• Korean Journal of Computational Design and Engineering
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• v.19 no.2
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• pp.157-168
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• 2014

In this paper, HSE (Health and Safety Environments) research with smart device and biometrics is conducted for the worker's HSE enhancement in the manufacturing shop floor. Today, various kinds of smart devices are popularized extensively. In addition, the wearable type devices are being introduced such as google glass very recently. Smart device of werable type is exptected to bring great opportunity out in terms of HSE functionality. Smart devices of phone or tablet type are being used for on-line work between control center and manufacturing shop floor by virtue of wireless communication. However, those devices are not appropriate for detecting of worker's physical senses such as temperature and pulse. In this paper, we developed a glass type smart device and required funictions for HSE enhancement with the investigation of biometrics technology. Also, required sensors are investigated for the detecting of temperature, pulse and noxious gasses. Smart device of glass type has advantages in that most senses of personnel are gathered around faces, and also it's possible to detect neutral axis of body because the wearing location is fixed. We expect that the proposing HSE product of glass type smart device could contribute the enhancement of the HSE of manufacturing shop floor.

• Journal of the Ergonomics Society of Korea
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• v.29 no.3
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• pp.357-364
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• 2010

This study proposes a lower-limb exoskeleton system that is controlled by a wearer's muscle activity. This system is designed by following procedure. First, analyze the muscle activation patterns of human leg while walking. Second, select the adequate actuator to support the human walking based on calculation of required force of knee joint for step walking. Third, unit type knee and ankle orthotics are integrated with selected actuator. Finally, using this knee-assistive system (KAS) and developed muscle stiffness sensors (MSS), the muscle activity pattern of the subject is analyzed while he is walking on the stair. This study proposes an operating algorithm of KAS based on command signal of MSS which is generated by motion intent of human. A healthy and normal subject walked while wearing the developed powered-knee exoskeleton on his/her knees, and measured effectively assisted plantar flexor strength of the subject's knees and those neighboring muscles. Finally, capabilities and feasibility of the KAS are evaluated by testing the adapted motor pattern and the EMG signal variance while walking with exoskeleton. These results shows that developed exoskeleton which controlled by muscle activity could help human's walking acceptably.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2377-2397
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• 2020

Human activity recognition is widely used in smart homes, health care and indoor monitor. Traditional approaches all need hardware installation or wearable sensors, which incurs additional costs and imposes many restrictions on usage. Therefore, this paper presents a novel device-free activities recognition system based on the advanced wireless technologies. The fine-grained information channel state information (CSI) in the wireless channel is employed as the indicator of human activities. To improve accuracy, both amplitude and phase information of CSI are extracted and shaped into feature vectors for activities recognition. In addition, we discuss the classification accuracy of different features and select the most stable features for feature matrix. Our experimental evaluation in two laboratories of different size demonstrates that the proposed scheme can achieve an average accuracy over 95% and 90% in different scenarios.

• Journal of Sensor Science and Technology
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• v.29 no.1
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• pp.19-26
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• 2020

Electrocardiogram (ECG) classification has become an essential task of modern day wearable devices, and can be used to detect cardiovascular diseases. State-of-the-art Artificial Intelligence (AI)-based ECG classifiers have been designed using various artificial neural networks (ANNs). Despite their high accuracy, ANNs require significant computational resources and power. Herein, three different ANNs have been compared: multilayer perceptron (MLP), convolutional neural network (CNN), and spiking neural network (SNN) only for the ECG classification. The ANN model has been developed in Python and Theano, trained on a central processing unit (CPU) platform, and deployed on a PYNQ-Z2 FPGA board to validate the model using a Jupyter notebook. Meanwhile, the hardware accelerator is designed with Overlay, which is a hardware library on PYNQ. For classification, the MIT-BIH dataset obtained from the Physionet library is used. The resulting ANN system can accurately classify four ECG types: normal, atrial premature contraction, left bundle branch block, and premature ventricular contraction. The performance of the ECG classifier models is evaluated based on accuracy and power. Among the three AI algorithms, the SNN requires the lowest power consumption of 0.226 W on-chip, followed by MLP (1.677 W), and CNN (2.266 W). However, the highest accuracy is achieved by the CNN (95%), followed by MLP (76%) and SNN (90%).

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.2
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• pp.91-102
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• 2017

Backpack-mounted mapping system is firstly introduced for flexible movement in indoor spaces where satellite-based localization is not available. With the achieved advances in miniaturization and weight reduction, use of LiDAR (Light Detection and Ranging) sensors in mobile platforms has been increasing, and indeed, they have provided high-precision information on indoor environments and their surroundings. Previous research on the development of backpack-mounted mapping systems, has concentrated mostly on the improvement of data processing methods or algorithms, whereas practical system components have been determined empirically. Thus, in the present study, a simulator for a LiDAR sensor (Velodyne VLP-16), was developed for comparison of the effects of diverse conditions on the backpack system and its operation. The simulated data was analyzed by visual inspection and comparison of the data sets' statistics, which differed according to the LiDAR arrangement and moving speed. Also, the data was used as input to a point-cloud registration algorithm, ICP (Iterative Closest Point), to validate its applicability as pre-analysis data. In fact, the results indicated centimeter-level accuracy, thus demonstrating the potentials of simulation data to be utilized as a tool for performance comparison of pointdata processing methods.

