• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1951-1956
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• 2008

Various MEMS accelerometers are used in engineering applications including automobiles, mobile phones, military systems, and electronic devices. Among them, the thermal accelerometer employing the temperature difference induced by the convective flow inside the micro cavity has been a topic of interest. As the convective sensor does not utilize a solid proof mass, it is compact, lightweight, inexpensive to manufacture, sensitive and highly endurable to mechanical shock. However, the complexity of the convective flow and various design constraints make optimization of a device a crucial step before fabrication. In this work, optimization of a 2-axis thermal convective MEMS accelerometer is conducted based on 3-dimensional numerical simulation. Parametric studies are performed by varying the several design variables such as the heater shape/size, the cavity size and types of the gas medium and the position of temperature probes in the sensor. The results of optimal design are presented.

• Journal of the Korea institute for structural maintenance and inspection
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• v.19 no.4
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• pp.43-48
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• 2015

In this study, a method to enhance the dynamic range of seismic sensor is proposed. The low frequency noise included in the measurement of seismic sensor is modelled as an ARMA(Auto Regressive Moving Average) model and the order and parameters of the model are identified through system identification method. The identified noise model is augmented into Kalmman filter which estimate seismic signal from sensor measurement. The proposed method is applied to a newly developed seismic sensor which is MEMS based 3-axis accelerometer type. The experiment show that the proposed method can enhance the dynamic range compared to the simple low pass filtering.

• Journal of Korea Multimedia Society
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• v.17 no.4
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• pp.506-513
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• 2014

In recent years, research on user's activity recognition using a smart phone has attracted a lot of attentions. A smart phone has various sensors, such as camera, GPS, accelerometer, audio, etc. In addition, smart phones are carried by many people throughout the day. Therefore, we can collect log data from smart phone sensors. The log data can be used to analyze user activities. This paper proposes an approach to inferring a user's physical activities based on the tri-axis accelerometer of smart phone. We propose recognition method for four activity which is physical activity; sitting, standing, walking, running. We have to convert accelerometer raw data so that we can extract features to categorize activities. This paper introduces a recognition method that is able to high detection accuracy for physical activity modes. Using the method, we developed an application system to recognize the user's physical activity mode in real-time. As a result, we obtained accuracy of over 80%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.2
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• pp.397-407
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• 2015

In this paper, we designed 1 chip IC for 3-axis gyroscope and 3-axis accelerometer used for various IoT/M2M mobile devices such as smartphone, wearable device and etc. We especially focused on analysis of gyroscope noise and proposed new architecture for removing various noise generated by gyroscope MEMS and IC. Gyroscope, accelerometer and geo-magnetic sensors are usually used to detect user motion or to estimate moving distance, direction and relative position. It is very important element to designing a low noise IC because very small amount of noise may be accumulated and affect the estimated position or direction. We made a mathematical model of a gyroscope sensor, analyzed the frequency characteristics of MEMS and circuit, designed a low noise, compact and low power 1 chip 6-axis inertial sensor IC including 3-axis gyroscope and 3-axis accelerometer. As a result, designed IC has 0.01dps/${\sqrt{Hz}}$ of gyroscope sensor noise density.

• Journal of the Korea institute for structural maintenance and inspection
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• v.18 no.1
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• pp.160-165
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• 2014

In this study, an efficiency test was performed by fabricating MEMS (Micro Electro Mechanical Systems) based 3-axis acceleration sensor modules and an earthquake monitoring system was composed. Data acquisition device (NI-9239) with a 24bit ADC (Analog to Digital Converter) was used for improving the performance of 3-axis acceleration sensor modules and filtered data (100Hz Low Pass Filter) was used for reducing noises. Also this paper focused on detecting meaningful vibration in the building by developing the earthquake monitoring software. If vector sum of 3-axis acceleration is greater than the preset value, the value will be recorded and saved to the file.

• The Journal of the Korea Contents Association
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• v.10 no.4
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• pp.98-105
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• 2010

Health of the people involved in blood sugar, blood pressure, activity, and using bio-sensors to obtain biometric information, the system for monitoring health research for development is a lot. This paper analyzes the bio information by monitoring the u-health care agent system was developed. Activity measurement technology that uses 3-axis accelerometer sensor. 3-axis acceleration sensors, using information obtained from activity to activity analysis to calculate the exact algorithm was developed. More accurate than the existing system to calculate the calorie consumption, it is stored in the database management. and you can check your health status using of activity and bio-information.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.101-102
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• 2007

We demonstrate a novel calibration-free vehicle crash and rollover detect system by using a 3-axis accelerometer as a sensor element.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.542-544
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• 2005

This paper describes the detection of spatio-temporal parameter using an accelerometer and footswitches to evaluate a symmetry and balance of hemiplegic patients. We detected gait data using a 3-axis accelerometer that mounted between L3 and IA intervertebral area and footswitches made by FSR-Sensor attached insole. To minimize the error of the gait parameters to be detected incorrectly in case of using only accelerometer, we enhancement the performance of detection by measuring an accelerometer and foots witches data at the same time. So, it was possible to detect more accurate gait parameters. As a result, we can confirm the symmetry and balance of hemiplegic patients. In the future. these results could be used to evaluate the walking ability in hemiplegic patients in clinical pratice.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.2
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• pp.67-74
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• 2017

This paper proposes a method of user authentication through the patterns of arm movement with a wrist-type wearable device. Using the accelerometer sensor which is built in the device, the 3-axis accelerometer data are collected. Then, the collected data are integrated and the periodic cycle are extracted. In the cycle, the features of frequency are generated with the accelerometer. With the frequency features, 2D Gaussian mixture are modelled. For authenticating an user, the data(the accelerometer) of the user at some point are tested with confidence interval of the Gaussian distribution. The model showed a valuable results for the user authentication with an example, which is average 92% accuracy with 95% confidence interval.

• Journal of Sensor Science and Technology
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• v.20 no.2
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• pp.137-144
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• 2011

Wireless sensor network(WSN) has the potential to greatly effect many aspects of u-healthcare. By outfitting the potential with WSN, wearable sensor node can collects real-time data on physiological status and transmits through base station to server PC. However, there is a significant gap between WSN and healthcare. WSN has the limited resource about computing capability and data transmission according to bio-sensor sampling rates and channels to apply healthcare system. If a wearable node transmits ECG and accelerometer data of 4 channel sampled at 100 Hz, these data may occur high loss packets for transmitting human activity and ECG to server PC. Therefore current wearable sensor nodes have to solve above mentioned problems to be suited for u-healthcare system. Most WSN based activity and ECG monitoring system have been implemented some algorithms which are applied for signal vector magnitude(SVM) algorithm and ECG noise algorithm in server PC. In this paper, A wearable sensor node using integrated ECG and 3-axial accelerometer based on wireless sensor network is designed and developed. It can form multi-hop network with relay nodes to extend network range in WSN. Our wearable nodes can transmit 1-channel activity data processed activity classification data vector using SVM algorithm to 3-channel accelerometer data. ECG signals are contaminated with high frequency noise such as power line interference and muscle artifact. Our wearable sensor nodes can remove high frequency noise to clear original ECG signal for healthcare monitoring.