• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.1
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• pp.220-224
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• 2010

In this study, we designed a device for consecutively observing position, utilizing 3-axises acceleration sensor. This method offer to check his or her wrong position and developed could to help derived a position appliance. And, we developed a Cobb's angle value in three dimensional using 3-axises acceleration sensor. A proposed device with integrated accelerometers, which can detect postural changes in terms of curvature variation of the spine in the sagittal and coronal planes, has been developed with intention to facilitate posture training. The proposed device was evaluated with 3 normal subjects daily activities. We evaluated the performance of our designed device as calculating the correlation coefficients and mean errors between the angle measured by an electro-goniometer and that estimated by a gravity accelerometer and verified the accuracy and sensitivity. The results showed that the angle obtained from the proposed device revealed a linear characteristic at the range of $\pm60^{\circ}$(correlation coefficient 0.99, error range $\pm2^{\circ}$). We demonstrated that our device could detect the changes of the motion in upper trunk accurately. Also, our device showed good potential for treatment of the patients with scoliosis and prevention of the unbalance position during a daily life.

• 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 Institute of Electronics Engineers of Korea SC
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• v.45 no.3
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• pp.1-11
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• 2008

This paper proposes a real-time method using a 3-axis accelerometer to enhance blurred images taken from a camera loaded in mobile devices. Blurring phenomenon is a smoothing effect occurring in photo images. Algorithms to cope with blurring phenomenon is essential since small-size mobile devices tremble severely by even a tiny hand-shaking of a user. In this paper, accurate sensing characteristics of the 3-axis accelerometer is acquired by applying the sensor in pendulum motion and the blurring phenomenon is modeled as a uniform distribution and Gaussian distribution. Also, non-Gaussian distributed model is observed in the experiment of real blurring phenomenon and a particular deblurring function is designed by reversing the model. It has been demonstrated that the application of trembling information to the deblurring function adequately removes the blurring phenomenon.

• Journal of Sensor Science and Technology
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• v.16 no.6
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• pp.467-474
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• 2007

The real-time monitoring about the activity of the human provides useful information about the activity quantity and ability. The present study implemented a small-size and low-power acceleration monitoring system for convenient monitoring of activity quantity and recognition of emergent situations such as falling during daily life. For the wireless transmission of acceleration sensor signal, we developed a wireless transmission system based on a wireless sensor network. In addition, we developed a program for storing and monitoring wirelessly transmitted signals on PC in real-time. The performance of the implemented system was evaluated by assessing the output characteristic of the system according to the change of posture, and parameters and acontext recognition algorithm were developed in order to monitor activity volume during daily life and to recognize emergent situations such as falling. In particular, recognition error in the sudden change of acceleration was minimized by the application of a falling correction algorithm

• Journal of the Korea Society of Computer and Information
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• v.15 no.6
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• pp.11-18
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• 2010

In this paper, it introduced the device that was fabricated for monitoring sleeping positions of infants with 3-axis accelerometer. Sleep monitoring studies has been usually conducted two ways. To monitor sleeping posture by installing a camera and then recording of sleep in the sleeping room continuously is the first one. The other one is monitoring pressure sensor's results data for sleeping. Those two ways' benefits are that are able to get relatively accurate sleeping posture data but, there are many disadvantages like constraints of spaces and places, the installation of sensors or cameras, and high cost. In addition, it has a lot of problems that difficult to solve. For babies, it's not easy to apply, as well as uncomfortable. The proposed method uses a 3-axis accelerometer's X axis, Y axis, Z axis position output values in order to recognize the bad ground sleeping position that use of the buzzer alarm. This method uses a 3-axis acceleration sensor to measure the data and transmit sleeping posture using Bluetooth wireless in real time monitoring. The data is helpful for prevention safety hazard such as choked themselves when they slept back side on.

