• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.249-252
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• 2008

A wearable ubiquitous health care monitoring system using integrated ECG and accelerometersensors based on WSN is designed and developed. Wireless sensor network technology is applied for non intrusive healthcare in some wide area coverage with small battery support for RF transmission. We developed wearable devices which are wearable USN node, sensor board and base-station. Low power operating ECG and accelerometer sensor board was integrated to wearable USN node for user's health monitoring. The wearable ubiquitous healthcare monitoring system allows physiological data to be transmitted in wireless sensor network from on body wearable sensor devices to a base-station connected to server PC using IEEE 802.15.4. Physiological data displays and stores on server PC continuously.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.11
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• pp.2427-2432
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• 2009

This paper proposes an monitoring system of elder and feeble person's motion activity using an object's motion activity data. The proposed system used wireless 3-axis sensor module, product by Freescale(Wireless Sensing Triple Axis Reference Design Board (ZSTAR)). We distribute sensing data into three classes using Neural Network System SVM. We find performance of proposed system that simulate some case about walk, past walk, fallen. Classify result data and graph of sensing data present succes rate 80%.

• Journal of the Korea Society of Computer and Information
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• v.17 no.3
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• pp.27-32
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• 2012

Balance measurement is widely used in fields of physiotherapy, neurology, sport medicine and rehabilitation medicine. This paper presents the development of balance measurement and rehabilitation training system. To this end, we have developed a prototype system using an 3-axis accelerometer sensor attached to the under surface of balance board. As a results, the system is stable and shows a good degree of balance function. Also, the various patterns for rehabilitation training can be added easily. This system can be used for daily balance monitoring and will contribute to increasing the effectiveness of training.

• Journal of Biomedical Engineering Research
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• v.32 no.2
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• pp.177-184
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• 2011

In this study, the system for application of the bone stimulation was implemented using high frequency and low strain method. The whole system consists of the high frequency and low strain vibration stimulation system 177 for stimulating bone, LVDT sensor, and wireless sensor based on tri-axial accelerometer. To evaluate the usefulness of the system, the frequencies and accelerations from function generator were applied to the vibration stimulation system. The range of frequency was 17 Hz, 30 Hz, 45 Hz, 50 Hz and the range of acceleration was set 0.3 g, 0.6 g, 1g, and 2 g. The measured frequencies and acceleration using LVDT (linear variable difference transformer) sensor and 3-axial accelerometer were estimated and compared. The range of frequencies average difference was from 0.0 to 0.004 Hz. As the standard deviation of frequencies estimated by LVDT sensor and accelerometer was below 0.03 Hz and the output frequencies of function generator were similar: Also the results of t-test were satisfied with conditions of p > 0.05. And the acquired frequencies and acceleration from vibration measuring device module were estimated and analyzed. As the mean of accelerations was similar to the acceleration applied from function generator. And the standard deviation of acceleration estimated from vibration measuring device module was ranged from 0.019 g to 0.038 g. Also the results of t-test were satisfied with conditions of p > 0.05. Therefore, these results were airy similar to the acceleration applied from function generator. As a result, the usefulness of the system was confirmed. n a further study, clinical experiment will be carried out with the authorization of IRB (institutional review board) so that appropriate frequency and strain would be investigated in clinical field.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.1
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• pp.709-714
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• 2017

Structures like bridges or buildings need to be checked continuously to diagnose their safety. However, it is extremely difficult for the people who access such structures to check all areas directly. To overcome this problem, there is a lot of active research into structural health monitoring (SHM) with wireless sensor nodes (WSNs). In this paper, for more accurate checking of SHM with WSNs, we experimentally compare and evaluate the performance of Xenomai, which provides real-time processing under the traditional Linux kernel. For this purpose, we patch Xenomai into the traditional Linux kernel of a commercial embedded board, Raspberry Pi, and implement a task that periodically reads vibration data of the z-axis from an accelerometer in order to analyze the natural frequency of cantilever beams. Reading the data from the traditional Linux kernel with the same method, we analyze the natural frequency of the cantilever beams using Smart Office Analyzer. Finally, to review the validity of Xenomai for WSNs, we obtain vibration data on the z-axis from the accelerometer via wired network and compared and analyzed them the same way.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.6
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• pp.375-381
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• 2019

