• 한국산업정보학회논문지
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• 제17권3호
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• pp.51-57
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• 2012

팩맨(Pacman)은 세계적으로 사랑을 받는 클래식 게임의 종결자로 알려져 있다. 본 논문에서는 클래식 게임인 팩맨을 키보드나 마우스를 사용하지 않고 간단한 손동작만으로 게임을 플레이 할 수 있도록 한다. 즉, 손의 좌표 중심점을 이용하여 방향키를 대신할 수 있도록 한 모션을 이용한 게임이다. 또한 캠을 이용하여 MFC 다이얼로그에 영상을 받아 손에 대한 포인터를 추출하여 손의 움직임에 따라 몬스터의 움직임도 바뀌도록 한다. 본 논문에서 피부색 추출을 위해 RGB 영상을 YCbCbr영상으로 변환하고, 보다 좋은 영상을 얻기 위하여 곱 연산과 하이브리드 미디언 필터링을 이용하였다. 그리고 손 영역의 무게 중심을 구하여 이를 중심으로 손 영역의 움직임을 구하는 방법을 사용하였다.

• 대한인간공학회지
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• 제31권6호
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• pp.725-731
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• 2012

Objective: The aim of this study is to investigate visual feedback effects and human performance in the foot mouse control. Background: Generally, computer mouse tasks are controlled by visual feedback. In order to understand the characteristics of a foot mouse control, it is important to investigate the patterns of visual feedback involved in foot-mouse control tasks. Human performance of foot mouse control is also an important factor to understand the foot mouse control. Method: Three types of mouse control were determined to investigate visual feedback effects and human performance in the foot mouse control. Visual feedback effects in the foot mouse control were compared with those of a typical hand mouse. The cursor movement speed and mental workload were measured in the three types of tasks and two types of mouses. Results: Mouse control tasks with an element of homing-in to the target were more quickly performed by the hand mouse than the foot mouse. Mental workload was also higher in the foot mouse than the hand mouse. However, in the steering movement, human performance of the foot mouse control was not lower than that of the hand mouse control. Visual feedback in the foot mouse control was less required than in the hand mouse control. Conclusion: The foot mouse was not efficient in the most mouse control tasks, compared to the hand mouse. However, the foot mouse was efficient in the steering movement, moving a cursor within a path with lateral constraints. Application: The results of this study might help to develop the foot mouse.

• 대한인간공학회지
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• 제26권2호
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• pp.149-155
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• 2007

Recently, various devices requiring text input such as mobile phone IPTV, PDA and UMPC are emerging. The frequency of text entry for them is also increasing. This study was focused on the evaluation of Korean text entry interface. Various models to evaluate text entry interfaces have been proposed. Most of models were based on human cognitive process for text input. The cognitive process was divided into two components; visual scanning process and finger movement process. The time spent for visual scanning process was modeled as Hick-Hyman law, while the time for finger movement was determined as Fitts' law. There are three questions on the model-based evaluation of text entry interface. Firstly, are human cognitive processes (visual scanning and finger movement) during the entry of text sequentially occurring as the models. Secondly, is it possible to predict real text input time by previous models. Thirdly, does the human cognitive process for text input vary according to users' text entry speed. There was time gap between the real measured text input time and predicted time. The time gap was larger in the case of participants with high speed to enter text. The reason was found out investigating Eye-Hand Coordination during text input process. Differently from an assumption that visual scan on the keyboard is followed by a finger movement, the experienced group performed both visual scanning and finger movement simultaneously. Arrival Lead Time was investigated to measure the extent of time overlapping between two processes. 'Arrival Lead Time' is the interval between the eye fixation on the target button and the button click. In addition to the arrival lead time, it was revealed that the experienced group uses the less number of fixations during text entry than the novice group. This result will contribute to the improvement of evaluation model for text entry interface.

• 대한인간공학회지
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• 제21권3호
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• pp.1-12
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• 2002

Recently, EEG gains much interests due to its applicability for people to communicate directly with computers without detouring motor output. This study was designed to address this issue if EEG can be successfully used to predict limb movement. It was found that ordinary people appeared to show significant difference in brainwaves between right hand (foot) and left hand (foot) movement. Lateral asymmetry was also found to interact significantly with EEG. Further research is urged with refined method to provide more useful insights into EEG-based BCI.

• 제어로봇시스템학회논문지
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• 제17권10호
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• pp.1014-1020
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• 2011

This presents a motion and force estimation system of human fingers by using an Electromyography (EMG) sensor module and a data glove system to be proposed in this paper. Both EMG sensor module and data glove system are developed in such a way to minimize the number of hardware filters in acquiring the signals as well as to reduce their sizes for the wearable. Since the onset of EMG precedes the onset of actual finger movement by dozens to hundreds milliseconds, we show that it is possible to predict the pattern of finger movement before actual movement by using the suggested system. Also, we are to suggest how to estimate the grasping force of hand based on the relationship between RMS taken EMG signal and the applied load. Finally we show the effectiveness of the suggested estimation system through several experiments.

