• Journal of rehabilitation welfare engineering & assistive technology
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• v.9 no.1
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• pp.67-72
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• 2015

The system for controlling the robotic arm through the foot motion detection was implemented for the disabled who not free to use of the arm. In order to get an image on foot movement, two cameras were setup in front of both foot. After defining multiple regions of interest by using LabView-based Vision Assistant from acquired images, we could detect foot movement based on left/right and up/down edge detection within the left/right image area. After transferring control data which was obtained according to left/right and up/down edge detection numbers from two foot images of left/right sides through serial communication, control system was implemented to control 6-joint robotic arm into up/down and left/right direction by foot. As a result of experiment, we was able to get within 0.5 second reaction time and operational recognition rate of more 88%.

• KIISE Transactions on Computing Practices
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• v.23 no.3
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• pp.148-155
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• 2017

In this paper, we develop a new system to estimate the step count for a smartphone user. The system analyzes data obtained from the accelerometer, magnetic sensor, and gyroscope of an android smartphone to extract pattern information of human steps. We conduct an experiment and evaluation to confirm that the proposed system successfully estimates the number of steps with 96% accuracy when hand-held and 95.5% accuracy when in-pocket. In addition, we found that detection errors were caused by human motions such as touching the screen, shaking the device up and down, sitting up and sitting down, and waving the phone around.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.405-406
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• 2008

This paper presents a high performance 2D PE architecture for H.264 Motion Estimation(ME). While existing 2D PE architectures reuse the overlapped data of adjacent search windows scanned in 1 or 3-way, the new architecture scan adjacent windows and multiple paths instead of single raster and zigzag scanning of adjacent windows in 4 way(up,down,left,right). By reducing the redundant access factor by 1.4, the new 4-way search window improve the memory bandwidth by 70-58% compared with 1/3-way search window. With Altera Stratix-III implementation, the high performance 2D PE architecture deals with SD ($720{\times}480$) video of 2 reference frame, $48{\times}48$ search area and $16{\times}16$ macroblock by 30fps at 97.1MHz.

• The Journal of Korean Physical Therapy
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• v.14 no.2
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• pp.74-85
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• 2002

The purpose of this study was to investigate the effect of static balance performance on gait in elderly. Subjects were twenty four members living in Gwangju(12males, 12females), between 65 and 81 years of age. The Force platform was used to measured static balance performance and gait analyzed the 3-D Motion Analysis The results of this study were as follow ; 1. The postural sway showed, The mean value of toe-heel was $1.41\pm0.51cm$ and left-right was $063\pm0.20cm$. In gait analysis, the mean value of each variable were swing phase $40.5\pm9.65\%$, stance phase $59.5\pm9.65\%$, stride length 0.79m, cadence $0.83\pm0.44step/sec$, velocity $0.57\pm0.32m/sec$, Knee up $34.7\pm31.0^{\circ}$, Knee down $-53.6\pm40.14^{\circ}$. Ankle up $12.14\pm13.94^{\circ}$, Ankle down $-16.8\pm25.0^{\circ}$ showed. 2. The correlation matrix between L-R sway and Toe-heel sway and gait variables was not showed. 3. In multiple regression test, there were no related variable.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1648-1652
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• 2004

An advanced training machine designed for elderly people is proposed. The training machine allows users to have a safe and effective training through exercise close to ordinal motion appears in daily life such as standing up/down motion. The activation level of user's muscle is real timely monitored during the exercise and the training load is adjusted based on the body information. The training load is exerted and continuously controlled by actuation of an air cylinder.

• 한국가시화정보학회:학술대회논문집
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• 2007.11a
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• pp.101-104
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• 2007

Kiwifruit vines with broad leaves are easily torn or shed by high-speed wind. In this study, the threshold wind speed at which a cane is broken was investigated experimentally with varying physical parameters of a kiwifruit vine under two different ABL (atmospheric boundary layer) conditions. In addition, the temporal variation of wind-blown young canes was visualized using a high-speed camera. The average threshold wind speeds for ABL types A and B are about 20.5 m/s and 18.9 m/s, respectively. A wind-blown young cane takes periodic up-and-down motion when it is broken off. The mean motion frequency of young canes of the kiwifruit vines was found to be about 4.5Hz.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.281-285
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• 1990

Our N.C. sewing machine is a device that acts sewing automatically in reference to N.C. data made by data input device. Our N.C. sewing mechine is composed of induction motor that has electric clutch and brake, step motor that drives x-y table. Sewing area of our machine is 170 mm * 100 mm, maximum sewing speed is about 2000 spm, maximum stitch length 6.2 mm. In actual sewing, synchronization between motion of needle up-down and motion of x-y table is a critical factor. In this paper, technology about synchronization will be profoundly discussed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.334-337
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• 2003

In this paper. we introduce a novel actuation method based on dielectric elastomer. Along with basic principles of actuation using dielectric elastomer a new design of actuator is discussed. The proposed design has advantageous features in reduction in size, speed of response, ease and ruggedness of operation. Using the actuator. a three-degree-of-freedom actuator module is developed, which can provide up-down. and two rotational degree-of-freedom motion. In the application of the proposed actuation method, a micro-robot mimicking the motion of an inchworm is developed.

• Korean Journal of Applied Biomechanics
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• v.16 no.3
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• pp.33-41
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• 2006

This study was to analysis three dimension angle of the upper extremity segment and trunk to putting the protector in women bowlers. For this study, the subjects selected 4 players of national and university team. All subjects putted in the same wrist support to satisfy the experiment conditions. To get three dimensions position coordination of swing motion used for 6 ProReflex MCU 240 camera produced by Qualisys. After position coordination calculation, Three dimension angle of the trunk and the upper extremity segment calculated for Matlab 6.5. the result is following; In the trunk motion, there were little differences among the subjects in a flexion and extension change. There were a lot of differences in motion change of the abduction-adduction and internal-external rotation, but the motion types translated to the adduction-abduction-adduction and from the internal rotation toward the external rotation. In the upper arm segment the Flexion and extension showed a consistent motion in the down swing and up swing phase. And the motion change of abduction-adduction and pronation-supination showed a abduction-adduction-abduction and pronation-supination change during swing phase. In the forearm segment changes, it showed a lot of differences among the subjects and a similar change with the upper arm segment. Especially, the hand segment showed a supination motion from the backswing apex to release phase, but for increasing a rotation velocity of ball, the hand segment translated toward pronation in follow throw phase.

• Journal of Korea Multimedia Society
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• v.17 no.5
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• pp.556-565
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• 2014

This paper proposes a method to track object of real-time video transferred through single web-camera and to recognize risk-situation and human actions. The proposed method recognizes human basic actions that human can do in daily life and finds risk-situation such as faint and falling down to classify usual action and risk-situation. The proposed method models the background, obtains the difference image between input image and the modeled background image, extracts human object from input image, tracts object's motion and recognizes human actions. Tracking object uses the moment information of extracting object and the characteristic of object's recognition is moment's change and ratio of object's size between frames. Actions classified are four actions of walking, waling diagonally, sitting down, standing up among the most actions human do in daily life and suddenly falling down is classified into risk-situation. To test the proposed method, we applied it for eight participants from a video of a web-cam, classify human action and recognize risk-situation. The test result showed more than 97 percent recognition rate for each action and 100 percent recognition rate for risk-situation by the proposed method.