• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.9-14
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• 2015

Touch interface is widely used in a smartphone instead of a keyboard or a keypad interface that has been adopted in a PC or a featurephone, respectively. Touch interface can recognize a variety of gestures that clearly represent the distinct features of each application's input. This paper analyzes users' gesture of each application captured by the touch interface of a smartphone. Specifically, we extract touch input traces from various application categories such as game, web browser, youtube, image and e-book viewer, video player, camera, and map applications, and then analyzed them. Through this analysis, we observed a certain unique characteristics of each application's touch input, and this can be utilized in various useful areas such as identification of an application user, prevention of running an application by an illegal user, or design of a new interface convenient to a specific user.

• International journal of advanced smart convergence
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• v.10 no.4
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• pp.30-37
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• 2021

Touch sensor interface has become the most useful input device in a smartphone. Unlike keypad/keyboard interfaces used in electronic dictionaries and feature phones, smartphone's touch interfaces allow for the recognition of various gestures that represent distinct features of each application's input. In this paper, we analyze application-specific input patterns that appear in smartphone's touch interfaces. Specifically, we capture touch input patterns from various Android applications, and analyze them. Based on this analysis, we observe a certain unique characteristics of application's touch input patterns. This can be utilized in various useful areas like user authentications, prevention of executing application by illegal users, or digital forensic based on logged touch patterns.

• Journal of the Ergonomics Society of Korea
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• v.31 no.5
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• pp.629-636
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• 2012

Objective: The purpose of this study is to compare the characteristics of single and double finger gestures related on the web browser and to extract the appropriate finger gestures. Background: As electronic equipment emphasizes miniaturization for improving portability various interfaces are being developed as input devices. Electronic devices are made smaller, the gesture recognition technology using the touch-based interface is favored for easy editing. In addition, user focus primarily on the simplicity of intuitive interfaces which propels further research of gesture based interfaces. In particular, the fingers in these intuitive interfaces are simple and fast which are users friendly. Recently, the single and double finger gestures are becoming more popular so more applications for these gestures are being developed. However, systems and software that employ such finger gesture lack consistency in addition to having unclear standard and guideline development. Method: In order to learn the application of these gestures, we performed the sketch map method which happens to be a method for memory elicitation. In addition, we used the MIMA(Meaning in Mediated Action) method to evaluate gesture interface. Results: This study created appropriate gestures for intuitive judgment. We conducted a usability test which consisted of single and double finger gestures. The results showed that double finger gestures had less performance time faster than single finger gestures. Single finger gestures are a wide satisfaction difference between similar type and difference type. That is, single finger gestures can judge intuitively in a similar type but it is difficult to associate functions in difference type. Conclusion: This study was found that double finger gesture was effective to associate functions for web navigations. Especially, this double finger gesture could be effective on associating complex forms such as curve shaped gestures. Application: This study aimed to facilitate the design products which utilized finger and hand gestures.

• Journal of the Ergonomics Society of Korea
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• v.31 no.4
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• pp.585-591
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• 2012

Objective: The aim of this study is to propose the contactless gesture-based interface on smart mobile devices for especially rhythm action games. Background: Most existing approaches about interactions of smart mobile games are tab on the touch screen. However that way is such undesirable for someone or for sometimes, because of the disabled person, or the inconvenience that users need to touch/tab specific devices. Moreover more importantly, new interaction can derive new possibilities from stranded game genre. Method: In this paper, I present a smart mobile game with contactless gesture-based interaction and the interfaces using computer vision technology. Discovering the gestures which are easy to recognize and research of interaction system that fits to game on smart mobile device are conducted as previous studies. A combination between augmented reality technique and contactless gesture interaction is also tried. Results: The rhythm game allows a user to interact with smart mobile devices using hand gestures, without touching or tabbing the screen. Moreover users can feel fun in the game as other games. Conclusion: Evaluation results show that users make low failure numbers, and the game is able to recognize gestures with quite high precision in real time. Therefore the contactless gesture-based interaction has potentials to smart mobile game. Application: The results are applied to the commercial game application.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.1
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• pp.13-18
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• 2010

Most of the research in the multi-touch area is based on the FTIR(Frustrated Total Internal Re리ection), which is just implemented by using the previous approach. Moreover, there are not the software solutions to improve a performance in the multi touch-blobs detection or the user gesture recognition. Therefore, we implement a multi-touch table-top display that is based on the DI(Diffused Illumination), the improved touch-points detection and user gesture recognition. The proposed method supports a simultaneous transformation multi-touch command for objects in the running application. Also, the system latency time is reduced by the proposed ore-testing method in the multi touch-blobs detection processing. Implemented device is simulated by programming the Flash AS3 application in the TUIO(Tangible User Interface Object) environment that is based on the OSC(Open Sound Control) protocol. As a result, Our system shows the 37% system latency reduction, and is successful in the multi-touch gestures recognition.

