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Identification of user`s Motion Patterns using Motion Capture System
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 Title & Authors
Identification of user`s Motion Patterns using Motion Capture System
Jung, Kwang Tae; Lee, Jaein;
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 Abstract
Objective:The purpose of this study is to identify motion patterns for cellular phone and propose a method to identify motion patterns using a motion capture system. Background: In a smart device, the introduction of tangible interaction that can provide new experience to user plays an important role for improving user`s emotional satisfaction. Firstly, user`s motion patterns have to be identified to provide an interaction type using user`s gesture or motion. Method: In this study, a method to identify motion patterns using a motion capture system and user`s motion patterns for using cellular phone was studied. Twenty-two subjects participated in this study. User`s motion patterns were identified through motion analysis. Results: Typical motion patterns for shaking, shaking left and right, shaking up and down, and turning for using cellular phone were identified. Velocity and acceleration for each typical motion pattern were identified, too. Conclusion: A motion capture system could be effectively used to identify user`s motion patterns for using cellular phone. Application: Typical motion patterns can be used to develop a tangible user interface for handheld device such as smart phone and a method to identify motion patterns using motion analysis can be applied in motion patterns identification of smart device.
 Keywords
Motion capture system;Motion patterns;Emotional satisfaction;Tangible interface;
 Language
English
 Cited by
 References
1.
Braido, P. and Zhang X., Quantitative analysis of finger motion coordination in hand manipulative and gestic acts, Human Movement Science, 22, 661-678, 2004. crossref(new window)

2.
Cai, L. and Chen, H., "Touchlogger: Inferring keystrokes on touch screen from smartphone motion". Proc. of HotSec'11, 2011.

3.
Gyeong, D., Han, E., Yang, J. and Jeong, G., Interface Study in Tangible Interactive Environment, Journal of Multimedia and Information Systems, 10(3), 64-72, 2006.

4.
Kamat, S.R. and Yoxall, A., "A Kinetic Study: Understanding Hand and Finger Motion Whilst Squeezing Bottles", Proceedings of the 2014 International Conference on Industrial Engineering and Operations Management, 2014.

5.
Kang, S. and Son, W., Analysis of Drive Motion by Grip Type in Table Tennis, Korean Journal of Sport Science, 17(3), 67-78, 2006.

6.
Lee, A., Interface Technology to Improve Product Value, SERI Economy Focus, SERI, 2008.

7.
Pavlovic, V., Sharma, R. and Huang, T., Visual interpretation of hand gestures for human-computer interaction: A review. IEEE Trans. Pattern Anal. Mach. Intell., 19(7), 677-695, 1997. crossref(new window)

8.
Quek, F., "Toward a Vision-based Hand Gesture Interface", Proceedings of Virtual Reality Software and Technology Conference (VRST), 17-31, 1994.

9.
Sanders, M.S. and McCormick, E.J., Human factors in engineering and design, 7th ed., McGraw Hill, 1993.

10.
Schloemer, T., Poppinga, B., Henze, N. and Boll, S., "Gesture recognition with a wii controller", Proceedings of the Second International Conference on Tangible and Embedded Interaction (TEI'08), ACM, 1-4, 2008.

11.
Witte, K., Schobesberger, H. and Peham, C., Motion pattern analysis of gait in horseback riding by means of Principal Component Analysis, Human Movement Science, 28(3), 394-405, 2009. crossref(new window)

12.
Yun, S., Lee, T., Park, S., Yi, J. and Kim, J., Muscle Activity and a Kinematic Analysis of Drinking Motion, The Journal of Korean Society of Occupational Therapy, 16(1), 77-88, 2008.