• 한국IT서비스학회:학술대회논문집
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• 2009.11a
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• pp.453-458
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• 2009

The purpose of this study was to detect early children with hyperactivity which is one of the symptoms of Attention Deficit - Hyperactivity Disorder (:ADHD). For this Purpose, This study used two methods; K-CBCL and observation of children`s behavior. K-CBCL was done online by parents at home. For observation of children's behavior, the school asked children to wear a 3 - axis accelerometer on their wrists. The data from K - CBCL and 3 - axis accelerometer were analyzed and clustered to separate hypersensitive children from ordinary children.

• International Journal of Automotive Technology
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• v.8 no.6
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• pp.753-760
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• 2007

In this paper, a roll and pitch estimation algorithm using a set of accelerometers and wireless sensor networks(S/N) is presented for use in a passenger vehicle. While an inertial measurement unit(IMU) is generally used for roll/pitch estimation, performance may be degraded in the presence of longitudinal acceleration and yaw motion. To compensate for this performance degradation, a new roll and pitch estimation algorithm is proposed that uses an accelerometer array, global positioning system(GPS) and in-vehicle networks to get information from yaw rate and roll rate sensors. Angular acceleration and roll and pitch approximation are first calculated based on vehicle kinematics. A discrete Kalman filter is then applied to estimate both roll and pitch more precisely by reducing noise from the running engine and from road disturbance. Finally, the feasibility of the proposed algorithm is shown by comparing its performance experimentally with that of an IMU in the framework of an indoor test platform as well as a test vehicle.

• Journal of Positioning, Navigation, and Timing
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• v.7 no.2
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• pp.91-103
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• 2018

Conventional inertial measurement units cannot be used in the spinning vehicle with high rotation rate due to gyro's narrow operation range. By the way, angular acceleration can be measured using the accelerometer array distributed in the vehicle. This paper derives a mechanization for the gyro-free INS in the navigation frame, and proposes a gyro-free INS algorithm based on the derived mechanization. In addition, the proposed algorithm is used to estimate angular velocity, attitude, velocity, and position of a spinning vehicle with high rotation rate. A MATLAB-based software platform is configured in order to show validation of the proposed algorithm. The reference trajectory of a spinning vehicle at 3 round per second, 30 round per second are set up, and the outputs of accelerometer are generated when triads of accelerometer are located at the origin and all the axes. Navigation results of the proposed algorithm for the generated output are presented. The results show that the proposed navigation algorithm can be applied to the spinning vehicle with high rotation rate.

• KEPCO Journal on Electric Power and Energy
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• v.6 no.4
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• pp.405-411
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• 2020

In this paper, we designed the COS MEMS system for sensing the falling detection and explosive noise of fuse link in COS (Cut Out Switch) installing on the power distribution. This system analyzed the failure characteristics and an instantaneous breakdown of power distribution. Therefore, our system strengths the industrial competence and guaranties the stable power supply. In this paper, we applied BLE (Bluetooth Low Energy) technology which is suitable protocol for low data rate, low power consumption and low-cost sensor applications. We experimented with LSM6DSOX which is system-in-module featuring 3 axis digital accelerometer and gyroscope boosting in high-performance mode and enabling always-on low-power features for an optimal motion for the COS fuse holder. Also, we used the MP34DT05-A for gathering an ultra-compact, low power, omnidirectional, digital MEMS microphone built with a capacitive sensing element and an IC interface. The proposed COS MEMS system is developed based on nRF52 SoC (System on Chip), and contained a 3-axis digital accelerometer, a digital microphone, and a SD card. In this paper of experiment steps, we analyzed the performance of COS MEMS system with gathering the accelerometer raw data and the PDM (Pulse Data Modulation) data of MEMS microphone for broadcasting the failure of COS status.