Structural health monitoring to determine structural conditions at an early stage and to efficiently manage the energy requirements of buildings using systems that collects relevant data, is under active investigation. Structural monitoring requires cutting-edge technology in which construction, sensing, and ICT technologies are combined. However, the scope of application is limited because expensive sensors and specialized technical skills are often required. In this study, a Raspberry Pi module, one of the most widely used single board computers, a Lora module that is capable of long-distance communication at low power, and a high-performance accelerometer are used to construct a wireless edge computing system that can monitor building response over an extended time period. In addition, the Raspberry Pi module utilizes an edge computing algorithm, and only meaningful data is obtained from the vast amount of acceleration data acquired in real-time. The raw data acquired using Wi-Fi communication are compared to the Laura data to evaluate the accuracy of the data obtained using the system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.4
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• pp.781-788
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• 2013

In this paper, we introduce a quadruped robot-based alarm system for monitoring the emergency situation due to falling in the elderly. Quadruped robot includes the FPGA Board(Field Programmable Gate Array) applying a red-color tracking algorithm. To detect a falling of the elderly, a sensor node is worn on chest and accelerations and angular velocities measured by the sensor node are transferred to quadruped robot, and then the emergency signal is transmitted to manager if a fall is detected. Manager controls the robot and then he judges the situation by monitoring the real-time images transmitted from the robot. If emergency situation is decided by the manager, he calls 119. When the fall detection system using only sensor nodes is used, sensitivity of 100% and specificity of 98.98% were measured. Using the combination of the fall detection system and portable camera (robot), the emergency situation was detected to 100 %.

• Smart Structures and Systems
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• v.19 no.1
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• pp.1-10
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• 2017

The operation of subway trains induces secondary structure-borne vibrations in the nearby underground spaces. The vibration, along with the associated noise, can cause annoyance and adverse physical, physiological, and psychological effects on humans in dense urban environments. Traditional tethered instruments restrict the rapid measurement and assessment on such vibration effect. This paper presents a novel approach for Wireless Smart Sensor (WSS)-based autonomous evaluation system for the subway train-induced vibrations. The system was implemented on a MEMSIC's Imote2 platform, using a SHM-H high-sensitivity accelerometer board stacked on top. A new embedded application VibrationLevelCalculation, which determines the International Organization for Standardization defined weighted acceleration level, was added into the Illinois Structural Health Monitoring Project Service Toolsuite. The system was verified in a large underground space, where a nearby subway station is a good source of ground excitation caused by the running subway trains. Using an on-board processor, each sensor calculated the distribution of vibration levels within the testing zone, and sent the distribution of vibration level by radio to display it on the central server. Also, the raw time-histories and frequency spectrum were retrieved from the WSS leaf nodes. Subsequently, spectral vibration levels in the one-third octave band, characterizing the vibrating influence of different frequency components on human bodies, was also calculated from each sensor node. Experimental validation demonstrates that the proposed system is efficient for autonomously evaluating the subway train-induced ambient vibration of underground spaces, and the system holds the potential of greatly reducing the laboring of dynamic field testing.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.565-568
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• 2009

This paper proposes an monitoring system of elder and feeble person's motion activity using an object's motion activity data. The proposed system used wireless 3-axis sensor module, product by Freescale(Wireless Sensing Triple Axis Reference Design Board (ZSTAR)). We distribute sensing data into three classes using Neural Network System SVM. We find performance of proposed system that simulate some case about walk, past walk, fallen. Classify result data and graph of sensing data present succes rate 80%.

• Journal of the Korean Institute of Gas
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• v.2 no.3
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• pp.88-95
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• 1998

Vibration analysis of rotating machinery can give an indication of possible faults thus allowing maintenance before further damage occurs. Current predictive maintenance system installed in Pyung-tak has the ability to diagnose the mechanical problems within the LNG Pump when the vibration exceeds preset overall alarm levels. In this study, LNG pump auto-diagnosis system based upon Windows NT and DSP Board is developed. This system analysis velocity signal acquired from dual accelerometer input monitor system to diagnose pump condition. Many plots which display machine condition are shown and features of vibration are stored in every time. If the fault is found, the system diagnoses automatically using expert system and trend monitoring. Operator checks pump condition intuitively using personal computer monitor.