• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.17 no.11
• /
• pp.2615-2620
• /
• 2013

Recently consumers pursue optimized health condition and high leveled quality of life through active promotion and prevention activity of health as the importance of health during daily life is emerged to meet the demand of aging society. Thus healthcare service is evolved into smart healthcare stage using various type of smart devices depending upon the needs of consumers. However the connectivity and interoperability among individual medical devices and smart devices are insufficient, thus data accumulation through individual medical devices is also insufficient. This thesis suggest the methodology to establish the connection among Bluetooth HDP and individual medical devices based on smart TV in addition to the monitoring of biometrics.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2021.11a
• /
• pp.921-923
• /
• 2021

최근 반려동물 시장이 커짐으로 인해, 반려동물들의 헬스케어를 위한 제품들이 증가하고 있다. 이에 따라 펫 웨어러블 디바이스를 통한 연구가 활발히 진행되고 있지만, 웨어러블 디바이스를 통해 수집되는 센싱 데이터는 변칙적인 반려동물의 특징 때문에 연구의 한계를 갖는다. 이를 위해 본 논문에서는 1-Dimensional CNN과 LSTM 하이브리드 모델을 기반으로 한 반려동물 행동 분류를 제안한다. 웨어러블 디바이스를 이용해 자이로와 가속도 센서를 수집하여 걸음수를 측정하고, 이후 수집된 센싱 데이터로 반려동물의 행동을 4가지로 분류한다. 행동 분류는 걷기, 뛰기, 앉기, 서기로 분류한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.10a
• /
• pp.104-105
• /
• 2021

Along with the rapid development of ICT, health management is continuing based on various smart healthcare devices in an aging society and non-face-to-face era caused by COVID-19. In this paper, a heart rate monitor was manufactured using the DF Robot SEN0203 heart rate sensor based on Arduino so that you can check your health and maintain a healthy life by measuring the heart rate per minute in real time to support personalized health management. The device manufactured through this thesis can be used in various ways, such as a wristband or a smart watch.

• The Journal of the Korea Contents Association
• /
• v.15 no.5
• /
• pp.498-506
• /
• 2015

As smart phone market has been rapidly saturated, wearable devices have been emerging as a new growth power in the post smart phone era. This study aims to comprehend the influential factors of purchasing intention of product features(perceived usefulness, perceived ease of use) and individual characteristics(innovation, fashion leadership, self-efficacy, concern for health) of wrist wearable device. The result shows that fashion leadership and health concern among consumers' individuality, and perceived usefulness and perceived usability among product features are proved to be significant factors. This means that both usefulness and usability have significant impacts on purchase intention of wearable device and product development should be made to enhance user experience.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2016.04a
• /
• pp.243-245
• /
• 2016

웨어러블 디바이스 시장이 커지고 있고, 웨어러블 디바이스의 성능이 좋아지고 있다. 이에 발맞춰 웨어러블 디바이스를 이용한 인증, 헬스케어 등 다양한 서비스들이 제공 되고 있다. 다양한 서비스를 제공할 때 웨어러블 디바이스에서 수집한 개인 정보들이 통신 과정을 통해 이동하게 된다. 이용자들에게 개인정보 보호는 중요한 문제이기 때문에 웨어러블 디바이스에 대한 보안은 중요하다. 그러나 웨어러블 디바이스에서의 통신 표준문서 IEEE802.15.6의 프로토콜은 사실상 표준에서 요구하는 보안 요구사항을 만족하지 못한다. 본 논문에서는 4개의 키 합의 프로토콜 중 3번 프로토콜에서의 취약점을 파악하고 보안 요구사항을 만족하는 안전한 키 합의 프로토콜을 제안한다. 제안한 프로토콜은 표준에서 요구하는 보안 요구사항을 만족하며, 웨어러블 디바이스 통신 환경에서 안전한 통신을 가능하게 한다.

• Journal of Technology Innovation
• /
• v.25 no.3
• /
• pp.1-24
• /
• 2017

With the rise of internet of things (IoT), there have been several studies to analyze the technological trend and technological convergence. However, previous work have been relied on the qualitative work that investigate the IoT trend and implication for future business. In response, this study considers the patent information as the proxy measure of technology, and conducts a quantitative and analytic approach for analyzing technological convergence using patent co-classification analysis and text mining. First, this study investigate the characteristics of IoT business, and characterize IoT business into four dimensions: device, network, platform, and services. After this process, total 923 patent classes are classified into four types of IoT technology group. Since most of patent classes are classified into device technology, we developed a co-classification network for both device technology and all technologies. Patent keywords are also extracted and these keywords are also classified into four types: device, network, platform, and services. As a result, technologies for several IoT devices such as sensors, healthcare, and energy management are derived as a main convergence group for the device network. For the total IoT network, base network technology plays a key role to characterize technological convergence in the IoT network, mediating the technological convergence in each application area such as smart healthcare, smart home, and smart grid. This work is expected to effectively be utilized in the technology planning of IoT businesses.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.10 no.9
• /
• pp.2354-2360
• /
• 2009

Healthcare is a field where ubiquitous computing is most widely used. We propose a mining-based healthcare multi-agent system for ubiquitous computing environments. This proposed scheme select diagnosis patterns using mining in the real-time biosignal data obtained from a patient's body. In addition, we classify them into normal, emergency and be ready for an emergency. This proposed scheme can deal with the enormous quantity of real-time sensing data and performs analysis and comparison between the data of patient's history and the real-time sensory data. We separate Association rule exploration into two data groups: one is the existing enormous quantity of medical history data. The other group is real-time sensory data which is collected from sensors measuring body temperature, blood pressure, pulse. Proposed system has advantage that can handle urgent situation in the far away area from hospital through PDA and mobile device. In addition, by monitoring condition of patient in a real time base, it shortens time and expense and supports medical service efficiently.

• The Journal of the Convergence on Culture Technology
• /
• v.8 no.2
• /
• pp.1-6
• /
• 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 Advanced Navigation Technology
• /
• v.18 no.6
• /
• pp.619-624
• /
• 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.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2016.10a
• /
• pp.671-673
• /
• 2016

기술의 발전에 따라 소형 디바이스에서도 데이터를 수집하고 전송하는 것이 가능해졌다. 따라서 최근 IoT와 헬스케어가 부각되고 있으며 여기서 발생한 데이터에 대한 많은 연구가 진행되고 있다. 그 중에서도 헬스케어 장비에 내장된 심전도 센서를 이용하여 시계열 데이터를 수집할 수 있고, 여기서 수집한 데이터는 부정맥 등의 심장질환 진단의 중요한 지표로서 사용될 수 있다. 시계열 데이터는 시계열 분석 방법을 사용하여 정상 패턴과 비정상 패턴으로 분류할 수 있지만, 대량의 시계열 분석 방법은 수행시간이 많이 소요되기 때문에 이를 단축 할 필요성이 있다. 본 논문에서는 시계열 데이터 분석 기법 중 하나인 Shapelet을 사용하여 심전도 데이터의 패턴을 정상 및 비정상으로 분류하였고, 병렬처리 기법을 적용하여 수행시간을 단축하였다. 실험 결과, 각각의 심전도 데이터는 87%의 정확도로 분류되었고, Shapelets을 탐색하는 구간의 병렬처리를 통하여 수행 시간이 약 60%로 감소하였음을 확인하였다.