• 대한의용생체공학회:의공학회지
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• 제28권1호
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• pp.139-147
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• 2007

The aim of this study was to evaluate effects of short-tenn repetitive-bilateral excercise on the activation of motor network using functional magnetic resonance imaging (fMRI). The training program was performed at 1 hr/day, 5 days/week during 6 weeks. Fugl-Meyer Assessments (FMA) were performed every two weeks during the training. We compared cerebral and cerebellar cortical activations in two different tasks before and after the training program: (1) the only unaffected hand movement (Task 1); and (2) passive movements of affected hand by the active movement of unaffected hand (Task 2). fMRI was performed at 3T with wrist flexion-extension movement at 1 Hz during the motor tasks. All patients showed significant improvements of FMA scores in their paretic limbs after training. fMRI studies in Task 1 showed that cortical activations decreased in ipsilateral sensorimotor cortex but increased in contralateral sensorimotor cortex and ipsilateral cerebellum. Task 2 showed cortical reorganizations in bilateral sensorimotor cortex, premotor area, supplemetary motor area and cerebellum. Therefore, this study demonstrated that plastic changes of motor network occurred as a neural basis of the improvement subsequent to repetitive-bilateral excercise using the symmetrical upper-limb ann motion trainer.

• 한국전자파학회논문지
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• 제29권7호
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• pp.508-514
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• 2018

뇌전도는 뇌 활동 시 발생하는 뇌 세포 간 상호작용으로 생성된 전기적 활동이며, 손동작 시 뇌 활동으로 인해 뇌전도가 발생한다. 본 연구에서는 16채널 뇌전도 측정 장비를 이용하여 손동작 전과 좌 혹은 우 손동작 시 발생되는 뇌전도를 측정하였으며, 측정된 데이터는 지도 학습 모델인 서포트 벡터 머신으로 분류하며, 서포트 벡터 머신의 학습 시간을 단축 위해 동작관련 정보 손실을 최소화하고, 뇌전도 정보를 축약할 수 있는 필터링을 통한 특징 추출과 벡터 차원 축소 기법을 제안한다. 분류 결과, 전두엽 부위의 전극에서 손동작 전 상태-손동작사이에서 평균 72.7 %의 정확도로 분류되었다.

• 디지털콘텐츠학회 논문지
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• 제13권2호
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• pp.235-245
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• 2012

우리는 본 논문에서 사용자 제스처 인터페이스 기반 퀴즈게임 콘텐츠를 제안한다. 우리는 기존의 아날로그 방식으로 수행해 오던 퀴즈게임의 요소들을 파악하여 디지털화함으로써 퀴즈 진행자의 역할을 콘텐츠 프로그램이 담당할 수 있도록 하였다. 우리는 키넥트 카메라를 사용하여 깊이영상을 획득하고 깊이영상에서 사용자 분할, 머리 위치 검출 및 추적, 손 검출 등의 전처리 작업과 손들기, 손 상하이동, 주먹 모양, 패스, 주먹 쥐고 당김 등의 명령형 손 제스처 인식기술을 개발하였다. 특히 우리는 사람이 일상생활에서 물리적인 객체를 조작하는 동작으로 인터페이스를 위한 제스처를 정의함으로써 사용자가 이동, 선택, 확인 등의 추상적인 개념을 인터페이스 과정에서 체감할 수 있도록 디자인하였다. 앞서 발표되었던 선행 작업과 비교할 때, 우리는 승리 팀에 대한 카드보상 절차를 추가하여 콘텐츠의 완성도를 높였으며, 손 상하이동 인식과 주먹 모양 인식 알고리즘 등을 개선하여 문제 보기선택의 성능을 크게 향상시켰고, 체계적인 실험을 통해 만족할 만한 인식 성능을 입증하였다. 구현된 콘텐츠는 실시간 테스트에서 만족스러운 제스처 인식 결과를 보였으며 원활한 퀴즈게임 진행이 가능하였다.

• Journal of Platform Technology
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• 제6권1호
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• pp.3-8
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• 2018

This paper proposes a technique for recognizing online handwritten cursive data obtained by tracing a motion trajectory while a user is in the 3D space based on a convolution neural network (CNN) algorithm. There is a difficulty in recognizing the virtual character input by the user in the 3D space because it includes both the character stroke and the movement stroke. In this paper, we divide syllable into consonant and vowel units by using labeling technique in addition to the result of localizing letter stroke and movement stroke in the previous study. The coordinate information of the separated consonants and vowels are converted into image data, and Korean handwriting recognition was performed using a convolutional neural network. After learning the neural network using 1,680 syllables written by five hand writers, the accuracy is calculated by using the new hand writers who did not participate in the writing of training data. The accuracy of phoneme-based recognition is 98.9% based on convolutional neural network. The proposed method has the advantage of drastically reducing learning data compared to syllable-based learning.

• 대한의용생체공학회:의공학회지
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• 제15권1호
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• pp.77-82
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• 1994

We investigated the characteristic of the sensory motor coordination by measuring the hand point ins and the gaze movement to the visual and sound stimulation. Our results showed that the gaze vol ocity to sound stimulation did not depend on stimulation direction, but lagged behind 0.2 sec toward the pheriperal direction to the visual stimulation. Our data showed that to both visual and sound stimulation, the error of hand pointing value increased with an increasement of eccentricity.