• Journal of Digital Contents Society
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• v.19 no.9
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• pp.1803-1810
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• 2018

Recently, many researches related to IoT (Internet of Things) have been actively conducted. In order to improve the context aware function of smart wearable devices using the IoT, we proposed a noise reduction method for the event data of the sensor part. In thisstudy, the adoption of the low - pass filter induces the attenuation of the abnormally measured value, and the benefit was obtained from the situation recognition using the event data of the sensor. As a result, we have validated attenuation for abnormal or excessive noise using event data detected and reported by 3-axis acceleration sensors on some devices, such as smartphones and smart watches. In addition, various pattern data necessary for real - time context aware were obtained through noise pattern analysis.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1963-1967
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• 2003

Communication device to use slight movement for serious disabled is proposed. This device is developed mainly for patients suffering from ALS or a cerebral infarction. They often have communication difficulty because of deterioration of muscular functions. Features of this device are that the device is wearable on the user’s body and that it detects the movement of eyebrow. Because of these features, it is quite easy to install the sensor on the patient’s body, not like the conventional sensors. Furthermore, an adaptive communication software is incorporated. A feature of this software is that the arrangement and size of the button and window on the display can be optimized depending on the user's physical ability. In the field test it is confirmed that the communication device developed in this study is successfully helped the people with disability for increasing their communication ability.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.11
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• pp.1330-1338
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• 2011

Social activities of the elderly have been increasing as our society progresses toward an aging society. As their activities increase, so does the occurrence of falls that could lead to fractures. Falls are serious health hazards to the elderly. Therefore, development of a device that can detect fall accidents and prevent fracture is essential. In this study, we developed a portable fall detection system for the fracture prevention system of the elderly. The device is intended to detect a fall and activate a second device such as an air bag deployment system that can prevent fracture. The fall detection device contains a 3-axis acceleration sensor and two 2-axis tilt sensors. We measured acceleration and tilt angle of body during fall and activities of daily(ADL) living using the fall detection device that is attached on the subjects'. Moving mattress which is actuated by a pneumatic system was used in fall experiments and it could provide forced falls. Sensor data during fall and ADL were sent to computer and filtered with low-pass filter. The developed fall detection device was successful in detecting a fall about 0.1 second before a severe impact to occur and detecting the direction of the fall to provide enough time and information for the fracture preventive device to be activated. The fall detection device was also able to differentiate fall from ADL such as walking, sitting down, standing up, lying down, and running.

• Journal of the Korea Society of Computer and Information
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• v.22 no.2
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• pp.9-19
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• 2017

Useful continuous sensing applications are increasingly emerging as a new class of mobile applications. Meanwhile, open, multi-use sensor devices are newly adopted beyond smartphones, and provide huge opportunities to expand potential application categories. In this upcoming environment, uncoordinated use of sensor devices would cause severe imbalance in power consumption of devices, and thus result in early shutdown of some sensing applications depending on power-hungry devices. In this paper, we propose EnergyCordy, a novel inter-device energy use coordination system; with a system-wide holistic view, it coordinates the energy use of concurrent sensing applications over multiple sensor devices. As its key approach, we propose a relaxed sensor association; it decouples the energy use of an application from specific sensor devices leveraging multiple context inference alternatives, allowing flexible energy coordination at runtime. We demonstrated the effectiveness of EnergyCordy by developing multiple example applications over custom-designed wearable senor devices. We show that EnergyCordy effectively coordinates the power usage of concurrent sensing applications over multiple devices and prevent undesired early shutdown of applications.

• 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.

• Journal of KIISE
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• v.43 no.7
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• pp.781-785
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• 2016

Learning from human behaviors in the real world is essential for human-aware intelligent systems such as smart assistants and autonomous robots. Most of research focuses on correlations between sensory patterns and a label for each activity. However, human activity is a combination of several event contexts and is a narrative story in and of itself. We propose a novel approach of human activity prediction based on event cognition. Egocentric multi-sensor data are collected from an individual's daily life by using a wearable device and smartphone. Event contexts about location, scene and activities are then recognized, and finally the users" daily activities are predicted from a decision rule based on the event contexts. The proposed method has been evaluated on a wearable sensor data collected from the real world over 2 weeks by 2 people. Experimental results showed improved recognition accuracies when using the proposed method comparing to results directly using sensory features.