• Journal of Sensor Science and Technology
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• v.26 no.4
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• pp.239-244
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• 2017

Noninvasive, cuffless, and continuous blood pressure (BP) monitoring is essential to prevent and control hypertension. A well-known existing method for this measurement is pulse transit time (PTT), which has been investigated by many researchers as a promising approach. However, the fundamental principle of the PTT method is based on the time interval taken by a pulse wave to propagate between the proximal and distal arterial sites. Consequently, this method needs an independent system with two devices placed at two different sites, which is a problem. Even though some studies attempted to synchronize the system, it is bulky and inconvenient by contemporary standards. To find a more sensitive method to be used in a BP measurement device, this study used radial electrical bioimpedance (REB) as a potential indicator for BP determination. Only one impedance plethysmography channel at the wrist is performed for demonstrating a ubiquitous BP wearable device. The experiment was evaluated on eight healthy subjects with the ambulatory BP monitor on the upper arm as a reference. The results demonstrated the potential of the proposed method by the correlation of estimated systolic (SBP) and diastolic (DBP) BP against the reference at $0.84{\pm}0.05$ and $0.83{\pm}0.05$, respectively. REB also tracked the DBP well with a root-mean-squared-error of $7.5{\pm}1.35mmHg$.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.947-948
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• 2015

IOT(Internet of things) is a technology to embed various sensors and communication features on diverse things such as home appliances, mobile devices, wearable computers and connect to the Internet and through this technology, the status of things connected to the network can be analyzed and controlled with various data. On the other hand, this paper suggests to develop a merchandise management app using Android-based barcode to systematically manage expiry date of various goods that we purchase in our daily life. Therefore, individual goods are recognized with mobile-based barcode and divided under each category. By additionally supporting the notification service to let us know about expire date, goods can be efficiently managed.

• Journal of Sensor Science and Technology
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• v.20 no.2
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• pp.118-123
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• 2011

Heart related diseases mainly caused by heavy work load and increasing stress in human daily life. Therefore, researches on mobile healthcare monitoring for daily life has been carried out. Notably, wearable healthcare monitoring system which has least restriction has been tried to provide an emergency alert of abnormal heart rate. In this study, we developed chair type unconstrained BCG measurement system which able to perform continuous heart status monitoring at the office and daily life in the unconstrained way. Furthermore, adaptive threshold is used to detect the heart rate from BCG signals. The HRV(heart rate variability) is calculated from heart rate interval. ECG signal measured using conventional method and BCG signal measured using unconstraint system are carried out simultaneously for the purpose of performance evaluation. From the comparison result, BCG signal shows a similar heart beat characteristic as ECG signal. This proves the possibility of practical implementation of unconstraint healthcare monitoring system. In addition, medical examination like valsalva maneuver is performed to observe the changes in HRV due to stress. By performing valsalva maneuver, heart is said to be placed under an artificial physical stress condition. Under this artificial physical stress condition, the time and frequency domain of HRV parameters are evaluated.

• Journal of Sensor Science and Technology
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• v.19 no.3
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• pp.209-213
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• 2010

This paper describes the fabrication and characteristics of AlN piezoelectric MPG(micro power generator). The micro energy harvester was fabricated to convert ambient vibration energy to electrical power as a AlN piezoelectric cantilever with Si proof-mass. To be compatible with CMOS process, AlN thin film was grown at low temperature by RF magnetron sputtering and micro power generators were fabricated by MEMS technologies. X-ray diffraction pattern proved that the grown AlN film had highly(002) orientation with low value of FWHM(full width at the half maximum, $\theta=0.276^{\circ}$) in the rocking curve around(002) reflections. The implemented harvester showed the $198.5\;{\mu}m$ highest membrane displacement and generated 6.4 nW of electrical power to $80\;k{\Omega}$ resistive load with $22.6\;mV_{rms}$ voltage from 1.0 G acceleration at its resonant frequency of 389 Hz. From these results, the AlN piezoelectric MPG will be possible to suitable with the batch process and confirm the possibility for power supply in portable, mobile and wearable microsystems.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.145-146
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• 2010

This paper proposed a new concept of global healthcare system based on M2M technology with the combination of networks by using IPv6 techniques. The proposed system consists of 6LoWPAN based wearable sensors, gateway for the connection of different networks, and server program offering health information. Thus our approach presents an intelligent system which allows direct exchange of information between machines without human assistance with the epoch-making extension of measurement environment in healthcare areas appropriately.