• Journal of Korean Gerontological Nursing
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• v.20 no.sup1
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• pp.144-153
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• 2018

Purpose: The purpose of this study was to review the influence of robot systems on nursing and robotics technology. Methods: The research design was a review article. The literature was done to help understand the current status and effects of robotic technology in the healthcare field, both domestic and overseas. The keywords searched were 'Nursing', 'Robot', and 'Patient safety' in Pubmed, CINAHL etc, and 'Nursing Activity', 'Nursing Care Integration Service' in RISS and KISS. Results: In healthcare, robotics is used in five areas; personal care robots, mobility and transfer robots, cognitive and emotional robots, nursing assist robots and care robots in palliative home care settings. Nurses' demands for utilization of robotic systems are high. Especially, if robotics is used for indirect and non-value-added nursing activities, efficiency may increase. Therefore, robotics should be used to help nurses focus on bedside care and perform better nursing care. Conclusion: Future robots and technology can help nurse to provide optimal nursing to patients, and will improve the quality life of patients. It is suggested that nursing research should be actively pursued in the future. Especially, it is an urgent field to improve nursing quality and reduce the burden of nurses.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.562-567
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• 2009

As a key mechanism of the human emotion interaction, Facial Expression is a powerful tools in HRI(Human Robot Interface) such as Human Computer Interface. By using a facial expression, we can bring out various reaction correspond to emotional state of user in HCI(Human Computer Interaction). Also it can infer that suitable services to supply user from service agents such as intelligent robot. In this article, We addresses the issue of expressive face modeling using an advanced active appearance model for facial emotion recognition. We consider the six universal emotional categories that are defined by Ekman. In human face, emotions are most widely represented with eyes and mouth expression. If we want to recognize the human's emotion from this facial image, we need to extract feature points such as Action Unit(AU) of Ekman. Active Appearance Model (AAM) is one of the commonly used methods for facial feature extraction and it can be applied to construct AU. Regarding the traditional AAM depends on the setting of the initial parameters of the model and this paper introduces a facial emotion recognizing method based on which is combined Advanced AAM with Bayesian Network. Firstly, we obtain the reconstructive parameters of the new gray-scale image by sample-based learning and use them to reconstruct the shape and texture of the new image and calculate the initial parameters of the AAM by the reconstructed facial model. Then reduce the distance error between the model and the target contour by adjusting the parameters of the model. Finally get the model which is matched with the facial feature outline after several iterations and use them to recognize the facial emotion by using Bayesian Network.

• The Journal of the Korea Contents Association
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• v.10 no.6
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• pp.286-296
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• 2010

The study of the development of DJ robots is to meet the demands of the music services which are changing very rapidly in the digital and network era. Existing studies, as a whole, develop music services on the premise of personalized environment and equipment, but the DJ robot is on the premise of the open space shared by the public. DJ robot gives priority to traditional space and music. Recently as the hospitality and demand for cultural contents of South Korea expand to worldwide, industrial use of the contents based on traditional or our unique characteristics is getting more and more. Meanwhile, the DJ robot is composed of a combination of two modules. One is to detect changes in the external environment and the other is to set the properties of the music by psychology, emotional engineering, etc. DJ robot detect the footprint of the temperature, humidity, illumination, wind, noise and other environmental factors measured, and will ensure the objectivity of the music source by repeated experiments and verification with human sensibility ergonomics based on Hevner Adjective Circle. DJ robot will change the soundscape of the traditional space being more beautiful and make the revival and prosperity of traditional music with the use of traditional music through BGM.

• Journal of KIISE:Software and Applications
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• v.34 no.10
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• pp.910-917
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• 2007

Of the possible interactions between human and robot, touch is an important means of providing human beings with emotional relief. However, most previous studies have focused on interactions based on voice and images. In this paper. a method of recognizing human touching behaviors is proposed for developing a robot that can naturally interact with humans through touch. In this method, the recognition process is divided into pre-process and recognition Phases. In the Pre-Process Phase, recognizable characteristics are calculated from the data generated by the touch detector which was fabricated using force sensors. The force sensor used an FSR (force sensing register). The recognition phase classifies human touching behaviors using a multi-layer perceptron which is a neural network model. Experimental data was generated by six men employing three types of human touching behaviors including 'hitting', 'stroking' and 'tickling'. As the experimental result of a recognizer being generated for each user and being evaluated as cross-validation, the average recognition rate was 82.9% while the result of a single recognizer for all users showed a 74.5% average recognition rate.

