• 한국정보교육학회:학술대회논문집
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• 2007.08a
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• pp.173-178
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• 2007

정보영재를 교육시키기 위한 프로그래밍 교육방법의 많은 문제점에도 불구하고 프로그래밍교육을 통해 얻을 수 있는 잠재적인 교육효과가 크기 때문에 프로그래밍 교육은 컴퓨터 정보영재 교육과정에서 빠질 수 없는 부분이다. 본 연구는 정보영재들에게 프로그래밍 교육을 실시할 때 프로그래밍 교육방법의 문제점을 극복할 수 있는 도구로 로봇을 소개하고, 로봇을 이용한 체계적인 로봇프로그래밍 교육과정의 개발로 문제해결력, 창의력, 사고력, 판단력 등의 고등인지기능을 신장시키고자 한다.

• Proceedings of the Korea Contents Association Conference
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• 2013.05a
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• pp.143-144
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• 2013

어린이들은 어른에 비해 신체조건이나 정신조건이 연약해 특별한 보호가 필요하다. 어른이 돌보아주는 것이 마땅하지만 경제적 여건 등으로 혼자 남겨질 수 밖 에 없는 경우 이를 대신할 로봇이 필요하다. 어린이를 위협하는 위험요소들 중 환경오염과 안전사고에 대한 문제를 파악한 후 해결방안을 제시하였다. 로봇의 대상으로 어린이들이 선호하는 펭귄을 선정하였고 아이디어스케치, 3D 렌더링을 진행하여 최종모델을 제작하였다. 가상 시나리오를 통해 로봇의 사용 사례를 제시하였다.

• Archives of design research
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• v.20 no.3 s.71
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• pp.97-106
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• 2007

This study examines whether the reinforcement theory could be effectively applied to teaching assistant robots between a robot and a student in the same way as it is applied to teaching methods between a teacher and a student. Participants interacted with a teaching assistant robot in a 3 (types of robots: positive reinforcement vs. negative reinforcement vs. both reinforcements) by 2 (types of participants: honor students vs. backward students), within-subject experiment. Three different types of robots, such as 'Ching-chan-ee' which gives 'positive reinforcement', 'Um-bul-ee' which gives 'negative reinforcement', and 'Sang-bul-ee' which gives both 'positive and negative reinforcement' were designed based on the reinforcement theory and the token reinforcement system. Subjective impressions and preferences were measured according to the types of robots and the types of participants. Participants preferred the positive reinforcement robot most, and the negative reinforcement robot least. Regarding the number of stimulus, in case of the negative reinforcement robot for honor students, the less the stimulus is, the more positive the impressions toward the robot are. The findings demonstrate that the reinforcement interaction is important and effective factor which determines children's preferences and impressions for teaching assistant robots. The results of this study can be implicated as an effective guideline to interaction design of teaching assistant robots.

• Archives of design research
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• v.20 no.3 s.71
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• pp.107-118
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• 2007

The aim of this paper is to suggest a design guideline for a teaching assistant robot by finding out images that satisfy the role of the teaching assistant robot, and to search for a body features that show such images. Role images of teaching assistant robots were established from literature review and factor analysis. And eight elements of body features were extracted from human's elements of body feature. Robot external form samples varied according to the body feature was modeled three-dimensionally. Children, who are the main users of teaching assistant robots, valuated the 3D robot samples projected onto wall in real size. The valuation basis was role images of teaching assistant robots, adjectives about age and gender, preference, and appropriateness as teaching assistant robots. The result of valuation was analyzed by analysis of variance, and analysis of correlation. The result revealed the fact that four elements of body feature (the ratio of head length, height, the ratio of breast girth, and waist girth) were related to role images. Among these elements, height and waist girth was more important than the rest, particularly, waist girth had strong relation with all the role images. Also, in order to reveal tender and kind image, the ratio of head length was proved to have to be adjusted according to waist girth. On the basis of these result, a design guideline for a teaching assistant robot was suggested.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.147-149
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• 2022

This paper proposes a state machine design methodology in which an interactive robot that mimics discrete trial training (DTT protocol) can support social interaction training for children with autism. The robot applied to social interaction training uses the response to the provided training stimulus as a quantitative indicator by processing the data received from the sensors measuring the behavioral response of the child. In this process, the state machine is used as information that classifies the state of the acquired data and provides the subsequent stimulus for DTT protocol. Through the joint attentional training, it can be used as evidence-based treatment information by quantitatively classifying the data on the number of sustainable and DTT protocol and the child's response, as well as the current reaction status of the child to the observer performing remote monitoring. At the same time, it was confirmed that it is possible to properly respond to misrecognition situations.

