• Korea Science and Art Forum
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• v.34
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• pp.251-262
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• 2018

The purpose of this study is to understand how wearable computing devices are designed and how to design them in a technology based wearable device design research. Research is premised on the consideration of producers and consumers. There is wearable computer of eyeglasses, watches, clothes, and so on. The user can always wear these products comfort and use as part of the body without any sense of discomfort, and the goal is to supplement or double the ability of the human being. It should be easy to use them convenient, wear comfortable, safe and sociable at any time. For the satisfaction these conditions, the wearable computing devices have several factors. There are technical performances, visual aesthetics, Human body system and devices communication and safety. Furthermore, these factors have to match to operating system, real-time operating system and applied software. To comprehend wearable computing devices should be offered the design of the both software and hardware designed.

• Journal of Information Processing Systems
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• v.20 no.2
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• pp.159-172
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• 2024

The number of healthcare products available for pets has increased in recent times, which has prompted active research into wearable devices for pets. However, the data collected through such devices are limited by outliers and missing values owing to the anomalous and irregular characteristics of pets. Hence, we propose pet behavior recognition based on a hybrid one-dimensional convolutional neural network (CNN) and long short- term memory (LSTM) model using pet wearable devices. An Arduino-based pet wearable device was first fabricated to collect data for behavior recognition, where gyroscope and accelerometer values were collected using the device. Then, data augmentation was performed after replacing any missing values and outliers via preprocessing. At this time, the behaviors were classified into five types. To prevent bias from specific actions in the data augmentation, the number of datasets was compared and balanced, and CNN-LSTM-based deep learning was performed. The five subdivided behaviors and overall performance were then evaluated, and the overall accuracy of behavior recognition was found to be about 88.76%.

• ETRI Journal
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• v.39 no.2
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• pp.145-150
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• 2017

As wearable devices are powered by batteries, they need to consume as little energy as possible. To address this challenge, in this article, we propose a synergistic technique for energy-efficient approximate speech signal processing (ASSP) for wearable devices. More specifically, to enable the efficient trade-off between energy consumption and sound quality, we synergistically integrate an approximate multiplier and a successive approximate register analog-to-digital converter using our enhanced conversion algorithm. The proposed ASSP technique provides ~40% lower energy consumption with ~5% higher sound quality than a traditional one that optimizes only the bit width of SSP.

• Journal of the Korea Society of Computer and Information
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• v.24 no.9
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• pp.43-49
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• 2019

Today, with the development of the internet of things, wearable devices related to personal health care have become widespread. Various global information and communication technology companies are developing various wearable health devices, which can collect personal health information such as heart rate, steps, and calories, using sensors built into the device. However, since individual health data includes sensitive information, the collection of irrelevant health data can lead to personal privacy issue. Therefore, there is a growing need to develop technology for collecting sensitive health data from wearable health devices, while preserving privacy. In recent years, local differential privacy (LDP), which enables sensitive data collection while preserving privacy, has attracted much attention. In this paper, we develop a technology for collecting vast amount of health data from a smartwatch device, which is one of popular wearable health devices, using local difference privacy. Experiment results with real data show that the proposed method is able to effectively collect sensitive health data from smartwatch users, while preserving privacy.

• The Journal of Information Systems
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• v.27 no.3
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• pp.181-202
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• 2018

Purpose Wearable device is considered as one of the methods powering the growth of the next generation. However, ICT's innovation resistance has been a contributing factor in slowing down this spread of wearable devices. Taking into consideration the lack of empirical research to this phenomenon, this study served to examine the effect of determinants of wearable devices to usage with the perspectives of behavioral economics. Design/methodology/approach: For research purposes, this study developed research hypotheses in order to empirically examine the factors that might have a significant effect on the usage of the wearable device. The empirical research was based on a survey which carried through 500 participants. Research results were evaluated via SPSS Statistics 21.0 and AMOS 19 statistical package program. Findings: Results showed that perceived costs and benefits had a significant effect on coupling. It means that perceived benefits lowering coupling and perceived costs increasing coupling. Perceived costs and benefits also had a significant effect on innovation resistance. Finally, perceived costs and benefits had a significant effect on the consumers' usage of wearable devices.

• Journal of the Korean Society for information Management
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• v.38 no.4
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• pp.129-152
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• 2021

This study proposed a plan to develop wearable devices suitable for female college students by analyzing female college students' perceptions and preferences for wearable devices and their needs for health care using topic modeling and network analysis techniques. To this end, 2,457 posts related to health care and wearable devices were collected from the community used by S Women's University students. After preprocessing the collected posts and comment data, LDA-based topic modeling was performed. Through topic modeling techniques, major issues of female college students related to health care and wearable devices are derived, and bi-gram analysis and network analysis are performed on posts containing related keywords to understand female college students' views on wearable devices.

