartphone users' acceptance of mobile health applications for smartphone overdependence management. Based on these results, we could develop mobile health applications more effectively.

• The Journal of the Convergence on Culture Technology
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• v.8 no.2
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• pp.1-6
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• 2022

Lifelog is a digital record of an individual collected from various digital sensors, and includes activity amount, sleep information, weight change, body mass, muscle mass, fat mass, etc. Recently, as wearable devices have become common, a lot of high-quality lifelog data is being produced. Lifelog data shows the state of an individual's body, and can be used not only for individual health care, but also for causes and treatment of diseases. However, at present, AI/ML-based correlation analysis and personalization are not reflected. It is only at the level of presenting simple records or fragmentary statistics. Therefore, in this paper, the correlation/relationship between lifelog data and disease, and AI/ML technology inside lifelog data are examined, and furthermore, a lifelog data analysis process based on AI/ML is proposed. The analysis process is demonstrated with the data collected in the actual Galaxy Watch. Finally, we propose a future convergence service roadmap including lifelog data, diet, health information, and disease information.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.6 no.2
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• pp.31-41
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• 2012

The combination of developed medical devices and the convergence of IT fusion technologies, health variables became to can be measured without discomfort in everyday life regardless of wherever and whenever. because various types of u-Health medical devices have been developed. Also, by considering the users, biological signals can be measured without difference with wearing general clothing, that conductive fabric is being used as smart clothing. However, considering that there is a growing prevalence of the devices and a great interest in the development of u-Health devices, it is urgent to establish performance evaluation. Accordingly, writing guidelines by force to raise checking before marketed or collecting checks after at the market for standard test methods for evaluating the performance. In this paper, it was studied that the possibility of using conductive fabric as electrodes for Wearable u-Health Devices through the material test of the ffabric.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.12
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• pp.891-898
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• 2009

This paper suggests producer/consumer-based Data Binder enabling applications and biomedical devices developed by mutually different vendors to transfer data dynamically. Data Binder is implemented as a bundle of OSGi platform providing component-based programming model and service-oriented operation architecture. Data Binder complements the disadvantage of OSGi WireAdmin service enabling static data delivery between a producer and a consumer of data. Data Binder normalizes an application requirement as an application descriptor and a device capability as a device descriptor so that it enables dynamic data delivery by making data producer/consumer pair in runtime. Therefore, Data Binder can be used as a connection management of a data link between a data producer and a data consumer in sensor-based application development. The object of this paper is to provide the facility of the healthcare service development by separating a data producer such as a biomedical device from a data consumer such as a healthcare application.