• Design Convergence Study
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• v.16 no.6
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• pp.123-135
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• 2017

In recent mobile health care service, health management using number of steps is becoming popular. In addition, a variety of activity trackers have made it possible to measure the number of steps more accurately and easily. Nevertheless, the activity tracker is not popularized, and it is a trend to use the pedometer sensor of the smartphone as an alternative. In this study, we tried to find out how much the number of steps collected by the smartphone versus the actual number of steps in actual situations, and what factors make the difference. We conducted an experiment to collect number of steps data of 21 people using the smartphone and wearable device simultaneously for 7 days. As a result, we found that the average number of steps of the smartphone is 62% compared to the actual number of steps, and that there is a large variation among users. We derived a regression model in which the accuracy of smartphone increases with the degree of awareness of smartphone. We expect that this can be used as a factor to correct the difference from the actual number of steps in the smartphone alone healthcare service.

• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.113-121
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• 2020

With the rapid development of information and communication technology (ICT), various sensors are being embedded in wearable devices. Consequently, these devices can continuously collect data including health data from individuals. The collected health data can be used not only for healthcare services but also for analyzing an individual's lifestyle by combining with other external data. This helps in making an individual's life more convenient and healthier. However, collecting health data may lead to privacy issues since the data is personal, and can reveal sensitive insights about the individual. Thus, in this paper, we present a method to collect an individual's health data from a smart band in a privacy-preserving manner. We leverage the local differential privacy to achieve our goal. Additionally, we propose a way to find feature points from health data. This allows for an effective trade-off between the degree of privacy and accuracy. We carry out experiments to demonstrate the effectiveness of our proposed approach and the results show that, with the proposed method, the error rate can be reduced upto 77%.

• Journal of Advanced Navigation Technology
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• v.18 no.6
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• pp.619-624
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• 2014

Nowadays there are various smart devices and development with the development of smart phones and that can be attached to the human body wearable computing device has been in the spotlight. In this paper, we proceeded developing wearable devices in watch type which can detect user's movement and developing a system which connects the wearable devices to smart TVs, or smart phones so that users can save and manage their physical information in those devices. Health care wearable devices already existing save information by connecting their systems to smart phones. And, smart TV health applications usually include motion detecting systems using cameras. However, there is a limit when connecting smart phone systems to different devices from various companies. Also, in case of smart TV, because some devices may not have cameras, there can be a limit for users who wants to connect their devices to smart TVs. Wearable device and user information collected by using the smart phone and when it is possible to exercise and manage anywhere. This information can also be confirmed by the smart TV applications. By using this system will be able to take advantage of the study of the behavior of the future work of the user more accurately be measured in recognition technology and other devices.

• Information and Communications Magazine
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• v.32 no.11
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• pp.12-20
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• 2015

최근 의학 기술이 눈부시게 발전함에 따라 사람들은 수명이 연장되고 삶의 질 향상에 많은 관심을 가지게 되었다. 더욱이 혁신적인 디지털 기술 발전과 함께 다양한 웨어러블 기기와 수많은 헬스케어 어플리케이션이 출시되고 있으며, 이들은 어떻게 하면 개인의 성향이나 체질에 잘 맞는 맞춤형 (개인화) 서비스를 제공할 수 있을 것인가에 관심을 두고 진화하고 있다. 따라서 IoT 환경의 일상생활에서 입력되는 센서 데이터의 수집, 처리, 가공 기술, 일상 행위 및 라이프 스타일 인지, 지식 획득 및 관리 기술, 개인화 추천서비스 제공, 프라이버시 및 보안을 통합적으로 지원할 수 있는 프레임워크 개발에 대한 요구가 증대되고 있다. 이에 본 고에서는 저자가 개발중인 개인 맞춤 건강 및 웰니스 서비스를 제공하는 마이닝 마인즈 프레임워크를 소개한다. 마이닝 마인즈는 현존하는 최신 기술의 집약체로 개인화, 큐레이션, 빅 데이터 처리, 클라우드 컴퓨팅의 활용, 다양한 센서 정보의 수집과 분석, 진화형 지식의 생성과 관리, UI/UX를 통한 습관화 유도 등 다양한 요소를 포함한다. 그리고 건강 및 웰니스 프레임워크 요구사항 분석을 통해 마이닝 마인즈가 이러한 요구를 충족시킬 수 있으며, 개발된 프로토타입을 통해 개인화 서비스의 발전 가능성을 입증하고 향후 나아가야 할 방향을 제시한다.

• Journal of the Korea Convergence Society
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• v.11 no.4
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• pp.151-156
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• 2020

The purpose of this study is to design a process for developing wearable sports helmet devices by utilizing IoT server technology, focusing on sports where helmet wear is essential at sports sites. This enables customized training of athletes by continuously accumulating personal biometric information during training, checking players' condition based on data, and informing them of injury prevention and dangerous situations. In addition, the wearable device that can be useful when the training place is likely to damage the physical health due to heat waves or extremes can provide a foundation for improving the performance. Since such technology can be applied not only to the sports field but also to the society such as the industrial field or the underprivileged, it can be expected to be expandable.

