• Journal of the Korean Magnetics Society
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• v.20 no.3
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• pp.106-113
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• 2010

In order to get the precise blood pressure and pulse number in the cuffless status, the wrist wearable pulsimeter with a portable and small size apparatus using by Hall device is developed. The regression analysis of the pulse wave measured by the testing product of pulsimeter is conducted two equations of the blood pressure algorithm. The estimated values of blood pressure obtained by the cuffless pulsimeter during 5 s are compared with the practical values measured by electronic or mercury liquid blood pressure meters. The standard deviation of the estimated value and the practical value for the high blood pressure and the low blood pressure were 12.1 and 5.9, respectively, which have the neighborhood values of BP International Standard. The detail analysis of a pulse wave measured by cuffless wrist wearable detecting the changes of the magnetic field can be used to develop a new diagnostic algorithm of blood pressure applying for oriental medical apparatus like as the wrist wearable pulsimeter.

• ETRI Journal
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• v.29 no.3
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• pp.270-280
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• 2007

In Linux, real-time tasks are supported by separating real-time task priorities from non-real-time task priorities. However, this separation of priority ranges may not be effective when real-time tasks make the system calls that are taken care of by the kernel threads. Thus, Linux is considered a soft real-time system. Moreover, kernel threads are configured to have static priorities for throughputs. The static assignment of priorities to kernel threads causes trouble for real-time tasks when real-time tasks require kernel threads to be invoked to handle the system calls because kernel threads do not discriminate between real-time and non-real-time tasks. We present a dynamic kernel thread scheduling mechanism with weighted average priority inheritance protocol (PIP), a variation of the PIP. The scheduling algorithm assigns proper priorities to kernel threads at runtime by monitoring the activities of user-level real-time tasks. Experimental results show that the algorithms can greatly improve the unexpected execution latency of real-time tasks.

• Journal of electromagnetic engineering and science
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• v.13 no.1
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• pp.28-33
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• 2013

This paper proposes a miniaturized high-isolation diversity antenna for wearable wireless body area network (WBAN) applications. An inverted-F type radiating element is used to reduce the overall dimension of the proposed antenna to $30mm{\times}30mm{\times}2.5mm$. The antenna performance on the human body phantom is analyzed through simulation and the performance of the fabricated antenna is verified by comparing the measured data with that of the simulation when the antenna is placed on a semi-solid flat phantom with equivalent electrical properties of a human body. The fabricated antenna has a 10 dB return loss bandwidth over the Industrial Scientific Medical (ISM) band from 2.35 GHz to 2.71 GHz and isolation is higher than 28 dB at 2.45 GHz. The measured peak gain of antenna elements # 1 and # 2 is -0.43 dBi and -0.54 dBi, respectively. Performance parameters are analyzed, including envelope correlation coefficient (ECC), mean effective gain (MEG), and the MEG ratio. In addition, the specific absorption ratio (SAR) distributions of the proposed antenna are measured for consideration in use.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.6
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• pp.271-280
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• 2017

In this paper, we propose a new safety system composed of wearable devices, driver's seat belt, and integrating controllers. The wearable device and driver's seat belt capture driver's biological information, while the integrating controller analyzes captured signal to alarm the driver or directly control the car appropriately according to the status of the driver. Previous studies regarding driver's safety from driver's seat, steering wheel, or facial camera to capture driver's physiological signal and facial information had difficulties in gathering accurate and continuous signals because the sensors required the upright posture of the driver. Utilizing wearable sensors, however, our proposed system can obtain continuous and highly accurate signals compared to the previous researches. Our advanced wearable apparatus features a sensor that measures the heart rate, skin conductivity, and skin temperature and applies filters to eliminate the noise generated by the automobile. Moreover, the acceleration sensor and the gyro sensor in our wearable device enable the reduction of the measurement errors. Based on the collected bio-signals, the criteria for identifying the driver's condition were presented. The accredited certification body has verified that the devices has the accuracy of the level of medical care. The laboratory test and the real automobile test demonstrate that our proposed system is good for the measurement of the driver's condition.

