• Journal of Sensor Science and Technology
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• v.21 no.4
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• pp.241-248
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• 2012

Recently healthcare industry such as pharmaceutical, medical device and healthcare service technology is growing significantly. Mobile healthcare has attracted big attention due to IT convergence technology. Paradigm of healthcare has been changed from the 1st generation(communicable disease prevention) and the 2nd generation(treatment of disease due to extended life expectancy) to the 3rd generation(extended life expectancy due to prevention and control). In our study, we suggest the 3rd generation mobile healthcare system using Bluetooth based wearable ECG monitoring system and smart phone technology. The mobile healthcare system consists of wearable shirts with Bluetooth communication module, ECG sensor, battery, and mobile phone. The ECG data is obtained by a miniaturized sensor and the data is transferred to a mobile phone using Bluetooth communication. Then, user can monitor his/her own ECG signal on an application using Android in mobile phone. The Bluetooth communication device is used due to highly reliable data transmission property and the Bluetooth chip is embedded in every mobile phone. The wearable shirts with chest belt of Bluetooth ECG module is designed with a focus on convenience in the daily life of a wearer. The ECG signal evaluation software in Android based mobile phone is developed for the health check and the ECG signal variation is tested according to the activities of the wearer such as walking, climbing stairs, stand up and sit down, and so on.

• Journal of the HCI Society of Korea
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• v.1 no.1
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• pp.29-36
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• 2006

Tactile displays can provide useful information without disturbing others and are particularly useful for people with visual or auditory impairments. They can also complement other displays. In this paper, we present a new vibrotactile display device for wearable, mobile, and ubiquitous computing environments. The proposed vibrotactile device has a $5{\times}5$ array configuration for displaying complex information such as letters, numbers, and haptic patterns as well as simple directional ques and situation awareness alarms. Commercially available coin-type vibration motors are embedded vertically in flexible mounting pads in order to best localize vibrations on the skin. An embedded microprocessor controls the motors sequentially with an advanced tracing mode to increase recognition rate. User studies with the vibrotactile device on the top of the foot show 86.7% recognition rate for alphabet characters after some training. In addition, applying vibrotactile device to driving situation shows 83.9% recognition rate. We also propose some potentially useful application scenarios including Caller Identification for mobile phones and Navigation Aids for GPS systems while driving.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.2
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• pp.43-50
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• 2018

Biometric information computing is greatly influencing both a computing system and Big-data system based on the bio-information system that combines bio-signal sensors and bio-information processing. Unlike conventional data formats such as text, images, and videos, biometric information is represented by text-based values that give meaning to a bio-signal, important event moments are stored in an image format, a complex data format such as a video format is constructed for data prediction and analysis through time series analysis. Such a complex data structure may be separately requested by text, image, video format depending on characteristics of data required by individual biometric information application services, or may request complex data formats simultaneously depending on the situation. Since previous bio-information processing computing systems depend on conventional computing component, computing structure, and data processing method, they have many inefficiencies in terms of data processing performance, transmission capability, storage efficiency, and system safety. In this study, we propose an improved biosensing converged big data computing architecture to build a platform that supports biometric information processing computing effectively. The proposed architecture effectively supports data storage and transmission efficiency, computing performance, and system stability. And, it can lay the foundation for system implementation and biometric information service optimization optimized for future biometric information computing.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.182-187
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• 2006

유비쿼터스 컴퓨팅이 차세대 IT 패러다임으로 자리매김하면서 유비쿼터스 서비스 개발이 경쟁적으로 이루어지고 있다. 그러나 이에 일반적으로 사용되는 시나리오 기반 개발 공정은 유비쿼터스 서비스 개발에 필요한 여러 요구사항들을 채워주기 힘들다. 따라서 본 논문에서는 유비쿼터스 서비스 개발을 위해 시나리오 기반 접근법을 바탕으로 시나리오를 계층적으로 분석하고 이로부터 기술적 요구 사항을 도출하는 방법론을 제시한다. 그리고 이 방법론을 유비쿼터스 패셔너블 컴퓨터(UFC) 프로젝트에 실제 적용하였다. 착용형 컴퓨터를 입은 사용자가 유비쿼터스 컴퓨팅 환경 하에서 받을 수 있는 다양한 서비스 프로토타입을 구현하였다. 그 결과 유비쿼터스 회의 시나리오 상에서 필요한 여러 서비스들을 효과적으로 개발할 수 있었다.