• Journal of the Ergonomics Society of Korea
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• v.36 no.4
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• pp.281-292
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• 2017

Objective: This study aims to identify important physical design variables in designing a necklace type wearable device, and to present design guidelines to maximize comfort that a user feels upon wearing the device. Background: Interests in fitness culture and personal health are on the rise recently. In such a situation, demand for necklace type wearable devices is projected to increase a lot, as the devices enable users to use their hands freely and to enjoy various contents through connection with mobile devices. However, the necklace type wearable device's comfort was assessed to have the lowest comfort in a running situation, where human body moves up and down and left and right more than other devices wearable on other human body parts. Therefore, the usability of a necklace type wearable device was low. In this regard, studies on identification of the variables affecting user comfort upon wearing a necklace type wearable device and on physical design direction maximizing comfort and usability are needed. Method: A pretest and a main test were carried out to draw the direction of necklace type wearable device design. In the pretest, wearing evaluation on the diverse types of devices released in the market was conducted to draw physical design variables of the devices affecting comfort. Furthermore, variables significantly affecting the comfort of a device were selected through an analysis of variance (ANOVA). In the main test, anthropometry was performed, and information on anthropometric items corresponding to the design variables selected in the pretest was acquired. Based on the pretest results and the anthropometric information in the main test, the present study produced design guidelines maximizing the comfort of a necklace type wearable device with regard to major design variables upon dynamic tasks. Results: According to the pretest results, the variables having effects on comfort were the angle of side points, width, and height. Due to interactions between variables, those need to be simultaneously considered upon designing a device. Upon dynamic tasks, the angle of side points and width of a device was designed to be smaller than mean angle of the trapezius muscle and neck width, and thus attachment to human body was high. As height was designed to be larger than mean neck front and rear point width, comfort was higher due to feeling of stability. Conclusion: Because user sensitivity to comfort was high at human body's inflection points, a device needs to be designed for users not to feel high pressure on specific body parts with the device fitting human body shape well. A design considering user's situation is also required in further studies.

• International Journal of Computer Science & Network Security
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• v.21 no.2
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• pp.221-228
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• 2021

Recent improvements on the quality, fidelity and availability of biometric data have led to effective human physical activity detection (HPAD) in real time which adds significant value to applications such as human behavior identification, healthcare monitoring, and user authentication. Current approaches usually use machine-learning techniques for human physical activity recognition based on the data collected from wearable accelerometer sensor from a single wearable smart device on the user. However, collecting data from a single wearable smart device may not provide the complete user activity data as it is usually attached to only single part of the user's body. In addition, in case of the absence of the single sensor, then no data can be collected. Hence, in this paper, a continuous HPAD will be presented to effectively perform user activity detection with mobile service infrastructure using multiple wearable smart devices, namely smartphone and smartwatch placed in various locations on user's body for more accurate HPAD. A case study on a comprehensive dataset of classified human physical activities with our HAPD approach shows substantial improvement in HPAD accuracy.

• Journal of Sensor Science and Technology
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• v.30 no.3
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• pp.181-184
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• 2021

Interest in healthcare and wearable devices has been increasing recently. A strain sensor is required in various wearable devices. With respect to such devices, studies on resistance changes in strain sensors using flexible materials are in progress. However, the resistance of the rest area in a strain sensor should not change according to the applied strain. So, an electrode with resistance to stretching, bending, and torsion is required in such strain sensors. Tension, bending, and torsion can be realized through structural shape control, rather than by using flexible materials. Further, such an electrode that maintains electrical properties has been developed and manufactured. This electrode can be used in various applications such as foldable devices, e-papers, batteries, and multifunctional wearable devices.

• International Journal of Advanced Culture Technology
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• v.8 no.1
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• pp.218-225
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• 2020

Purpose Wearable devices are widely used in our daily life. The purpose of this study is to investigate the relationship between persuasive designs of fitness trackers and users' physical activity behavior. Methods To test the research model, data was collected from a web-based survey in China, resulting in an effective sample of 166 usable questionnaires. The survey was restricted only to respondents who wear a fitness tracker. Results The sample surveyed in this study indicated that half of the respondents had been wearing a smart fitness tracker shorter than one year, and only 27% were long-time users (longer than two years). Dialogue support and social support strategies were both proved to be effective in increasing users' workout behavior intention. Social support strategies had a greater effect on behavior change than dialogue support strategies. Conclusion The findings from this study make several contributions to the practice. Wearable devices developers can employ the result from this study to help them design devices, which can persuade people to do more exercises and preserve a healthier life.