• International Journal of Advanced Culture Technology
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• v.7 no.1
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• pp.231-236
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• 2019

Background/Objectives: This paper proposes a dual mode feedback-controlled cycling system for children with spastic cerebral palsy to rehabilitate upper extremities. Repetitive upper limb exercise in this therapy aims to both reduce and analyze the abnormal torque patterns of arm movements in three- dimensional space. Methods/Statistical analysis: We designed an exercycle robot which consists of a BLDC motor, a torque sensor, a bevel gear and bearings. Mechanical structures are customized for children of age between 7~13 years old and induces reaching and pulling task in a symmetric circulation. The shafts and external frames were designed and printed using 3D printer. While the child performs active/passive exercise, angular position, angular velocity, and relative torque of the pedal shaft are measured and displayed in real time. Findings: Experiment was designed to observe the features of a cerebral palsy child's exercise. Two children with bilateral spastic cerebral palsy participated in the experiment and conducted an active exercise at normal speed for 3 sets, 15 seconds for each. As the pedal reached 90 degrees and 270 degrees, the subject showed minimum torque, in which the child showed difficulty in the pulling task of the cycle. The passive exercise assisted the child to maintain a relatively constant torque while visually observing the movement patterns. Using two types of exercise enabled the child to overcome the abnormal torque measured in the active data by performing the passive exercise. Thus, this system has advantage not only in allowing the child to perform the difficult task, which may contribute in improving the muscle strength and endurance and reducing the spasticity but also provide customizable system according to the child's motion characteristic. Improvements/Applications: Further study is needed to observe how passive exercise influences the movement characteristics of an active motion and how customized experiment settings can optimize the effect of pediatric rehabilitation for spastic cerebral palsy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.1
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• pp.165-172
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• 2015

The purpose of this study was to identify the effect of Genibo program robot-based learning(R-Learning) on a pre-schooler's mental state. To achieve above study purpose, the subject of this study was selected 46(teacher 2, five years old pre-schooler 44) from pre-school childrens in Kyongki Y city(R-Learning activity participants group 21: boys 10, girls 11. non-participants 25: boys 13, girls 12). R-Learning program is consist of 5 field about 20 contents using Genibo robot, were applied to the experimental group and the pre-post test was conducted using the EQ assessment tool and observations. The data were analyzed by t-test using the SPSS(ver 18.0) program. The results were as follows: First, the exposure of robots to pre-schoolers in practical situation has shown positive influence to the children's emotional well-being. Positive improvements were observed in the four sub categories of the EQ assessment after exposure. Second, the Genibo used for this study, is a biomimetic AI based robot mimicking the behavior of a pet dog. This is related more or less to the specifications of a pre-school education where animals are used as a 'friendly medium' to facilitate the learning process. Third, the robot exposure gave benefit to all the ones in the sample, regardless of sex. Furthermore, It is suggested that promising potential for robots to be utilized as a new educational media plus facilitator, R-Learning is related more or less to the specifications of a pre-school education where animals are used as a 'friendly medium' to facilitate the learning process, and when applying them for education, stereotyping the likes of sex is overrated - instead, the focus should be more on the pre-schoolers' / childrens' individual traits, learning curve differences and alike.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.53-69
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• 2011