• MALSORI
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• no.58
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• pp.101-117
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• 2006

The development of efficient multimodal interfaces and fusion algorithms requires knowledge of usage patterns that show how people use multiple modalities. We analyzed multimodal usage patterns for TV-guide application scenarios (or tasks). In order to collect usage patterns, we implemented a multimodal usage pattern collection system having two input modalities: speech and touch-gesture. Fifty-four subjects participated in our study. Analysis of the collected usage patterns shows a positive correlation between the task type and multimodal usage patterns. In addition, we analyzed the timing between speech-utterances and their corresponding touch-gestures that shows the touch-gesture occurring time interval relative to the duration of speech utterance. We believe that, for developing efficient multimodal fusion algorithms on an application, the multimodal usage pattern analysis for the given application, similar to our work for TV guide application, have to be done in advance.

• Korean Journal of Adult Nursing
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• v.21 no.1
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• pp.105-116
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• 2009

Purpose: The purpose of the study was to describe nonverbal behaviors of nurses in communication with patients with dementia in an elderly care institution in Korea. Methods: Conversation analysis was utilized to analyze the data which were collected using video camera to capture non-verbal as well as verbal behaviors. A total of 66 episodes of everyday conversations were analyzed using seven nonverbal categories: affirmative head nodding; illustrative gestures; patient-directed eye gaze; smiling and/or laughing; forward leaning; affective touch; and instrumental touch. Results: Among seven categories, patient-directed eye gaze(94%) was the most frequently utilized among nurses followed by affirmative head nodding(67%) and forward leaning(67%), while smiling was the least used(32%). Affective touch was identified in 39 episodes(59%). Among them, the most frequently touched area was hand or handshaking(59%) followed by shoulder or back, arm, and face. There were wide differences among nurses in terms of using affective touch, ranging from 0% to 98%. Nonverbal behaviors were more frequently identified in effective episodes than in ineffective episodes. Conclusion: Actively utilizing effective nonverbal behaviors may help geriatric nurses in promoting communication and in establishing rapport with patients with dementia.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.4
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• pp.565-569
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• 2014

Recently, various kinds of new computer controlled devices have been introduced in a wide range of areas, and convenient user interfaces for controlling the devices are strongly needed. To implement natural user interfaces(NUIs) on top of the devices, new technologies like a touch screen, Wii Remote, wearable interfaces, and Microsoft Kinect were presented. This paper presents a natural and intuitive gesture-based model for controlling contents of LCD display. Microsoft Kinect sensor and its SDK are used to recognize human gestures, and the gestures are interpreted into corresponding commands to be executed. A command dispatch model is also proposed in order to handle the commands more naturally. I expect the proposed interface can be used in various fields, including display contents control.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.6
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• pp.121-126
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• 2017

Recently, a lot of people use touch-pen devices such as smart phones and tab computers. To generate the picture and text, a user can give input or control the touch-pen device through simple or multi-touch gestures by touching the screen with a special stylus pen and/or one or more fingers. The accuracy and response time from the moment of contact with the touch board is very important to the touch device. Therefore, research is needed to find a way of removing the noise included in the touch signal quickly and efficiently. In this paper, we propose a method for removing a noise mixed in with a touch point coordinate which has been caused by a input pen on the touch screen. For effective filtering, the fast sampling of the coordinate corresponding to the noise from the input signal is required primarily. Secondly the total compensation of the touch coordinates using the characteristics of the B-Spline curve is applied to correct coordinates of the points. This method can ensure a real-time response than other algorithms. The applied performance evaluation method is comparing error pixels with evaluation values by dividing 10 intervals on the touch pad diagonally. Usually the average error is 7.1 pixels but our proposed method shows an average 4.1 errors. Therefore, our proposed touch pen method can express the input signal on the coordinates more correctly.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.2
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• pp.113-120
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• 2015

Under the penetration of smartphones equipped with a variety of features grows globally, the efficient using of a variety of functions of smartphones has been increased. In accordance with this trend, a lot of researches on the remote control method using the smart phone for consumer products in home networks. Input methods of the current smpartphoes are typically button-based inputs through touching. The button input methods are inconvenient for people who are not familiar touch. Therefore, the researches on the different input schemes to replace the touch methods are required. In this paper, we propose a gesture based input method to replace the touch-sensitive input that of the existing smartphone applications, and a way to apply it to home networks. The proposed method uses three-axis acceleration sensor which is built into smatphones, and it also defines six kinds of gestures patterns that may be applied to home network systems by measuring the recognition rates.