• Journal of the HCI Society of Korea
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• v.11 no.3
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• pp.23-30
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• 2016

The landscape of the current fitness trackers is not only limited to the aerobic exercises but also the weight training is comparatively excluded. Recently, a few weight training fitness tracker was released, human-computer interaction was not well designed due to the lack of considering the context. Because body movement would be intense while doing exercises, having exercise performers hold or operate a device makes a negative experience. As the wearable device is always inseparable to body, it could provide effective feedback because holding or operating a device is not necessary. Therefore, this study aims to make the exercise performers feel a natural feedback through the wearable device to do effective exercises. As a result, this study identified three findings. First, the information which exercise performers most needed was 'during exercise.' and the most necessary information for exercise performers through wearable device's sensory feedback was about 'pace control' with counting and motivation. Second, the order of the most preferred presentation type of sensory feedback was auditory feedback, haptic feedback and visual feedback. Third, the satisfaction, utility, usefulness score of sensory feedback as same as the personal trainer's feedback. In conclusion, this study illustrated the feedback design implications using a wearable device while doing weight training and the possibilities that wearable device could be substitute for personal trainer.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.2
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• pp.67-74
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• 2017

This paper proposes a method of user authentication through the patterns of arm movement with a wrist-type wearable device. Using the accelerometer sensor which is built in the device, the 3-axis accelerometer data are collected. Then, the collected data are integrated and the periodic cycle are extracted. In the cycle, the features of frequency are generated with the accelerometer. With the frequency features, 2D Gaussian mixture are modelled. For authenticating an user, the data(the accelerometer) of the user at some point are tested with confidence interval of the Gaussian distribution. The model showed a valuable results for the user authentication with an example, which is average 92% accuracy with 95% confidence interval.

• Journal of Electrical Engineering and Technology
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• v.13 no.4
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• pp.1732-1739
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• 2018

With the explosion of digital devices, interaction technologies between human and devices are required more than ever. Especially, hand gesture recognition is advantageous in that it can be easily used. It is divided into the two groups: the contact sensor and the non-contact sensor. Compared with non-contact gesture recognition, the advantage of contact gesture recognition is that it is able to classify gestures that disappear from the sensor's sight. Also, since there is direct contacted with the user, relatively accurate information can be acquired. Electromyography (EMG) and force-sensitive resistors (FSRs) are the typical methods used for contact gesture recognition based on muscle activities. The sensors, however, are generally too sensitive to environmental disturbances such as electrical noises, electromagnetic signals and so on. In this paper, we propose a novel contact gesture recognition method based on Flexible Epidermal Tactile Sensor Array (FETSA) that is used to measure electrical signals according to movements of the wrist. To recognize gestures using FETSA, we extracted feature sets, and the gestures were subsequently classified using the support vector machine. The performance of the proposed gesture recognition method is very promising in comparison with two previous non-contact and contact gesture recognition studies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.1-15
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• 2019

Internet of Things (IoT) is commonly referred to as a future internet technology to provide advanced services by interconnecting physical and virtual things, collecting and using many data from them. The IoT platform is a server platform with a common architecture to collect and share the data independent of the IoT devices and services. Recently, oneM2M, the global standards initiative for Machine-to-Machine (M2M) communications and the IoT announced the availability of oneM2M Release 2 specifications. Accordingly, this paper presents a new oneM2M-compliant IoT platform called Mobius 2.0 and proposes its application to collect the biosignal data from wearable IoT devices for emotion recognition. Experimental results show that we can collect various biosignal data seamlessly and extract meaningful features from the biosignal data to recognize two emotions of joy and sadness.

• Journal of Korea Multimedia Society
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• v.25 no.9
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• pp.1251-1256
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• 2022

Auscultation of heart sounds using a stethoscope is the basic method to diagnose the cardiovascular disease and observation of abnormalities. However, the heart sound transmitted to the ear through the stethoscope is greatly affected by internal sounds such as organ movement or breathing. In addition, the user's experience significantly influences the accuracy of the auscultation result. Therefore, in this paper, we developed a wearable device that simultaneously measures heart sound and PPG signals for cardiac condition monitoring. The structure of the proposed device is designed to simultaneously measure heart sound and PPG signals when worn on a finger and placed on the chest. A prototype was implemented according to the design structure, and it was confirmed that the performance of measurements and collection for physiological signals was excellent through experiments.

• Journal of IKEEE
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• v.23 no.3
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• pp.1104-1107
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• 2019

This paper proposes a DC-DC boost converter for wearable AMOLED display using dead time controller to reduce dead time and improve power efficiency. Also the DC-DC boost converter adopts PWM-SPWM (set-time variable pulse width modulation) dual-mode to enhance power efficiency under light load and decrease output voltage ripple. The proposed circuit has been designed using $0.18{\mu}m$ BCDMOS process. Simulation results show that the circuit has power efficiency of 39%~96% and output ripple voltage of 2 mV under load current range of 1 mA~70 mA. The power efficiency of the proposed circuit is up to 2% higher than the previous PWM-SPWM method and up to 8% higher than only PWM method.