Vision and voice-based technologies are commonly utilized for human-robot interaction. But it is widely recognized that the performance of vision and voice-based interaction systems is deteriorated by a large margin in the real-world situations due to environmental and user variances. Human users need to be very cooperative to get reasonable performance, which significantly limits the usability of the vision and voice-based human-robot interaction technologies. As a result, touch screens are still the major medium of human-robot interaction for the real-world applications. To empower the usability of robots for various services, alternative interaction technologies should be developed to complement the problems of vision and voice-based technologies. In this paper, we propose the use of accelerometer-based gesture interface as one of the alternative technologies, because accelerometers are effective in detecting the movements of human body, while their performance is not limited by environmental contexts such as lighting conditions or camera's field-of-view. Moreover, accelerometers are widely available nowadays in many mobile devices. We tackle the problem of classifying acceleration signal patterns of 26 English alphabets, which is one of the essential repertoires for the realization of education services based on robots. Recognizing 26 English handwriting patterns based on accelerometers is a very difficult task to take over because of its large scale of pattern classes and the complexity of each pattern. The most difficult problem that has been undertaken which is similar to our problem was recognizing acceleration signal patterns of 10 handwritten digits. Most previous studies dealt with pattern sets of 8~10 simple and easily distinguishable gestures that are useful for controlling home appliances, computer applications, robots etc. Good features are essential for the success of pattern recognition. To promote the discriminative power upon complex English alphabet patterns, we extracted 'motion trajectories' out of input acceleration signal and used them as the main feature. Investigative experiments showed that classifiers based on trajectory performed 3%~5% better than those with raw features e.g. acceleration signal itself or statistical figures. To minimize the distortion of trajectories, we applied a simple but effective set of smoothing filters and band-pass filters. It is well known that acceleration patterns for the same gesture is very different among different performers. To tackle the problem, online incremental learning is applied for our system to make it adaptive to the users' distinctive motion properties. Our system is based on instance-based learning (IBL) where each training sample is memorized as a reference pattern. Brute-force incremental learning in IBL continuously accumulates reference patterns, which is a problem because it not only slows down the classification but also downgrades the recall performance. Regarding the latter phenomenon, we observed a tendency that as the number of reference patterns grows, some reference patterns contribute more to the false positive classification. Thus, we devised an algorithm for optimizing the reference pattern set based on the positive and negative contribution of each reference pattern. The algorithm is performed periodically to remove reference patterns that have a very low positive contribution or a high negative contribution. Experiments were performed on 6500 gesture patterns collected from 50 adults of 30~50 years old. Each alphabet was performed 5 times per participant using $Nintendo{(R)}$ $Wii^{TM}$ remote. Acceleration signal was sampled in 100hz on 3 axes. Mean recall rate for all the alphabets was 95.48%. Some alphabets recorded very low recall rate and exhibited very high pairwise confusion rate. Major confusion pairs are D(88%) and P(74%), I(81%) and U(75%), N(88%) and W(100%). Though W was recalled perfectly, it contributed much to the false positive classification of N. By comparison with major previous results from VTT (96% for 8 control gestures), CMU (97% for 10 control gestures) and Samsung Electronics(97% for 10 digits and a control gesture), we could find that the performance of our system is superior regarding the number of pattern classes and the complexity of patterns. Using our gesture interaction system, we conducted 2 case studies of robot-based edutainment services. The services were implemented on various robot platforms and mobile devices including $iPhone^{TM}$. The participating children exhibited improved concentration and active reaction on the service with our gesture interface. To prove the effectiveness of our gesture interface, a test was taken by the children after experiencing an English teaching service. The test result showed that those who played with the gesture interface-based robot content marked 10% better score than those with conventional teaching. We conclude that the accelerometer-based gesture interface is a promising technology for flourishing real-world robot-based services and content by complementing the limits of today's conventional interfaces e.g. touch screen, vision and voice.

• Science of Emotion and Sensibility
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• v.13 no.1
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• pp.33-40
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• 2010

The study is to examine relationship between the level of depression and facial EMG responses during the humor condition. Forty-three children(age range 22-49 years) participated in the study. The Korean Personality Inventory for Children(KPI-C) was used to measure the level of depression in children. While children were presented to audio-visual film clip inducing humor, facial EMG were measured on their faces(bilateral corrugators and orbicularis). A baseline state was measured during 60 seconds before the presentation of the stimulus, i.e., emotional state lasting 120 seconds. Participants were asked to report the intensity of their experienced emotion. The results of emotion assessment showed 95.3% appropriateness and 3.81 intensity on the 5 points Likert scale). Facial EMG showed a significant increase while participants experiencing humor compared to baseline state. Additionally, the result showed a negative correlation between right corrugator responses and the level of depression. The study findings showed the more children experienced depression, the less facial EMG activity they had while experiencing humor.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.10
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• pp.1427-1434
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• 2021

In this paper, we propose a psychological state estimation process that computes children's attention and tension in response to training stimuli. Joint attention was adopted as the training stimulus required for behavioral intervention, and the Discrete trial training (DTT) technique was applied as the training protocol. Three types of training stimulation contents are composed to check the user's attention and tension level and provided mounted on a character-shaped tabletop robot. Then, the gaze response to the user's training stimulus is estimated with the vision-based head pose recognition and geometrical calculation model, and the nervous system response is analyzed using the PPG and GSR bio-signals using heart rate variability(HRV) and histogram techniques. Through experiments using robots, it was confirmed that the psychological response of users to training contents on joint attention could be quantified.