• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.735-738
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• 2019

본 연구에서는 불안장애를 가진 사람들이 겪는 불안한 상황들을 수치화하여 보호자와 불안해하는 본인에게 불안 상황을 해소할 수 있도록 하여 일상생활에 도움을 주고자 한다. 이를 관리 할 수 있도록 아두이노(Arduino) 센서를 활용하여 심박수 데이터와 체내의 전기 전도도 데이터를 수집할 수 있다. 수집한 데이터들은 애플리케이션 DB에 저장되어 캘린더 형식의 UI 화면에서 저장된 데이터들을 날짜마다 확인할 수 있으며 특정 수치 이상 증가 시에 저장된 번호로 SMS알림을 주어 현재 사용자의 상황을 알려 줄 수 있다.

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

• 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%.

• The Journal of the Korea Contents Association
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• v.21 no.6
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• pp.285-294
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• 2021

This study analyzes the factors that determine the attitude toward the electronic wristband(smartband) to check the position of self-quarantine subjects due to COVID-19. Furthermore, I analyze the interaction of class and age among the factors that determine attitudes toward the electronic wristband. In this study, the attitude toward self-quarantine electronic wristband is analyzed as a binary logit model, focusing on class and age. As a result of the analysis, the middle class significantly agreed with the self-quarantine electronic wristband compared to the lower class, and the older the person, the more in favor. On the other hand, the interaction between the class and the age shows that the age weakens the positive effect on the attitude of the self-quarantine electronic wristband in the middle and upper middle classes. The implication of this study is that it is necessary to push for mandatory electronic wristband in areas with high proportion of high-aged people with positive attitude toward self-quarantine electronic wristband and in the same age group, the approval rate is low, so it is necessary to promote mandatory electronic wristband in areas where the vulnerable class is dense.