• Journal of Sensor Science and Technology
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• v.9 no.3
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• pp.196-202
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• 2000

In this paper, we proposed the new bridge combination detection method for three dimensional piezoresistive silicon accelerometer, and the accelerometer with SOI structures was fabricated by bulk micromachining technology for using higher temperature than $200^{\circ}C$. The sensitivities of fabricated accelerometer for X, Y and Z-axis acceleration were about 8mV/V G, 8mV/V G and 40mV/V G. The nonlinearity of the output voltage was 1.6%FS and cross-axis sensitivity was within 4.6%. We confirmed that the three bridges detection method is very simple and the output characteristics of this accelerometer were similar to arithmetic circuit method accelerometer. The temperature characteristics of SOI structure accelerometer showed high operating temperature and good stability. And the temperature coefficient of offset voltage and sensitivity were $1033ppm^{\circ}C^{-1}$ and $1145ppm^{\circ}C$ respectively.

• Proceedings of the Korean Society of Computer Information Conference
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• 2012.01a
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• pp.7-10
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• 2012

본 논문에서는 스마트폰을 이용하여 도로 주행 정보를 기록하고 운전자에게 패턴 별 주행정보를 제공하는 라이프로그(Lifelog) 형태의 서비스에 목적을 두고 있다. 운전자의 도로 주행 데이터를 데이터베이스화한 이 정보는 다양하게 이용될 수 있다. 주행 패턴 인식은 이벤트 구간 검출 과정을 통한 패턴 구간을 검출하고 가속도 센서와 방향 센서, 즉 멀티 센서 기반으로 주행패턴을 인식한다. 주행 패턴을 분석 후 시간 정보를 이용하여 촬영된 영상 데이터에서의 패턴 구간 영상을 같이 제공한다. 이렇게 패턴 구간의 센서 스트리밍 정보와 영상을 제공하면 운전자의 운전 성향 및 주행 기록을 분석하는데 이용될 수 있다. 따라서 주행패턴 인식 알고리즘을 프로토타입으로 제안한다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.6
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• pp.135-140
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• 2021

In this paper is a study on system design to prevent accidents using accelerometers. A switching power FET was configured at the power supply stage, and DC-DC converter, a regulator, and an LDO were designed for the power supply. In order to solve the power problem at once, it was divided into two parts, and a 3-axis accelerometer was designed to extract motion information to safely prevent accidents. Microprocessor enables communication through I2C and UART communication ports, and enables debugging through J-LINK. As a result of measuring the acceleration sensor data, it was confirmed that the power is normally cut off to prevent accidents when motion at an angle of 30° or more is detected.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.6
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• pp.303-309
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• 2012

Energy expenditure values were estimated based on the voice signals and body activities. Voice signals and body activities were obtained using PVDF contact vibration sensor and 3-axis accelerometer, respectively. Vibration caused by voices, activity signals, and actual energy consumption were acquired using data acquisition system and gas analyzer. With the use of power values from the voice signals and weight as independent variables, R-square of 0.918 appeared to show the highest value. For activity outputs, use of signal vector magnitude, body mass index, height, and age as independent variables revealed to provide the highest correlation with actual energy expenditure. Estimation of energy expenditure based on voice and activity provides more accurate results than based on activity only.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.6
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• pp.1150-1158
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• 2010

In this paper, a new reliable portable activity monitoring device implemented with the buddhist-style bowing activity and walking step detection algorithm, is presented. In order to monitor the bowing and walking activities, miniaturized 3-axis accelerometer sensor with the sensitivity of 800 mV/g was used. After initial signal conditioning, vector magnitude of accelerometer signals was calculated. Syntactic peak detection method was used in order to feature points. All signal processing algorithms were implemented in ultra-low power microcontroller MSP430 with double precision floating point arithmetic. For evaluation, 19 young man($24.22\pm5.22$ yrs) and woman($22.28\pm2.72$ yrs) were involved. The accuracy of the proposed algorithms were 98.91 %($\pm0.011$) for walking step detection and 98.25 %($\pm0.023$) for buddhist-style bowing activity. Comparing to the commercialized pedometer accuracy, 87.1 %($\pm0.058$), the proposed walking step detection algorithms show more reliable accuracy.