• ETRI Journal
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• v.45 no.6
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• pp.1079-1089
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• 2023

Stroke is one of the leading causes of long-term disability worldwide, placing huge burdens on individuals and society. Further, automatic human activity recognition is a challenging task that is vital to the future of healthcare and physical therapy. Using a baseline long short-term memory recurrent neural network, this study provides a novel dataset of stretching, upward stretching, flinging motions, hand-to-mouth movements, swiping gestures, and pouring motions for improved model training and testing of stroke-affected patients. A MATLAB application is used to output textual and audible prediction results. A wearable sensor with a triaxial accelerometer is used to collect preprocessed real-time data. The model is trained with features extracted from the actual patient to recognize new actions, and the recognition accuracy provided by multiple datasets is compared based on the same baseline model. When training and testing using the new dataset, the baseline model shows recognition accuracy that is 11% higher than the Activity Daily Living dataset, 22% higher than the Activity Recognition Single Chest-Mounted Accelerometer dataset, and 10% higher than another real-world dataset.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.2
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• pp.155-161
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• 2016

This paper proposes a novel fabrication method for a capacitive type micro-accelerometer with uniform nano-gap using photo-assisted electro-chemical etching. The sensitivity of the accelerometer should be improved while the electrodes between the inertial mass and the sensing comb should be narrowed. In this paper the nano-gap trench structure is fabricated using the photo-assisted electrochemical etching method. The sensor was designed and analysed using ANSYS simulator. The characteristics of the etching were observed according to the dc bias, the light intensity, the composition of the solution, the temperature of the solution, and the pattern pitch variation. The optimum etching conditions were dc bias of 2V, Blue LED of 20mA, 49wt% HF:DMF:D.I.Water=1:20:10, the pattern pitch of $20{\mu}m$. Uniform trench structure with width of 344nm and depth of $11.627{\mu}m$ are formed using the optimum condition.

• Journal of the Korea Society of Computer and Information
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• v.15 no.10
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• pp.129-136
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• 2010

In this paper proposed the sensor fusion algorithm between a gyroscope and an accelerometer to maintain the inverted posture with two wheels which can make the robot body move to the desired destination. Mobile inverted robot fall down to the forward or reverse direction to converge to the stable point. Therefore, precise information of tilt angles and quick posture control by using the information are necessary to maintain the inverted posture, hence this paper proposed the sensor fusion algorithm between a gyroscope to obtain the angular velocity and a accelerometer to compensate for the gyroscope. Kalman Filter is normally used for the algorithm and numerous research is progressing at the moment. However, a high-performing DSP and systems are needed for the algorithm. This paper realized the robot control method which is much simpler but able to get desired performance by using the sensor fusion algorithm and PID control.

• 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.

• Journal of Korea Multimedia Society
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• v.16 no.1
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• pp.67-74
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• 2013

In this paper, we propose the pointing and correction algorithm for optimized performance based on Bluetooth communication. The error from the accelerometer sensor's output must be carefully managed as the accelerometer sensor is more sensitive to data change compared to that of the gyroscope sensor. Thus, we minimize the noise by applying the Kalman filter to data for each axis from the accelerometer. In addition, we can also obtain effect compensating the hand tremor by applying the Kalman filter to the data variation for x and y. In this study, we extract data through the Quaternion mapping process on data from the accelerometer and gyroscope. In turn, we can obtain a tilt compensation by applying a compensation algorithm with acceleration of the gravity of the extracted data. Moreover, in order to correct the inaccuracy on smart sensor due to the rapid movement of a device, we propose a adaptive pointing and correction algorithm using the genetic approach to generate the initial population depending on the user.

• JSTS:Journal of Semiconductor Technology and Science
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• v.17 no.3
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• pp.438-445
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• 2017

This paper presents a low-power high-resolution band-pass ${\Sigma}{\Delta}$ ADC for accelerometer applications. The proposed band-pass ${\Sigma}{\Delta}$ ADC consists of a high-performance 6-th order feed-forward ${\Sigma}{\Delta}$ modulator with 1-bit quantization and a low-power, area-efficient digital filter. The ADC is fabricated in 180 nm 1P6M mixed-signal CMOS process with a die area of $5mm^2$. This high-resolution ADC got 90 dB peak signal to noise plus distortion ratio (SNDR) and 96 dB dynamic range (DR) over 4 kHz bandwidth, while the intermediate frequency (IF) is shifting from 100 KHz to 200 KHz. The power dissipation of the chip is 5.6 mW under 1.8 V (digital)/3.3 V (analog) power supply.