• Journal of the Ergonomics Society of Korea
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• v.35 no.5
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• pp.403-411
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• 2016

Objective: This study is concerned with the user interface (UI) design of touch screen based on the reaction time of Automated Teller Machine (ATM) user. Background: Adopting the touch screen technology, the ATM service has recently established a new user interface different from the existing button-type interface. Method: Experiments were conducted by simulating ATM touch screen layouts, and layouts were focused on location of menu buttons (left and right, top and bottom), number of menu buttons (8 and 12 buttons). Results: The results show that there are significant differences in correction ratio and reaction time by user groups, types of menu location, and the number of buttons. Conclusion and Applications: The results of this study can be used to provide baseline information for the interface design of ATM touch screen and the age differences in reaction time.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.5 no.1
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• pp.103-110
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• 2011

In this paper, we propose a gaze recognition interface for smart wheelchair. The gaze recognition interface is a user interface which recognize the commands using the gaze recognition and avoid the detected obstacles by sensing the distance through range sensors on the way to driving. Smart wheelchair is composed of gaze recognition and tracking module, user interface module, obstacle detector, motor control module, and range sensor module. The interface in this paper uses a camera with built-in infra red filter and 2 LED light sources to see what direction the pupils turn to and can send command codes to control the system, thus it doesn't need any correction process per each person. The results of the experiment showed that the proposed interface can control the system exactly by recognizing user's gaze direction.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.1
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• pp.75-83
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• 2008

We propose a welfare interface using multiple fecial features tracking, which can efficiently implement various mouse operations. The proposed system consist of five modules: face detection, eye detection, mouth detection, facial feature tracking, and mouse control. The facial region is first obtained using skin-color model and connected-component analysis(CCs). Thereafter the eye regions are localized using neutral network(NN)-based texture classifier that discriminates the facial region into eye class and non-eye class, and then mouth region is localized using edge detector. Once eye and mouth regions are localized they are continuously and correctly tracking by mean-shift algorithm and template matching, respectively. Based on the tracking results, mouse operations such as movement or click are implemented. To assess the validity of the proposed system, it was applied to the interface system for web browser and was tested on a group of 25 users. The results show that our system have the accuracy of 99% and process more than 21 frame/sec on PC for the $320{\times}240$ size input image, as such it can supply a user-friendly and convenient access to a computer in real-time operation.

• Journal of Digital Convergence
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• v.16 no.5
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• pp.221-229
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• 2018

Machine learning and artificial intelligence are core technologies for the 4th industrial revolution. However, it is difficult for the general public to get familiar with those technologies because most people lack programming ability. Thus, we developed a Graphic User Interface(GUI) to overcome this obstacle. We adopted TensorFlow and used .Net of Microsoft for the develop. With this new GUI, users can manage data, apply algorithms, and run machine learning without coding ability. We hope that this development will be used as a basis for developing artificial intelligence in various fields.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.835-838
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• 2003

Computer vision and natural-language dialogue play an important role in friendly human-machine interfaces for service robots. In this paper we describe an integrated face detection and face recognition system for a welfare robot, which has also been combined with the robot's speech interface. Our approach to face detection is to combine neural network (NN) and genetic algorithm (GA): ANN serves as a face filter while GA is used to search the image efficiently. When the face is detected, embedded Hidden Markov Model (EMM) is used to determine its identity. A real-time system has been created by combining the face detection and recognition techniques. When motivated by the speaker's voice commands, it takes an image from the camera, finds the face inside the image and recognizes it. Experiments on an indoor environment with complex backgrounds showed that a recognition rate of more than 88% can be achieved.

• International Journal of Advanced Culture Technology
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• v.9 no.1
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• pp.196-202
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• 2021

Currently, as Korea enters into a fast aging society, the problem of dementia population is increasing. In this paper, we intend to contribute to the improvement of welfare for the elderly by developing virtual reality technology and related interface technology to effectively perform hand movements known as effective methods for preventing and treating dementia. As the content of the research and development of this paper, it is designed to be easy for the elderly to use and stimulate brain function by applying VR technology using sensors, and to activate mental and physical activities for the elderly who are marginalized in terms of cultural welfare. We intend to develop by classifying the types of games and contents that can induce them. As a result of this thesis, we developed contents using virtual reality to improve cognitive abilities for elderly people with poor cognitive ability to activate the brains of users' cognition, memory, and attention to prevent and treat dementia I want to contribute.

• Journal of KIBIM
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• v.13 no.3
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• pp.39-47
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• 2023

This study aims to introduce a model for enhancing community well-being through the utilization of public open data. To objectively assess abstract notions of residential satisfaction, text data from complaints is analyzed. By leveraging accessible public data, costs related to data collection are minimized. Initially, relevant text data containing civic complaints is collected and refined by removing extraneous information. This processed data is then combined with meaningful datasets and subjected to topic modeling, a text mining technique. The insights derived are visualized using Geographic Information System (GIS) and Application Programming Interface (API) data. The efficacy of this analytical model was demonstrated in the Godeok/Gangil area. The proposed methodology allows for comprehensive analysis across time, space, and categories. This flexible approach involves incorporating specific public open data as needed, all within the overarching framework.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.2 no.1
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• pp.45-49
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• 2009

This paper proposes a data glove for a rehabilitation robot interface for the upper extremity paralysis. The designed data glove uses seven flexible sensors so as to measure the flexion angles of fingers and wrist. We verified the performance of the data glove using a 3D graphic interface developed. The experimental results show that the proposed data glove is feasible to sense hand motions and applicable to the robot interface.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.1 no.1
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• pp.1-6
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• 2007

Applying the gyroscopic technology, HeadZmouse has been developed to simulate left and right mouse click, double click, drag and drop, and even a wheel function for navigating web. This device was designed to work on both PC and Macintosh environments using a USB cable. The first time you use this device, you'll find out how much freedom it offers to someone who can't use his or her hands freely. Rather than being tied to your computer, simple manipulation such as blowing an air (breathing) into a sonic sensor can simulate all the functions which standard mouse has, even including a wheel function. Also, a macro-interface device has been developed. By storing repetitive tasks into a memory, you can carry out repetitive tasks just by clicking a button once.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1163-1168
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• 2005

This paper proposes a soft-remote-control (soft-remocon) system based on EMG signals for the Intelligent Sweet Home. The proposed system is applied to Intelligent Sweet Home which was developed to help the independence living of the elderly and physically handicapped individuals. The goal of proposed system is to control home-installed electronic devices such as TV, air-conditioner, curtain and lamp in Intelligent Sweet Home using EMG signals. Features such as VAR and DAMV having good separability performance are selected for pattern classification. FMMNN is adopted as a pattern classifier. Classification results are allowed to a developed remote control module and then corresponding infrared pulses can operate home-installed electronic devices. We concluded that EMG as an input interface for home-installed electronic devices in Intelligent Sweet Home.