• Journal of Korea Game Society
• /
• v.13 no.5
• /
• pp.73-80
• /
• 2013

NUI(Natural User Interface) allows users to directly interact with surrounding digital devices using their voices or body motions without additional input/output interface devices. Our study has been carried out on human users who play a tangible game with body motions in the NUI-applied smart space. ECG was measured for 60 seconds duration before and after playing the game to determine user stress levels, and the measured signals were analyzed through an improved Random Forest algorithm. In order to experiment by a supervised learning, users additionally input whether or not the user felt stress. Moreover, the improved algorithm showed 1.04% higher accuracy than existing algorithm.

• The Journal of the Korea Contents Association
• /
• v.11 no.12
• /
• pp.619-628
• /
• 2011

Normally vision-based 3D human pose recognition technology is used to method for convey human gesture in HCI(Human-Computer Interaction). 2D pose model based recognition method recognizes simple 2D human pose in particular environment. On the other hand, 3D pose model which describes 3D human body skeletal structure can recognize more complex 3D pose than 2D pose model in because it can use joint angle and shape information of body part. In this paper, we describe a development of interactive game contents using pose recognition interface that using 3D human body joint information. Our system was proposed for the purpose that users can control the game contents with body motion without any additional equipment. Poses are recognized comparing current input pose and predefined pose template which is consist of 14 human body joint 3D information. We implement the game contents with the our pose recognition system and make sure about the efficiency of our proposed system. In the future, we will improve the system that can be recognized poses in various environments robustly.

• Journal of Multimedia Information System
• /
• v.2 no.3
• /
• pp.275-280
• /
• 2015

Recently brainwaves are utilized diversely in the field of medicine, entertainment, education and so on. In the case of medicine, brainwaves are analyzed to estimate patients' diseases. However, the applications for entertainments usually utilize brainwaves as control signal without figuring out the characters of the brainwaves. Given that users' brainwaves are different each other, a normalization method is essential. The traditional brainwave normalization approaches utilize normal distribution. However, those approaches assume that brainwaves are collected enough to conduct normal distribution. When the few amounts of brainwaves are measured, the accuracy of the control signal based on the measured brainwaves becomes low. In this paper, we propose a normalization framework of BCI-based facial interfaces for novel volume controllers, which can normalizes the few amounts of brainwaves and then generates the control signals of BCI-based facial interfaces. In the experiments, two subjects were involved to validate the proposed framework and then the normalization processes were introduced.

• Proceedings of the Korean Information Science Society Conference
• /
• 2005.11b
• /
• pp.490-492
• /
• 2005

최근 사용자 행태 분석 개념이 매우 중요한 이슈가 되고 있으며, HCI(Human-Computer Interface)의 관점에서 사용자의 행태와 시스템 모델링은 적절한 모델링 언어나 도구가 부족하여 사용자의 행태를 전부 표현하지 못한다. 소프트웨어공학에서는 시스템을 설계하기 위해 UML(Unified Modeling Language)을 사용하여 시스템을 모델링하고 있다. 물론 UML에 액터 개념은 있으나 시스템 중심의 모델에 초점을 두고 있어, 사용자의 행태 표현에 제약이 존재한다. 이에 본 논문에서는 사용자 행태를 모델링하기위해 OBA(Object Behavior Analysis)방법론을 기반으로 사용자 행태에 초점을 맞춰 시스템을 모델링 하고, 결과로써 HCI관점을 위해 부족한 UML의 문제와 확장성을 언급하고자 한다.

• Annual Conference on Human and Language Technology
• /
• 1994.11a
• /
• pp.483-492
• /
• 1994

고속 통신망의 발달은 CSCW의 연구를 초래했다. 본 연구에서는 CSCW를 위한 다중 사용자용 인터페이스를 지원하는 한글 에이전트 설계에 대하여 설명한다. 본 연구의 다중 사용자용 인터페이스는 우리 글인 "한글" 사용자의 개념적 모델과 객체지향 프로그래밍 언어에 의하여 지원 받는 구조 사이에서의 동질 구조를 갖도록 한다. 즉, 한글 에이전트는 인터페이스를 공유할 수 있도록 하여 모든 데이타를 개념적 모델에 의한 객체로 동시, 공유 처리한다. 본 연구의 한글 에이전트는 객체지향 방법으로 설계되어 인간의 개념 모델에 더욱 가까운 공동작업 환경을 제시함으로써, 원격지 회의, 실시간 강의 시스템 등에 응용된다.

