• IEMEK Journal of Embedded Systems and Applications
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• v.6 no.2
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• pp.68-75
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• 2011

This paper describes the development of an open source motion sensor emulator. It helps developers to understand the motion sensor and its data better. Through this emulator, the realtime or stored motion sensor data can be applied to the applications that utilize motion sensors. The data of motion sensors which include accelerometer sensor, magnetic field sensor, gyro sensor, GPS, and so on, can be collected by using smart phones or motion sensors. We also describe a visualizer which shows various graphs, video and 3D animations based on the data sent by the emulator. It helps developers to understand motion sensors and how to use the sensors. The developed emulator is compatible with Android sensor simulator.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.1
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• pp.67-76
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• 2005

In this paper, An analysis on the intelligence system for a biped walking robot(BWR) was made and its results were applied to the BWR. Various sensors were applied to the developed BWR for autonomous and intelligent walk in unknown environments. To measure the distance between the object and BWR, ultrasonic sensor and infrared-rays sensor were used. To identity surrounding environments, vision system was used. Gyro sensor was used to control the posture of BWR. Also, piezoelectricity sensor was used to identity the pressure of foot landing on the surface. Sensors applied to the robot have measurement errors according to noises or walking environments. To improve the function of these sensors, influences of noise or sensing errors were minimized using a sensor fusion scheme. A gait test using the sensor fusion system was performed, and its results are presented.

• Journal of Korea Multimedia Society
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• v.17 no.12
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• pp.1437-1445
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• 2014

A smartphone has very limited input methods regardless of its various functions. In this respect, it is one alternative that sensor motion recognition can make intuitive and various user interface. In this paper, we recognize user's motion using acceleration sensor, magnetic field sensor, and gyro sensor in smartphone. We try to reduce sensing error by gradient descent algorithm because in single sensor it is hard to obtain correct data. And we apply vector quantization by conversion of rotation displacement to spherical coordinate system for elevated recognition rate and recognition of small motion. After vector quantization process, we recognize motion using HMM(Hidden Markov Model).

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.56 no.4
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• pp.161-167
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• 2007

This paper introduces a dynamic walking control of biped walking robot using intelligent sensor interface and shows an intelligent control method for biped walking robot. For the dynamic walking control of biped walking robot, serious motion controllers are used. They are main controller(using INTEL80C296SA MPU), sub controller(using TMS320LF2406 DSP), sensor controller(using Atmega128 MPU) etc. The used sensors are gyro sensor, tilt sensor, infrared sensor, FSR sensor etc. For the feasibility of a dynamic walking control of biped walking robot, we use the biped walking robot which has twenty-five degrees of freedom(D.O.F.) in total. Our biped robot is composed of two legs of six D.O.F. each, two arms of five D.O.F. each, a waist of two D.O.F., a head of one D.O.F.

• Journal of Sensor Science and Technology
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• v.22 no.1
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• pp.54-64
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• 2013

In this study, we developed a falling recognition system to transmit SMS data through CDMA communication using a three axises acceleration sensor and a two axises gyro sensor. 5 healthy men were selected into a control group, and the fall recognition system using the three axises acceleration sensor and the two axises gyro sensor was devised to conduct an experiment. The system was attached to the upper of their sternum. According to the experiment protocol, the experiment was carried out 3 times repeatedly divided into 3 specific protocols: falling during gait, falling in stopped state, and falling in everyday life. Data obtained in the falling recognition system and LabVIEW 8.5 were used to decide if falling corresponds to that regulated in an analysis program applying an algorithm proposed in this study. In addition, results from falling recognition were transmitted to designated cellular phone in a SMS (Shot Message Service) form. These research results show that an erroneous detection rate of falling reached 19% in applying an acceleration signal only; 6% in applying an angular velocity; and 2% in applying a proposed algorithm. Such finding suggests that an erroneous detection rate of falling is improved when the proposed algorithm is applied incorporated with acceleration and angular velocity. In this study therefore, we proposed that a falling recognition system implemented in this study can make a contribution to the recognition of falling of the aged or the disabled.

• Journal of the Korea Convergence Society
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• v.11 no.5
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• pp.9-17
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• 2020

Human activity recognition(HAR) using smartphones is a hot research topic in computational intelligence. Smartphones are equipped with a variety of sensors. Fusing the data of these sensors could enable applications to recognize a large number of activities. However, these devices have fewer resources because of the limited number of sensors available, and feature selection and classification methods are required to achieve optimal performance and efficient feature extraction. This paper proposes a smartphone-based HAR scheme according to these requirements. The proposed method in this paper extracts time-domain features from acceleration sensors, gyro sensors, and barometer sensors, and recognizes activities with high accuracy by applying KDA and SVM. This approach selects the most relevant feature of each sensor for each activity. Our comparison results shows that the proposed system outperforms previous smartphone-based HAR systems.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.79-79
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• 2000

In this Paper, the PC input device using MEMS gyros and accelerometer is newly developed, so that it can measure rotation rate and linear acceleration of the human body in space. In General, the human motion has 6 degree of freedom but 2 degree of freedom is enough PC monitor with 2D display. Therefore the simple method is proposed to achieve minimum degree of freedom. It is also applied to the PC mouse. This method can be expanded to the input device for internet set-top box or internet TV.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.4
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• pp.39-46
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• 2008

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.7
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• pp.1218-1223
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• 2007

A surface micro machined angular rate sensor utilizing a vibrating MEMS structure on a silicon has been developed. These tuning fork angular rate sensors are extremely rugged, inherently balanced, and easy to fabricate. The device is fabricated using a temperature compensation method based on automatic gain control technique. A linearity of approximately 0.6%, limited by the on-chip electronics has been obtained with this new sensor. Tests of the sensor demonstrate that its performance is equivalent to that required for implementation of a yaw control system. Vehicle handling and safety are substantially improved using the sensor to implement yaw control.

• Journal of the HCI Society of Korea
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• v.5 no.2
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• pp.1-6
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• 2010

In this research, we designed the head mouse system for disabled and gamers, a mouse controller which can be controlled by head movements and eye blinks only, and compared its performance with other regular mouse controller systems. The head mouse was moved by a gyro-sensor, which can measure an angular rotation of a head movement, and the eye blink was used as a clicking event of the mouse system. Accumulated errors caused by integral, which was a problem that previous head mouse system had, were removed periodically, and treated as dead zones in the non-linear relative point graph, and direct mouse point control was possible using its moving distance and acceleration calculation. We used the active light sources to minimize the influence of the ambient light changes, so that the head mouse was not affected by the change in external light source. In a comparison between the head mouse and the gazing tracking mouse (Quick Glance), the above method resulted about 21% higher score on the clicking event experiment called "20 clicks", about 25% higher on the dasher experiment, and about 37% higher on on-screen keyboard test respectively, which concludes that the proposed head mouse has better performance than the standard mouse system.