• Journal of Engineering Education Research
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• v.11 no.4
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• pp.19-33
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• 2008

The purpose of this study is to find out the effects of the use of Chatting Method(with AI Chatting robot: Chatterbot) and Computer Interest Levels on Teaching & Learning. The major findings of the study are as follows. Firstly, the chatting activities using the chatterbot method and computer Interest Levels were not effective in the academic achievement. Secondly, the chatting activities using the chatterbot method and computer Interest Levels were effective in improving the learning motivation. Thirdly, According to the result of post-feedback analysis, the benefits of chatterbot method was 'the new', 'transcends time and space', 'drill and practice learning' and was some of the drawbacks 'response fixed', lack of emotional transactions. and the proposal 'PBL' was reached(1. strength: new experience, 2. weakness: be tired, 3. proposal: PBL approach). Fourthly, the relationship between the academic achievement, learning motivation, post-feedback was no correlation. Based on these results, the study suggests that the chatterbot method was need for multiple instructional design strategy.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.129-149
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• 2021

Recently, interest in social robots that can socially interact with humans is increasing. Thanks to the development of ICT technology, social robots have become easier to provide personalized services and emotional connection to individuals, and the role of social robots is drawing attention as a means to solve modern social problems and the resulting decline in the quality of individual lives. Along with the interest in social robots, the spread of social robots is also increasing significantly. Many companies are introducing robot products to the market to target various target markets, but so far there is no clear trend leading the market. Accordingly, there are more and more attempts to differentiate robots through the design of social robots. In particular, anthropomorphism has been studied importantly in social robot design, and many approaches have been attempted to anthropomorphize social robots to produce positive effects. However, there is a lack of research that systematically describes the mechanism by which anthropomorphism for social robots is formed. Most of the existing studies have focused on verifying the positive effects of the anthropomorphism of social robots on consumers. In addition, the formation of anthropomorphism of social robots may vary depending on the individual's motivation or temperament, but there are not many studies examining this. A vague understanding of anthropomorphism makes it difficult to derive design optimal points for shaping the anthropomorphism of social robots. The purpose of this study is to verify the mechanism by which the anthropomorphism of social robots is formed. This study confirmed the effect of the human-likeness of social robots(Within-subjects) and the construal level of consumers(Between-subjects) on the formation of anthropomorphism through an experimental study of 3×2 mixed design. Research hypotheses on the mechanism by which anthropomorphism is formed were presented, and the hypotheses were verified by analyzing data from a sample of 206 people. The first hypothesis in this study is that the higher the human-likeness of the robot, the higher the level of anthropomorphism for the robot. Hypothesis 1 was supported by a one-way repeated measures ANOVA and a post hoc test. The second hypothesis in this study is that depending on the construal level of consumers, the effect of human-likeness on the level of anthropomorphism will be different. First, this study predicts that the difference in the level of anthropomorphism as human-likeness increases will be greater under high construal condition than under low construal condition.Second, If the robot has no human-likeness, there will be no difference in the level of anthropomorphism according to the construal level. Thirdly,If the robot has low human-likeness, the low construal level condition will make the robot more anthropomorphic than the high construal level condition. Finally, If the robot has high human-likeness, the high construal levelcondition will make the robot more anthropomorphic than the low construal level condition. We performed two-way repeated measures ANOVA to test these hypotheses, and confirmed that the interaction effect of human-likeness and construal level was significant. Further analysis to specifically confirm interaction effect has also provided results in support of our hypotheses. The analysis shows that the human-likeness of the robot increases the level of anthropomorphism of social robots, and the effect of human-likeness on anthropomorphism varies depending on the construal level of consumers. This study has implications in that it explains the mechanism by which anthropomorphism is formed by considering the human-likeness, which is the design attribute of social robots, and the construal level of consumers, which is the way of thinking of individuals. We expect to use the findings of this study as the basis for design optimization for the formation of anthropomorphism in social robots.