• Proceedings of the KSPS conference
• /
• 2006.05a
• /
• pp.135-138
• /
• 2006

The communication method between human and robot is one of the important parts for a human-robot interaction. And speech is easy and intuitive communication method for human-being. By using speech as a communication method for robot, we can use robot as familiar way. In this paper, we developed TTS for human-robot interaction. Synthesis algorithms were modified for an efficient utilization of restricted resource in robot. And synthesis database were reconstructed for an efficiency. As a result, we could reduce the computation time with slight degradation of the speech quality.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2011.07a
• /
• pp.490-493
• /
• 2011

최근 사용자와 컴퓨터간의 상호작용이 가능한 사용자 인터페이스(UI, User Interface)에 대한 연구가 활발히 진행되고 있다. 이중 키보드나 마우스, 리모컨과 같은 별도의 입력장치가 없이 뇌의 활동으로부터 발생하는 생체신호를 이용하여 사용자의 생각만으로 컴퓨터와 커뮤니케이션을 할 수 있는 뇌만으로 컴퓨터와 커(BCI, Brain-Computer Interface) 시스템이 각광을 받고 있다. 본 연구에서는 뇌의 생체신호로는 뇌전도도(EEG, Electroencephalogram)를 사용하였으며, 이를 통하여 P300 speller 실험을 수행하였다. P300 speller 실험을 통하여 발생된 뇌전도도를 취합하여 P300(사건 관련 전위(ERP, Event-related potential)에서 자극 제시 약 300msec 후에 정점에 달하는 정파)을 분석하였다.

• Journal of the Ergonomics Society of Korea
• /
• v.29 no.6
• /
• pp.907-914
• /
• 2010

Cognitive model, that is cognitive architecture, is the model expressed with computer program to show the process how human solve a certain problem and it is continuously under investigation through various fields of study such as cognitive engineering, computer engineering, and cognitive psychology. In addition, the much extensive applicability of cognitive model usually helps it to be used for quantitative prediction of human Behavior or Natural programming of human performance in many HCI areas including User Interface Usability, artificial intelligence, natural programming language and also Robot engineering. Meanwhile, when a system designed, an usability test about conceptual design of interface is needed and in this case, analysis evaluation using cognitive model like GOMS or ACT-R is much more effective than empirical evaluation which naturally needs products and subjects. In particular, if we consider the recent trend of very short-end term between a previous technology development and the next new one, it would take time and much efforts to choose subjects and train them in order to conduct usability test which is repeatedly followed in the process of a system development and this finally would bring delays of development of a new system. In this study, we predicted quantitatively the human behavior processes which contains cognitive processes for menu selection in touch screen interface through ACT-R, one of the common method of usability test. Throughout the study, it was shown that the result using cognitive model was equal with the result using existing empirical evaluation. And it is expected that cognitive model has a possibility not only to be used as an effective methodology for evaluation of HCI products or system but also to contribute the activation of HCI cognitive modeling in Korea.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2001.04a
• /
• pp.182-187
• /
• 2001

This study deals with CARS (Computer Aided ROMUM System) which is a computer version of ROMUM (RObot Modularization of the Unit Motion). ROMUM was a method developed by the concept of modularization of the unit motion of robots. Because CARS is a computer assisted method of menu-driven type for human interface, this method can be easily applied for analyzing the work motion and measuring the execution time of robots. Therefore, it will be helpful for reducing the analysis effort and time of robot work.

• Proceedings of the Korean Information Science Society Conference
• /
• 2002.10d
• /
• pp.232-234
• /
• 2002

EEG-based brain computer interface (BCI) provides a new communication channel between human brain and computer. The classification of EEG data is an important task in EEG-based BCI. In this paper we present methods which jointly employ principal component analysis (PCA) and linear dynamical system (LDS) modeling for the task of EEG classification. Experimental study for the classification of EEG data during imagination of a left or right hand movement confirms the validity of our proposed methods.