• ETRI Journal
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• v.29 no.3
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• pp.281-291
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• 2007

Wearable computers consisting of various small devices such as smart phones, digital cameras, MP3 players and specialized I/O devices in personal area networks will play an important role in future ubiquitous computing. In this environment, accessing user data is quite complex due to the dynamic and heterogeneous characteristics of the underlying networks. Moreover, since the amount of user data increases rapidly, automatic data backup management is also critical. To overcome these challenges, several studies have been conducted including our previously proposed file service system, PosCFS, which could be adapted to the requirements with a virtualization technique allowing per-user global namespace for managing and accessing data stored on physical storage spaces detected in PAN. In this paper, we present a smart file service framework, PosCFS+ which is an improved and extended version of our previous work. Performance improvement is made possible by redesigning the metadata management scheme based on database and keywords rather than ontology. In addition, the automatic data replication management is newly designed based on the OSD protocol.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.2
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• pp.247-258
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• 2003

In this paper, we present a pen-shaped input device equipped with accelerometers and gyroscopes that measure inertial movements when a user writes on 2 or 3 dimensional space with the pen. The measurements from gyroscope are integrated once to find the attitude of the system and are used to compensate gravitational effect in the accelerations. Further, the compensated accelerations are integrated twice to yield the position of the system, whose basic concept stems from the field of inertial navigation. However, the accuracy of the position measurement significantly deteriorates with time due to the integrations involved in recovering the handwriting trajectory This problem is common in the inertial navigation system and is usually solved by the periodic or aperiodic calibration of the system with external reference sources or other information in the filed of inertial navigation. In the presented paper, the calibration of the position or velocity is performed on-line and off-line. In the on-line calibration stage, the complementary filter technique is used, where a Kalman filter plays an important role. In the off-line calibration stage, the constant component of the resultant navigational error of the system is removed using the velocity information and motion detection algorithm. The effectiveness and feasibility of the presented system is shown through the experimental results.

• Journal of the Korea Society of Computer and Information
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• v.22 no.2
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• pp.9-19
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• 2017

Useful continuous sensing applications are increasingly emerging as a new class of mobile applications. Meanwhile, open, multi-use sensor devices are newly adopted beyond smartphones, and provide huge opportunities to expand potential application categories. In this upcoming environment, uncoordinated use of sensor devices would cause severe imbalance in power consumption of devices, and thus result in early shutdown of some sensing applications depending on power-hungry devices. In this paper, we propose EnergyCordy, a novel inter-device energy use coordination system; with a system-wide holistic view, it coordinates the energy use of concurrent sensing applications over multiple sensor devices. As its key approach, we propose a relaxed sensor association; it decouples the energy use of an application from specific sensor devices leveraging multiple context inference alternatives, allowing flexible energy coordination at runtime. We demonstrated the effectiveness of EnergyCordy by developing multiple example applications over custom-designed wearable senor devices. We show that EnergyCordy effectively coordinates the power usage of concurrent sensing applications over multiple devices and prevent undesired early shutdown of applications.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.2
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• pp.129-132
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• 2017

A conventional pulse oximeter has high power consumption; thus, its mobility is severely limited. In this paper, we discuss the drawbacks of the existing pulse oximeters and propose a new ultra-low-power pulse oximeter that supports wireless data transmission for remotely monitoring vital signs, such as peripheral capillary oxygen saturation (SpO2) and beats per minute (BPM). We could notably reduce power consumption by using a low-frequency single clock in all well-customized modules. Also, our device is publicly certified, and thus, possibly engaged in clinical trials for commercial use.

• Journal of the Korean Society of Safety
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• v.30 no.3
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• pp.93-99
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• 2015

Economic burden of work-related musculoskeletal disorder(WMDs) is increasing. Known causes of WMDs include improper posture, repetition, load, and temperature of workplace. Among them, improper postures play an important role. A smart sensor called SensorTag is employed to estimate the trunk postures including flexion-extension, lateral bend, and the trunk rotational speeds. Measuring gravitational acceleration vector in the smart sensor along the tri-orthogonal axes offers an orientation of the object with the smart sensor attached to. The smart sensor is light in weight and has small form factor, making it an ideal wearable sensor for body posture measurement. Measured data from the smart senor is wirelessly transferred for analysis to a smartphone which has enough computing power, data storage and internet-connectivity, removing need for additional hardware for data post-processing. Based on the estimated body postures, WMDs risks can be conviently gauged by using existing WMDs risk assesment methods such as OWAS, RULA, REBA, etc.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.9
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• pp.1363-1368
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• 2015

Recently, computer form were smaller than before because of computing technique's development and many wearable device are formed. So, computer's cognition of human emotion has importantly considered, thus researches on analyzing the state of emotion are increasing. Human voice includes many information of human emotion. This paper proposes a discriminative feature vector selection for emotion classification based on speech. For this, we extract some feature vectors like Pitch, MFCC, LPC, LPCC from voice signals are divided into four emotion parts on happy, normal, sad, angry and compare a separability of the extracted feature vectors using Bhattacharyya distance. So more effective feature vectors are recommended for emotion classification.