• Journal of Digital Convergence
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• v.18 no.4
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• pp.37-44
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• 2020

This study aimed to explore the relationship between Intelligent Robot Reacher(IRT)-student by examining the factors of their relationship perceived by middle school students. In doing so, we developed questionnaires based on the existing teacher-student relationship scale and conducted an online survey of 283 first graders in middle school. The collected date were analyzed using exploratory factor analyses with SPSS 23 and confirmatory factor analysis with Amos 21. The study findings identified four factors of IRT-student relationship namely "trust", "competence", "emotional exchange", and "tolerance". It is expected that the study can be used to discuss ways to enhance educationally significant interaction between students-IRT and teaching methods using intelligent robots(IRs). Also, the study will contribute to the understanding and development of various services using IRs. Based on the study finidngs, future studies should investigate the perception of various education stockholders (teachers, parets, etc) on IRT to elevate the Human-Robot Interaction in the education field.

• Information and Communications Magazine
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• v.33 no.8
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• pp.19-27
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• 2016

최근 들어 로봇 기술은 팔과 다리가 달린 인간형 로봇 휴머노이드(Humanoid)와 같이 겉모습뿐만 아니라 히노애락(喜怒哀樂)과 같은 인간의 감정을 흉내 내는 지능형 감성로봇(Emotional robot)으로 진화하고 있으며, 사물인터넷(Internet of things, IoT), 빅데이터(Big data) 및 인공지능(Artificial intelligence, AI) 기술까지 융합하는 연구가 진행되고 있다. 이러한 기술 발전을 기반으로 로봇산업은 전통적인 제조업뿐만 아니라 의료, 실버, 국방, 건설, 생활가전, 물류, 드론 등 다양한 분야에서 활용이 가능하며, 또한 교육, 문화, 예술에도 접목을 할 수 있어 넓은 분야에서 발전 가능성이 매우 큰 산업이다. 본 논문에서는 인간과 교감하는 감성로봇의 개념과 주요 기술을 소개한다. 아울러, 최근까지 연구 개발되었거나 제품으로 출시되었던 감성로봇 사례를 소개하고 향후 전망에 대해서 논의한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2011.01a
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• pp.217-220
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• 2011

영상 압축 기술의 발전과 인터넷의 보급으로 사람들은 언제 어디서나 고화질의 미디어를 쉽게 접할 수 있게 되었다. 또한 미디어 플레이어에서 문자열의 출력을 지원함으로써 사용자들은 쉽게 영상의 자막을 만들고 볼 수 있는 환경이 만들어졌다. 그러나 문자는 번역을 위한 역할만 할 뿐 미디어에서 나타내고자 하는 감성을 전달하는 역할은 하지 못한다. 본 연구에서는 애니메이션 캐릭터와 콘텐츠 로봇을 사용하는 새로운 의미전달 기술을 적용한 감성형 콘텐츠 서비스를 제안한다. 제안하는 기술은 동기화 시나리오를 구성하여 미디어가 재생되는 동안 애니메이션 캐릭터 데이터를 제공하며, 또 다른 출력장치인 로봇과 동기화되어 상황에 따른 로봇의 움직임을 통해 시청자에게 내용 전달의 효과와 함께 감성 전달의 효율을 증대시켜주는 역할을 한다. 본 논문에서는 감성형 콘텐츠를 제작한 후 시현을 통해 감성 전달의 효율이 높아짐을 확인하였다.

• Journal of Smart Tourism
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• v.2 no.1
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• pp.33-39
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• 2022

This research explores the public's perceptions of the appropriateness of the use of robots in museums and galleries. Using data from an international survey of 1589 participants, the data show that the perceived appropriateness of robot implementation in museums and galleries is driven largely by perceptions of the usefulness and emotional skills of robotic technologies, and their perceived advantages compared to human employees. Additionally, the findings suggest that the general attitudes towards service robots in tourism shape the attitudes towards robots in museums and galleries in particular. Furthermore, the findings reveal that the demographic characteristics of visitors are not related to their perceptions of robots in museums and galleries.