• Journal of Sensor Science and Technology
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• v.5 no.4
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• pp.57-70
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• 1996

Motion can be estimated continuously from each sensor through the analysis of the instantaneous states of an object. This paper is aimed to introduce a method to estimate the general 3D motion of a planar object from the instantaneous states of an object using multi-sensor data fusion. The instantaneous states of an object is estimated using the linear feedback estimation algorithm. The motion estimated from each sensor is fused to provide more accurate and reliable information about the motion of an unknown planar object. We present a fusion algorithm which combines averaging and deciding. With the assumption that the motion is smooth, the approach can handle the data sequences from multiple sensors with different sampling times. Simulation results show proposed algorithm is advantageous in terms of accuracy, speed, and versatility.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.5
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• pp.493-497
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• 2010

Real time coordinate conversion of vessel was realized, we developed motion control algorithm of DC Servo Motor. We made servo control circuit and PCB, also We developed the system using 3-axis Gyro Sensor based Servo Motion Controller. For ship's movement simulation, we made the ship simulator of 6 degree of freedom. With a mounted camera on developed simulator, We tested the desired ship's movement, and the desired result of error tolerance was obtained.

• Journal of the Korea Society of Computer and Information
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• v.23 no.8
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• pp.17-23
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• 2018

In this paper, we implemented a flight posture simulator that intuitively understands aircraft flight posture and visualizes the principle of motion. The proposed system operates the 6 - axis motion platform according to the change of the navigation information and transmits the flight attitude to the simulator using the gyro sensor. A gyro sensor and an acceleration sensor are used together to analyze the attitude of the aircraft. The reason is that the gyro sensor has a cumulative error in the integration process. And the accelerometer sensor was compensated by using the complementary filter because noise was serious due to short term vibration. Using the compensated sensor information, the motion platform is operated by calculating the angle to be transmitted to the 6-axis motor. And visualization result is implemented using OpenGL. The results of this study can be used as teaching materials for students related to aviation in the future.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.37.3-37
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• 2002

$\textbullet$ Mobile robots $\textbullet$ Sensor-based motion planning $\textbullet$ Potential field $\textbullet$ Local minimum-free motion $\textbullet$ Virtual target point $\textbullet$ Set of linked line segments $\textbullet$ We build a sensor-based motion planning using virtual target point for free of local minimum

• Journal of Biomedical Engineering Research
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• v.30 no.3
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• pp.185-190
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• 2009

Biomedical mobile devices for ubiquitous healthcare consist of biomedical sensors and communication terminal. They have two types of configuration. One is the sensor-network type device using wired or wireless communication with intelligent sensors to acquire biomedical data. The other is the sensor embedded type device, where the data can be acquired directly by itself. There are many examples of sensor network type, such as, fall detection sensor, blood glucose sensor, and ECG sensors networked with commercial PDA phone and commercial phone terminal for ubiquitous healthcare. On the other hand, sensor embedded type mounts blood glucose sensor, accelerometer, and etc. on commercial phone. However, to enable true ubiquitous healthcare, motion sensing is essential, because users go around anywhere and their signals should be measured and monitored, when they are affected by the motion. Therefore, in this paper, two biomedical mobile devices with motion monitoring function were addressed. One is sensor-network type with motion monitoring function, which uses Zigbee communication to measure the ECG, PPG and acceleration. The other is sensor-embedded type with motion monitoring function, which also can measure the data and uses the built-in cellular phone network modem for remote connection. These devices are expected to be useful for ubiquitous healthcare in coming aged society in Korea.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.4
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• pp.229-237
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• 2022

Motion recognition is very useful for implementing an intuitive HMI (Human-Machine Interface). In particular, hands are the body parts that can move most precisely with relatively small portion of energy. Thus hand motion has been used as an efficient communication interface with other persons or machines. In this paper, we design and implement a light-weight ANN (Artificial Neural Network)-based hand motion recognition using a state-of-the-art flex sensor. The proposed design consists of data collection from a wearable flex sensor, preprocessing filters, and a light-weight NN (Neural Network) classifier. For verifying the performance and functionality of the proposed design, we implement it on a low-end embedded device. Finally, our experiments and prototype implementation demonstrate that the accuracy of the proposed hand motion recognition achieves up to 98.7%.

