• 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.

• The Journal of the Korea Contents Association
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• v.5 no.4
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• pp.94-102
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• 2005

In this paper, three axial accelerometer was used to develop a small sensor module, which was attached to human body to calculate the acceleration in gravity direction by human motion, when it was positioned in any direction. To measure its wearer's walking or running motion using the sensor module, the acquired sensor data was pre-processed to enable its quantitative analysis. The acquired digital data was transformed to orthogonal coordinate value in three dimension and calculated to be single scalar acceleration data in gravity direction and normalized to be physical unit value. The normalized sensor data was used to detect walking pattern and calculate their step counts. Developed algorithm was implemented in the form of PDA application. The accuracy of the developed sensor to detect step count was about 97% in laboratory experiment.

• 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.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.103-111
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• 2011

The research has increased the role of physical activity in promoting health and preventing chronic disease. Estimating algorithm of physical activity energy expenditure was implemented by using a tri-axial accelerometer motion detector of the SVM(Signal Vector Magnitude) of 3-axis(x, y, z). COUNT method has been proven through experiments of validity Freedson, Hendelman, Leenders, Yngve was implemented by applying the SVM method. A total of 10 participants(5 males and 5 females aged between 20 and 30 years). The activity protocol consisted of three types on treadmill; participants performed three treadmill activity at three speeds(3, 5, 8 km/h). These activities were repeated four weeks. Customized estimating algorithm for energy expenditure of physical activities were implemented with COUNT and SVM correlation between the data.

• Proceeding of KASS Symposium
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• 2008.05a
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• pp.184-188
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• 2008

Performance degradation of concrete structures is generally caused by structural deteriorations, such as cracks. It may result in serious defects of concrete structures. Methods of damage detection are used a visual angle of human or non-destructive test, and they are using various sensors. Problems of crack damage detection are occurred to directions of cracks by using 1 axial type of accelerometer in concrete element. In addition, these sensors are not used to occurring fire in RC building. Thermocouple sensors are able to using measurement of temperature in fire, and then deformations of main element and structures are not used. In this study, fundamental studies for development of multiple function sensor using 3 axial type of accelerometer and electric resistance property of thermocouple sensors are discussed estimation to stability of structures when happened form active load or fire, and so on.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.5
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• pp.1564-1572
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• 2010

In this study, the falls detection and direction classification system was implemented using 3-axial acceleration signal. The acceleration signals were acquired from the 3-axial accelerometer(MMA7260Q, Freescale, USA), and then transmitted to the computer through USB interface. The implemented system can detect falls using the newly proposed algorithm, and also classify the direction of falls using fuzzy classifier. The 6 subjects was selected for experiment and the accelerometer was attached on each subject's chest. Each subject walked in normal pace for 5 seconds, and then the fall down according to the four direction(front_fall, back_fall, left_fall and right_fall) during at least 2 second. The falls was easily detect using the newly proposed algorithm in this study. The acquired signals were analyzed after 1 second from generating falls. The fuzzy classifier was used to classify the direction of falls. The mean value of the falls detection rate was 94.79%. The classifier rate according to falls direction were 95.83% in case of front falls, 100% incase of back falls, 87.5% in case of left falls, and 95.83% in case of right falls.

• Korean Journal of Applied Biomechanics
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• v.18 no.2
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• pp.59-64
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• 2008

D. W. KANG, J. S. CHOI, and G. R. TACK, A Study on Real-Time Sports Activity Classification & Monitoring Using a Tri-axial Accelerometer. Korean Jouranl of Sport Biomechanics, Vol. 18, No. 2, pp. 59-64, 2008. This study was conducted to study the real-time sports activity classification and monitoring using single waist mounted tri-axial accelerometer. This monitoring system detects events of sports activities such as walking, running, cycling, transitions between movements, resting and emergency event of falls. Accelerometer module was developed small and easily attachable on waist using wireless communication system which does not constrain sports activities. The sensor signal was transferred to PC and each movement pattern was classified using the developed algorithm in real-time environment. To evaluate proposed algorithm, experiment was performed with several sports activities such as walking, running, cycling movement for 100sec each and falls, transition movements(sit to stand, lie to stand, stand to sit, lie to sit, stand to lie and sit to lie) for 20 times each with 5 healthy subjects. The results showed that successful detection rate of the system for all activities was 95.4%. In this study, through sports activity monitoring. it was possible to classify accurate sports activities and to notify emergency event such as falls. For further study, the accurate energy consumption algorithm for each sports activity is under development.

• Journal of IKEEE
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• v.22 no.4
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• pp.953-958
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• 2018

In this study, a portable detection system was developed that can detect harmful gas and signals simultaneously in an enclosed space of industrial sites and underground facilities. The developed system is a sensor module for gas detection, a patch type 1 channel small ECG sensor, a module for three-axial acceleration detection sensor, and a system for statistics. In order to verify the performance of the system modules, the digital resolution, signal frequency, output voltage, and ultra-small modules were evaluated. As a result of the performance of the developed system, the digital resolution was 300 (rps) and the signal amplification gain was 500 dB or more, and the ECG module was manufactured with $50mm{\times}10mm{\times}10mm$ to increase patch utilization. It is believed that the product of this research will be valuable if it is used as an IoT-based management system for real-time monitoring of industrial workers.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.10
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• pp.40-45
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• 2009

In this paper, we introduce a mobile-type tiny sensor device that can classify the activities of daily living based on the state-dependent motion analysis using a 3-axial accelerometer in real-time. The device consists of an accelerometer, GPS module, 32bit micro-controller for sensor data processing and activity classification, and a bluetooth module for wireless data communication. The size of device is 50*47*14(mm) and lasts about 10 hours in operation-mode and 160 hours in stand-by mode. Up to now, the device can recognize three user activities ("Upright", "Running", "Walking") based on the decision tree. This tree is constructed by the pre-learning process to activities of subjects. The accuracy rate of recognizing activities is over 90% for various subjects.

• The Journal of the Korea Contents Association
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• v.6 no.12
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• pp.96-104
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• 2006

In this study, data transmission ratio and power consumption issues of Zigbee based sensor module and personal digital assistant(PDA) were addressed to develop ECG telemetry device. PDA processes the data transmitted through serial port using non-blocking method. The transmission rate was dependent on the packet structure. It was 300 ECG samples/sec, when each packet was composed of 2 ECG data and 3-axial acceleration vector. Using two AAA batteries in series, operating time of the wireless sensor module was above 28 hours in average. Power consumption of PDA was dependent on screen ON/OFF condition and serial port usage. In this application, operating time of PDA was 5 hours in average. In conclusion, there was no problem in the power consumption of wireless sensor module and transmission rate, when the developed device was used as 24 hour Holter device. But, PDA has the problem of power consumption, which should be solved.