• Journal of Platform Technology
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• v.6 no.4
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• pp.41-48
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• 2018

Accidents involving infants and toddlers are occurring frequently, and if elementary measures are not smooth, they can lead to even greater accidents. Rapid elementary measures require an appropriate monitoring system, and it is necessary to build a system that can accurately monitor the child's living condition and notify the emergency situation immediately. Recently, with the development of IoT technology, various types of sensors are being developed in a very small size, and development of wearable devices connected with smart phones is accelerating with the development of smart phones. By using these wearable devices, it is possible to reduce the risk of infant accidents and to respond promptly in case of an accident. In this paper, we propose a wearable system that can monitor the infant condition and present a service to prevent infant accidents.

• Korean Journal of Applied Biomechanics
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• v.29 no.1
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• pp.1-8
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• 2019

Objective: The purpose of this study was to confirm that the cross-country ski sprint course in PyeongChang, where the 2018 Winter Olympics course was to utilize wearable devices equipped with inertial measurement unit (IMU), global positioning system (GPS) and heart rates sensor. Method: For the data collection, two national level cross-country (XC) skiers performed classic technique on the entire sprint course. We analyzed cycle characteristics, range of motion on double poling (DP) technique, average velocity, and displacement of 3 points according to the terrain. Results: The absolute cycle time gradually decreased during starting, middle and finish sections. While the length of the DP increased and the heart rates tended to increase for men skier. In addition, the results indicated that range of motion of knee joint during starting and finish section decreased more than middle section. The errors of latitude and longitude data collected through GPS were within 3 m from 3 points. Conclusion: Through the first case study in Korea, which analyzed the location and condition of XC skiers in the entire sprint course in real time, confirmed that feedback was available in the field using various wearable sensors.

• Composites Research
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• v.33 no.2
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• pp.50-54
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• 2020

Soft robotics and wearable devices require large motions and flexibility. In this regard, there is a demand for developing stretchable strain sensors which can be attached to the soft robots and wearable devices. In this work, we fabricated stretchable and electrically conductive composite fibers by combining polyurethane (PU) and silver nanoflowers (AgNFs). The PU/AgNF composite fibers showed the change of the resistance as a function of the applied strain, demonstrating the potential for stretchable strain sensors in soft robotics and wearable devices. The mechanical and electrical characteristics of the composite fibers were measured and analyzed to use the composite fibers for stretchable strain sensors.

• Journal of Electrical Engineering and Technology
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• v.13 no.4
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• pp.1732-1739
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• 2018

With the explosion of digital devices, interaction technologies between human and devices are required more than ever. Especially, hand gesture recognition is advantageous in that it can be easily used. It is divided into the two groups: the contact sensor and the non-contact sensor. Compared with non-contact gesture recognition, the advantage of contact gesture recognition is that it is able to classify gestures that disappear from the sensor's sight. Also, since there is direct contacted with the user, relatively accurate information can be acquired. Electromyography (EMG) and force-sensitive resistors (FSRs) are the typical methods used for contact gesture recognition based on muscle activities. The sensors, however, are generally too sensitive to environmental disturbances such as electrical noises, electromagnetic signals and so on. In this paper, we propose a novel contact gesture recognition method based on Flexible Epidermal Tactile Sensor Array (FETSA) that is used to measure electrical signals according to movements of the wrist. To recognize gestures using FETSA, we extracted feature sets, and the gestures were subsequently classified using the support vector machine. The performance of the proposed gesture recognition method is very promising in comparison with two previous non-contact and contact gesture recognition studies.

• Vacuum Magazine
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• v.3 no.3
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• pp.15-18
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• 2016

In future wearable electronic systems, 3-dimensional (3D) devices have attracted much attention due to their high density integration and low-power functionality. Among 3D devices, gate-all-around (GAA) nanowire transistor provides superior gate controllability, resulting in suppressing short channel effect and other drawbacks in 2D metal-oxide-semiconductor field-effect transistor (MOSFET). Silicon nanowires (SiNWs) are the most promising building block for GAA structure device due to their compatibility with the current Si-based ultra large scale integration (ULSI) technology. Moreover, the theoretical limit for subthreshold swing (SS) of MOSFET is 60 mV/dec at room temperature, which causes the increase in Ioff current. To overcome theoretical limit for the SS, it is crucial that research into new types of device concepts should be performed. In our present studies, we have experimentally demonstrated feedback FET (FBFET) and tunnel FET (TFET) with sub-60 mV/dec based on SiNWs. Also, we fabricated SiNW based complementary TFET (c-TFET) and SiNW complementary metal-oxide-semiconductor (CMOS) inverter. Our research demonstrates the promising potential of SiNW electronic devices for future wearable electronic systems.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.2
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• pp.7-16
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• 2019

Neural networks can be implemented in variety of ways, and specialized chips is being developed for hardware improvement. In order to apply such neural networks to wearable devices, the compactness and the low power operation are essential. In this point of view, a suitable implementation method is a digital circuit design using field programmable gate array (FPGA). To implement this system, the learning algorithm which takes up a large part in neural networks must be implemented within FPGA for better performance. In this paper, a back propagation algorithm among various learning algorithms is implemented using FPGA, and this neural network is verified by OR gate operation. In addition, it is confirmed that this neural network can be used to analyze various users' bio signal measurement results by learning algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.861-864
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• 2008

In ubiquitous computing environments that can be connected to the networks any time any where, wearable computer should be able to offer a variety service. The necessity of a variety service using wearable computer becomes more important. In this paper, we can not only provide services over interaction of wearable computer devices, but also propose the method of the better service over interaction of the cell phone.

• Ceramist
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• v.22 no.1
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• pp.4-16
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• 2019

Recently, wearable sensors have received considerable attention in a variety of research fields and industries as the importance of wearable healthcare systems, soft robotics and bio-integrated devices increased. However, expensive and complex processes are hindering the commercialization of wearable sensors. Nanoparticle presents some of solutions to these problems as its adjustable for processability and tunable properties. In this paper, the recent development of nanoparticle based pressure and strain sensors was reviewed, and a discussion on their strategies to overcome the conventional limitation and operating principles is presented.

• Journal of the Korea Society of Computer and Information
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• v.22 no.6
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• pp.95-100
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• 2017

Recently, as stress has become a major threat to people's health, there is a growing interest in wearable stress management services for stress relief. In this paper, we developed a wearable device(Care-on) capable of extracting changeable human voice information at each site and a Healthcare App(S-Manager) that enables stress management in real time using the wearable device. It collects and analyzes variable real-time voice information for each part of the person's body. And It also provides the ability to monitor stress conditions in a mobile environment and provide feedback on the analysis results in step by step in the mobile environment. We tested the developed wearable devices and app in a mobile environment and analyzed the results to confirm their usefulness.

• Journal of Integrative Natural Science
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• v.12 no.1
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• pp.9-13
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• 2019

Recently, as the sleep disorder problem of modern people deepens, the interest towards quality of sleep is increasing. To increase the quality of modern people's sleep. This paper has suggested an LED lighting control system according to the sleep stage using PPG sensors of wearable devices. The pulse of the wrist radial artery was measured using a wearable device mounted with PPG sensor, which enables heart rate-measuring, and by using the point that heart rate lowers during stable sleep than non-sleeping, the LED lighting of indoors was controlled, which is the disturbing element when sleeping. For the performance evaluation, a 10-Fold cross analysis was conducted for performance evaluation, and a result of an average accuracy 87.02% was obtained as a result. Therefore, the LED lighting control system according to the sleep stage using a wearable device of this paper is expected to contribute to raise the quality of the user's life.