• Korean Journal of Applied Biomechanics
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• v.31 no.3
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• pp.183-188
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• 2021

Objective: The purpose of this study was to develop a stretchable joint motion sensor that is based on silver nano-particle. Through this sensor, it can be utilized as an equipment for rehabilitation and analyze joint movement. Method: In this study, precursor solution was created, after that, nozel printer (Musashi, Image master 350PC) was used to print on a circuit board. Sourcemeter (Keithley, Keithley-2450) was used in order to evaluate changes of electric resistance as the sensor stretches. In addition, the sensor was attached on center of a knee joint to 2 male adults, and performed knee flexion-extension in order to evaluate accurate analysis; 3 infrared cameras (100 Hz, Motion Master 100, Visol Inc., Korea) were also used to analyze three dimensional movement. Descriptive statistics were suggested for comparing each accuracy of measurement variables of joint motions with the sensor and 3D motions. Results: The change of electric resistance of the sensor indicated multiple of 30 times from initial value in 50% of elongation and the value of electric resistance were distinctively classified by following 10%, 20%, 30%, 40% of elongation respectively. Through using the sensor and 3D camera to analyze movement variable, it showed a resistance of 99% in a knee joint extension, whereas, it indicated about 80% in flexion phase. Conclusion: In this research, the stretchable joint motion sensor was created based on silver nanoparticle that has high conductivity. If the sensor stretches, the distance between nanoparticles recede which lead gradual disconnection of an electric circuit and to have increment of electric resistance. Through evaluating angle of knee joints with observation of sensor's electric resistance, it showed similar a result and propensity from 3D motion analysis. However, unstable electric resistance of the stretchable sensor was observed when it stretches to maximum length, or went through numerous joint movements. Therefore, the sensor need complement that requires stability when it comes to measuring motions in any condition.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.5
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• pp.998-1013
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• 2013

Wireless wearable sensor networks have emerged as a promising technique for human motion tracking due to the flexibility and scalability. In such system several wireless sensor nodes being attached to human limb construct a wearable sensor network, where each sensor node including MEMS sensors (such as 3-axis accelerometer, 3-axis magnetometer and 3-axis gyroscope) monitors the limb orientation and transmits these information to the base station for reconstruction via low-power wireless communication technique. Due to the energy constraint, the high fidelity requirement for real time rendering of human motion and tiny operating system embedded in each sensor node adds more challenges for the system implementation. In this paper, we discuss such challenges and experiences in detail during the implementation of such system with wireless wearable sensor network which includes COTS wireless sensor nodes (Imote 2) and uses TinyOS 1.x in each sensor node. Since our system uses the COTS sensor nodes and popular tiny operating system, it might be helpful for further exploration in such field.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.2
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• pp.145-152
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• 2010

Gait phase detection is important for evaluating the recovery of gait ability in patients with paralysis, and for determining the stimulation timing in FES walking. In this study, three different motion sensors(tilt sensor, gyrosensor and accelerometer) were used to detect gait events(heel strike, HS; toe off, TO) and they were compared one another to determine the most applicable sensor for gait phase detection. Motion sensors were attached on the shank and heel of subjects. Gait phases determined by the characteristics of each sensor's signal were compared with those from FVA. Gait phase detections using three different motion sensors were valid, since they all have reliabilities more than 95%, when compared with FVA. HS and TO were determined by both FVA and motion sensor signals, and the accuracy of detecting HS and TO with motion sensors were assessed by the time differences between FVA and motion sensors. Results show of that the tilt sensor and the gyrosensor could detect gait phase more accurately in normal subjects. Vertical acceleration from the accelerometer could detect HS most accurately in hemiplegic patient group A. The gyrosensor could detect HS and TO most accurately in hemiplegic patient group A and B. Valid error ranges of HS and TO were determined by 3.9 % and 13.6 % in normal subjects, respectively. The detection of TO from all sensor signals was valid in both patient group A and B. However, the vertical acceleration detected HS validly in patient group A and the gyrosensor detected HS validly in patient group B. We could determine the most applicable motion sensors to detect gait phases in hemiplegic patients. However, since hemiplegic patients have much different gait patterns one another, further experimental studies using various simple motion sensors would be required to determine gait events in pathologic gaits.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.603-605
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• 2005

In this paper, we deal with a calibration method for low cost motion capture sensor using PSD (Position Sensitive Detection). The PSD sensor is employed to measure the direction of incident light from moving markers attached to motion body. To calibrate the PSD optical module, a conventional camera calibration algorithm introduced by Tsai. The 3-dimensional positions of the markers are measured by using stereo camera geometry. From the experimental results, the low cost motion capture sensor can be used in a real time system.