• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.4
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• pp.53-58
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• 2009

In recently years, the research and application for sensor has increased in each field. In this paper, the system which can perceive and detect using 3-axis accelerometer sensor and serial communication is proposed. Also, the user has GUI environment for monitor in real-time. In order to reduce unstable data and error defect of electronic rechargeable liquid tilt sensor used digital 3-axis accelerometer sensor which has AD convertor. Therefore, this system provide exact data and a problem of objects for user more easier.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.2
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• pp.105-111
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• 2010

The purpose of this study was to detect early children with hyperactivity which is one of the symptoms of Attention Deficit-Hyperactivity Disorder (ADHD). 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. This experiment confirmed that 3-axis accelerometer which is one of Ubiquitous techniques and the K-CBCL questionnaire were helpful for detection of hypersensitive children.

• Journal of Sensor Science and Technology
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• v.27 no.4
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• pp.254-258
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• 2018

A Wi-Fi signal network (WSN) system is introduced in this paper. This system consists of several data-transmitting sensor modules and a data-receiving server. Each sensor module and the server contain a unique intranet IP address. A piezoelectric accelerometer with a bandwidth of 12 kHz, a 24-bit analog-digital converter with a sampling rate of 15.625 kS/s, a 32-bit microprocessor unit, and a 1-Mbps Wi-Fi module are used in the data-transmitting sensor module. A 300-Mbps router and a PC are used in the server. The system is verified using an accelerometer calibrator. The voltage output from the sensor is converted into 24-bit digital data and transmitted via the Wi-Fi module. These data are received by a Wi-Fi router connected to a PC. The input frequencies of the accelerometer calibrator (320 Hz, 640 Hz, and 1280 Hz) are used in the data transfer verification. The received data are compared to the data retrieved directly from the analog-to-digital converter used in the sensor module. The comparison shows that the developed system represents the original data considerably well. Theoretically, the system can acquire vibration signals from 600 sensor modules at an accelerometer bandwidth of 15.625 kHz. However, delay exists owing to software processes, multiplexing between sensor modules, and the use of non-real time operating system. Hence, it is recommended that this system may be used to acquire vibration signals with up to 10 kHz, which is approximately 70% of the theoretical maximum speed of the system. The system can be upgraded using parts with higher performance

• Proceedings of the Korea Multimedia Society Conference
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• 2012.05a
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• pp.83-85
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• 2012

Gait analysis through wearable sensors is becoming a key research topic in mobile. In gait analysis, step detection is one of the most important processes that will lay down the foundation for future implementation. In this paper, we will propose a simpler algorithm to determine and analyze the steps using accelerometer sensor built-in mobile phone that physically placed into the trouser pocket. This is the location where most of mobile devices are. With 5 volunteers walking in 160 seconds, the accuracy of this method is approximately 98.5%.

• 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.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.12
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• pp.497-506
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• 2017

There have been previous researches about user authentication by analyzing the user's gait or behavior or action using the accelerometer sensor of smartphone, but there was a lack of user convenience to apply PIN entry. In this paper, we propose the technique for PIN entry without a touch on smartphone, the technique uses an accelerometer sensor and a vibration sensor built in the smartphone to enter the PIN. We conducted a usability experiment using the proposed technique and confirmed that the usability can be increased according to users become accustomed to this technique and that the users can enter PIN with 12.9 seconds and a probability of 100% on average. Also we conducted a security experiment and confirmed that an attack success rate is 0% when an attacker attacked the user using the recording attack and that it is more secure than the previous PIN entry technique. As a result, we was able to confirm that this technique can be used sufficiently.

• The Journal of the Korea Contents Association
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• v.8 no.8
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• pp.253-260
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• 2008

The research for a 3-axial accelerometer sensor has increased dramatically in the fields of cellular phone, PDA, etc. In this paper, we develop a human walking detection algorithm using 3-axial accelerometer sensor and a user interface system to show the activity expenditure in real-time. To measure a walking number more correctly in a variety of walking activities including walking, walking in place, running, slow walking, we propose a new walking number detection algorithm using adaptive threshold value. In addition, we calculate the activity expenditure base on counted walking number and display calculated activity expenditure on UI in real-time. From the experimental results, we could obtain that the detection rate of proposal algorithm is higher than that of existing algorithm using a fixed threshold value about $5{\sim}10%$. Especially, it could be found out high detection rate in walking in place.

• Korean Journal of Applied Biomechanics
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• v.18 no.4
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• pp.109-114
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• 2008

The purpose of this study was to estimate the energy expenditure simply and practically during physical activities. The physical activity is quantified by the integration of the accelerometer signals obtained from the triaxial accelerometer attached at the waist level of the human body. To find a relationship between energy expenditure and accelerometer data, 6 male and 5 female subjects walked and ran on the treadmill with speeds of 1.5, 3.0, 4.5, 6.0, 6.5, 7.0, and 8.5 km/hr. Each subject performed walking at the speed lower than 6.0 km/hr and running at the speed higher than 6.5 km/hr. Actual energy expenditure was determined by a continuous direct gas analyzer. Two predictive equations of walking and running mode for energy expenditure which includes gender, body mass index(BMI) and data from accelerometer were developed using multiple regression analysis. The correlation coefficients and coefficients of determination between the estimated and measured energy expenditure were R=0.936, R2=0.876 and R=0.881, R2=0.776 in walking and running mode, respectively. For further study, experiments on a larger scale of test subjects are essential for acquiring more reliable results.

• Journal of Korea Entertainment Industry Association
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• v.14 no.7
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• pp.511-518
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• 2020

The purpose of this study was to provide useful data for clinical occupational therapy by examining the correlation between the use of affected and unaffected sides measured using an accelerometer and upper limb function in chronic stroke patients. In this study, accelerometer, Fugle-Meyer Assessment(FMA), Motor Activity Log(MAL), and Yonsei-Bilateral Activity Test(Y-BAT) was measured on 40 stroke patients who were hospitalized in Won-ju city Y hospital between May 2, 2019 and July 18, 2020. As a result of the study, there was a significant negative correlation between amount of use on the unaffected side and FMA and MAL's Amount of Use(AOU), Quality of Movement(QOM), the quality and satisfaction of performing both hands through Y-BAT. The amount of use on the affected side showed a significant positive correlation with FMA and MAL's AOU, QOM, satisfaction of performing both hands. This study is meaningful in that it suggested the possibility that the actual amount of use on the affected and unaffected side measured using an accelerometer could be used as an evaluation item for upper limb function in stroke patients.

• The KIPS Transactions:PartD
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• v.18D no.2
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• pp.143-148
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• 2011

In this paper developed a wearable activity device and algorithm which can be converted into the real-time activity and monitoring by acquiring sensor row data to be occurred when a person is walking by using a tri-axial accelerometer. Test was proceeded at various step speeds such as slow walking, walking, fast walking, slow running, running and fast running, etc. for 36 minutes in accordance with the test protocol after wearing a metabolic test system(K4B2), Actical and the device developed in this study at the treadmill with 59 participants of subjects as its target. To measure the activity of human body, a regression equation estimating the Energy Expenditure(EE) was drawn by using data output from the accelerometer and information on subjects. As a result of experiment, the recognition rate of algorithm being proposed was shown the activity conversion algorithm was enhanced by 1.61% better than the performance of Actical.