• Fashion & Textile Research Journal
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• v.24 no.5
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• pp.647-654
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• 2022

Wearable devices come in a variety of shapes and sizes in numerous fields in numerous fields and are available in various forms. They can be integrated into clothing, gloves, hats, glasses, and bags and used in healthcare, the medical field, and machine interfaces. These devices keep track individuals' biological and behavioral data to help with health communication and are often used for injury prevention. Those with hearing loss or impaired vision find it more difficult to recognize an approaching person or object; these sensing devices are particularly useful for such individuals, as they assist them with injury prevention by alerting them to the presence of people or objects in their immediate vicinity. Despite these obvious preventive benefits to developing Internet of Things based devices for the disabled, the development of these devices has been sluggish thus far. In particular, when compared with people without disabilities, people with hearing impairment have a much higher probability of averting danger when they are able to notice it in advance. However, research and development remain severely underfunded. In this study, we incorporated a wearable detection system, which uses an infrared proximity sensor, into a backpack. This system helps its users recognize when someone is approaching from behind through visual and tactile notification, even if they have difficulty hearing or seeing the objects in their surroundings. Furthermore, this backpack could help prevent accidents for all users, particularly those with visual or hearing impairments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.791-793
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• 2016

In the development of various types of sensor technology, the general users smartphone, the environment is increased, which can be seen in contact with the movement recognition device, such as a console game machine (Nintendo Wii), an increase in the user needs of the action recognition-based input device there is a tendency to have. Mouse existing behavior recognition, attached to the outside, is mounted in the form of mouse button is deformed, the left mouse was the role of the right button and a wheel, an acceleration sensor (or a gyro sensor) inside to, plays the role of a mouse cursor, is to manufacture a compact, there is a difficulty in operating the button, to apply a motion recognition technology is used to operate recognition technology only pointing cursor is limited. Therefore, in this paper, using a MEMS-based motion-les Koguni tion sensor (Motion Recognition Sensor), to recognize the behavior of the two points of the human body (thumb and forefinger), to generate the motion data, and this to the foundation, compared to the pre-determined matching table (moving and mouse button events cursor), and generates a control signal by determining, were studied the generated control signal input device of the computer wirelessly transmitting.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.12
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• pp.1521-1527
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• 2013

This study proposes a wearable master device that can measure the joint stiffness and the angular displacement of a human operator to enhance the adapting capability of a slave system. A lightweight inertial sensor and the exoskeleton mechanism of the master device can make an operator feel comfortable, and artificial pneumatic muscles having a working principle similar to that of human muscles improve the performance of the slave device on emulating what a human operator does. Experimental results revealed that the proposed master/slave system based on the muscle stiffness sensor yielded uniform tracking performance compared with a conventional position-feedback controller when the payload applied to the slave system changed.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.2059-2066
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• 2018

This study explored the feasibility of utilizing an SWCNT-coated fabric sensor for the development of a wearable motion sensing device. The extent of variation in electric resistance of the sensor material was evaluated by varying the fiber composition of the SWCNT-coated base fabrics, attachment methods, number of layers, and sensor width and length. 32 sensors were fabricated by employing different combinations of these variables. Using a custom-built experimental jig, the amount of voltage change in a fabric sensor as a function of the length was measured as the fabric sensors underwent loading-unloading test with induced strains of 30 %, 40 %, and 50 % at a frequency of 0.5 Hz. First-step analysis revealed the following: characteristics of the strain-voltage curves of the fabric sensors confirmed that 14 out of 32 sensors were evaluated as more suitable for measuring human joint movement, as they yield stable resistance values under tension-release conditions; furthermore, significantly stable resistance values were observed at each level of strain. Secondly, we analyzed the averaged maximum, minimum, and standard deviations at various strain levels. From this analysis, it was determined that the two-layer sensor structure and welding attachment method contributed to the improvement of sensing accuracy.