• The Journal of the Korea Contents Association
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• v.19 no.4
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• pp.41-53
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• 2019

As the paradigm of healthcare shifts from the center of treatment to the center of prevention, products and services related to disease prevention are emerging at domestic and abroad. The government considers the smart healthcare industry as a solution to healthcare problems such as an increase in the number of chronic illnesses and an increase in the burden of medical expenses. The purpose of this study is to explore the factors affecting the use of smart healthcare products and services focusing on Health Literacy and health related personal characteristics and to provide policy implications. The subjects of the questionnaire are 1,027 adults over 20 in the nation, and conducted an online survey. In addition, the factors were analyzed by decision tree method. As a result, most of the respondents(76.9%) did not have experience using Smart Healthcare products and services. However, in the Health Literacy question, there was a difference in use experience depending on the degree of difficulty in using the mass media information. Other factors were the degree of intention to use new technology, the understanding of counseling about family members and friends, and health checkups. In order to enable self-healthcare through smart healthcare products and services, the ability of consumers to explore and utilize health information from the mass media should be improved. In addition, government and enterprise efforts are needed to achieve this.

• Journal of Digital Convergence
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• v.14 no.11
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• pp.249-255
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• 2016

Since the elderly voices include a lot of noise caused by physiological changes in respiration, phonation, and resonance, the performance of the convergence health-care equipments such as speech recognition, synthesis, analysis program done by elderly voice is deteriorated. Therefore it is necessary to develop researches to operate health-care instruments with elderly voices. In this study, a voice activity detection using a symmetric higher-order differential energy function (SHODEO) was developed and was compared with auto-correlation function(ACF) and the average magnitude difference function(AMDF). It was confirmed to have a better performance than other methods in the voice interval detection. The voice activity detection will be applied to a voice interface for the elderly to improve the accessibility of the smart devices.

• Review of KIISC
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• v.32 no.4
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• pp.135-146
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• 2022

포스트 코로나시대에는 다가올 디지털 인프라 사회에서의 스마트시티에서 안전하고 편리한 사이버 경제활동을 구현하기 위해서는 특히 비대면 디지털 환경에서 바이오인식기술의 중요성은 증대될 것으로 전망된다. 이에 따라 바이오인식 관련 국제표준화기구인 ISO/IEC JTC1 SC37(Biometrics)/SC27(Security)과 ITU-T SG17 Q10(ID Management & Telebiometrics) 등 바이오인식기술 국제 표준화 동향과 아시아바이오인식협의회(Asian Biometric Consoritum) 사실 표준화 현황을 면밀히 분석하여, 모바일기기·웨어러블 디바이스 응용분야, 디지털 헬스케어분야, 자율주행 응용분야, 국제공통·국가공용 ID카드분야, 동물보호 공학분야 등 미래의 스마트시티에서 활용될 바이오인식기술에 대한 전망과 함께 관련되는 국제표준에 대한 주요내용과 적용분야를 제안하고자 한다. 이를 통하여 향후 디지털 사회로의 대전환 시대가 도래함에 따른 생체인식기술을 적용한 스마트시티의 발전전망을 고찰하고자 한다.

• Journal of Convergence for Information Technology
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• v.11 no.11
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• pp.151-158
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• 2021

In this paper, we analyzed the latest research trends, challenges, and potential applications of next-generation solar cell materials in various industrial fields. In addition, future prospects and possibilities of Smart Textile Hybrid Energy Harvesting Devices that will supply electricity by combining with wearable IoT devices are presented. The hybrid textile energy harvesting device fused next-generation solar cells with tribo-piezoelectric devices will develop into new 'Convergence Integrated Smart Wear' by combining the material itself with wearable IoT devices in the era of the 4th industrial revolution. The next-generation nanotechnology and devices proposed in this paper will be applied to the field of smart textile with an energy harvesting function. And we hope it will be a paradigm shift that evolves into creative products which provide AI services such as medical & healthcare by convergence with the future smart wear industry.

• The Journal of Information Systems
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• v.28 no.3
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• pp.159-202
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• 2019

Purpose The purpose of this study is to explain users' wearable healthcare device adoption using performance expectancy, effort expectancy, the hedonic motivation and price value of UTAUT2, and to identify the causal relationship between intention to use wearable healthcare device and innovation resistance formed by perceived risks. Design/methodology/approach The research model proposed in this study is based on UTAUT2(Extended Unified Theory of Acceptance and Use of Technology) and MIR(Model of Innovation Resistance). In specific, performance expectancy, effort expectancy, hedonic motivation and price value of UTAUT2 and innovation resistance formed by perceived risks of MIR are adopted in our research model. To validate the research model, we carry out the analysis of the survey data using Smart PLS 3.0 to test the hypotheses. Findings According to the empirical analysis results, this study confirms that the performance expectancy, effort expectancy, hedonic motivation, and price value have significant effects on the intention to use wearable healthcare devices. It also finds that perceived risk affects innovation resistance and in turn, innovation resistance affects the intention to use wearable healthcare devices.