• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.24 no.1
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• pp.81-88
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• 2011

A real time monitoring system from a PC has been developed which can be accessed through transmitted data, which incorporates an established low powered transport system equipped with a single chip combined with wireless sensor network technology from a three-axis acceleration sensor. In order to distinguish between static posture and dynamic posture, the extracted parameter from the rapidly transmitted data needs differentiation of movement and activity structures and status for an accurate measurement. When results interpret a static formation, statistics referring to each respective formation, known as the K-mean algorithm is utilized to carry out a determination of detailed positioning, and when results alter towards dynamic activity, fuzzy algorithm (fuzzy categorizer), which is the relationship between speed and ISVM, is used to categorize activity levels into 4 stages. Also, the ISVM is calculated with the instrumented acceleration speed on the running machine according to various speeds and its relationship with kinetic energy goes through correlation analysis. With the evaluation of the proposed system, the accuracy level stands at 100% at a static formation and also a 96.79% accuracy with kinetic energy and we can easily determine the energy consumption through the relationship between ISVM and kinetic energy.

• 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.

• Korean Journal of Applied Biomechanics
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• v.21 no.2
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• pp.253-258
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• 2011

The purpose of this study was to compare metabolic energy expenditure with the computed kinetic energy for different speeds of walking and running over the treadmill and to find the relevance for individual and group equation by performing a statistical analysis, Bland-Altman plot. Seven male subjects participated, and they were required to walk and run on the treadmill with the gas analyzer and triaxial accelerometer. Walking speeds were 3.0, 4.0, 5.0 and 6.0 km/h and running speeds were 7.0, 8.0 and 9.0 km/h respectively. Kinetic energy was calculated by the integration of acceleration data and compared with the metabolic energy measured by a gas analyzer. Correlation coefficients showed relatively good between the measured metabolic energy and the calculated kinetic energy. In addition, a dramatic increase in kinetic energy was also observed at the transition speed of walking and running, and two standard deviations in Bland-Altman plot, derived from the difference between measured and predicted values, were 1.14, 2.53, 2.93, 1.80, 2.80, 0.60 and 2.48 respectively. It was showed that there is no difference for methods of how to predict the kinetic energy expenditure for individual and group even though people had each different physical characteristic.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.3
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• pp.135-141
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• 2008

We propose a new method for recognizing the activities of daily living(ADL) based on the state-dependent motion analysis using 3-axial accelerometers and a glove type RFID reader. Two accelerometers are used for the classification of 5 body states based on the decision tree. Classification of the instrumental activities is performed based on the hand interaction with an object ID using an accelerometer and a RFID reader. Object-dependent hand movements are classified into 5 categories in advance and final decision combines the body state and the instrumental activities. Experiment shows that the suggested hierarchical motion analysis provides accuracy rate of over 90% for all 20 ADLs.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.9
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• pp.1557-1563
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• 2016

According to recent studies, poor sitting posture of the spine has been shown to lead to a variety of spinal disorders. For this reason, it is important to measure the sitting posture. We proposed a strategy for classification of sitting posture using machine learning. We retrieved acceleration data from single tri-axial accelerometer attached on the back of the subject's neck in 5-types of sitting posture. 6 subjects without any spinal disorder were participated in this experiment. Acceleration data were transformed to the feature vectors of principle component analysis. Support vector machine (SVM) and K-means clustering were used to classify sitting posture with the transformed feature vectors. To evaluate performance, we calculated the correct rate for each classification strategy. Although the correct rate of SVM in sitting back arch was lower than that of K-means clustering by 2.0%, SVM's correct rate was higher by 1.3%, 5.2%, 16.6%, 7.1% in a normal posture, sitting front arch, sitting cross-legged, sitting leaning right, respectively. In conclusion, the overall correction rates were 94.5% and 88.84% in SVM and K-means clustering respectively, which means that SVM have more advantage than K-means method for classification of sitting posture.

• 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.

• 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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1609-1613
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• 2003

This research focused on the development of automatically exclusive production equipment of corrupad as changing manual system into automatic system to increase the output. Therefore the minimization of the problem of the rewinding mechanism with eccentric cantilever structure is key to the achievement of the high performance for automation production. Proto-type corrupad rewinding machine is manufactured after considering the effect of the rotational vibration and natural frequency of the structure of machine by using 3D design packages such as ADAMS and I-deas. For evaluating the performance of the proto-type machine, simulations of dynamic and static characteristics using 3D design packages, a series of modal tests by accelerometer and measurements of dynamic behavior by high-speed camera for rewinding part, were carried out. As a result, the proto-type machine was not affected with the rotational vibration. Whirling error of eccentric cantilever structure in driving is small. Therefore the machine developed is most suitable to produce corrupad automatically. However reinforcement of the structure in axial direction is required due to so vibration in that direction.

• Smart Structures and Systems
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• v.12 no.6
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• pp.661-678
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• 2013

In this paper, a wireless sensing system for structural field evaluation and rating of bridges is presented. The system uses a wireless platform integrated with traditional analogue sensors including strain gages and accelerometers along with the operating software. A wireless vehicle position indicator is developed using a tri-axial accelerometer node that is mounted on the test vehicle, and was used for identifying the moving truck position during load testing. The developed software is capable of calculating the theoretical bridge rating factors based on AASHTO Load and Resistance Factor Rating specifications, and automatically produces the field adjustment factor through load testing data. The sensing system along with its application in bridge deck rating was successfully demonstrated on the Evansville Bridge in West Virginia. A finite element model was conducted for the test bridge, and was used to calculate the load distribution factors of the bridge deck after verifying its results using field data. A confirmation field test was conducted on the same bridge and its results varied by only 3% from the first test. The proposed wireless sensing system proved to be a reliable tool that overcomes multiple drawbacks of conventional wired sensing platforms designed for structural load evaluation of bridges.

• Journal of the Korean Wood Science and Technology
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• v.26 no.4
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• pp.26-33
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• 1998

Acoustical properties of chestnut and paulownia woods have been determined in four film thicknesses of oriental lacquering and cashew varnishing on double surfaces of soundboard to elucidate effects of finishing. Accelerometer was attached to the specimen at one third position from one end, and specimen was hit by the impact hammer at one third position from opposite end. Data were processed by vibration analyzer. The ratio of axial-to-transverse sound velocity of untreated specimens of chestnut and paulownia were 3.25 and 5.34, respectively. Natural frequency, specific Young's modulus, acoustical coefficient, sound velocity, damping of sound radiation(DSR) and acoustical converting efficiency(ACE) decreased by oriental lacquering and cashew varnishing for both species. Damping of internal friction of chestnut decreased by oriental lacquering and cashew varnishing, but that of paulownia increased. Natural frequency. specific Young's modulus, acoustical coefficient, sound velocity, and DSR decreased with increased film thickness of both finishing materials. However, damping of internal friction and ACE showed irregular tendency with increased film thickness. Acoustical properties of cashew varnished chestnut specimen were better than those of oriental lacquered specimen. Acoustical properties of oriental lacquered paulownia specimen were better than those of cashew varnished specimen.