Abstract
A daily-wear wearable system is one of the most convenient mediums in practical application scenario of transferring various information data or services between two users as well as between a user and a device. To implement this service scenario, we chose to develop a wearable forearm mounted accelerometer based input system. A set of gesture commands was defined by analyzing intuitive forearm movements. A hardware system and software recognition engine that utilizes the accelerometer sensor data to recognize the gesture commands were implemented and tested. This paper describes the development techniques of a wearable gesture recognition system. It also includes discussions of software and hardware design and how variations in these affected gesture recognition rate by analyzing experimental results from the actual implementations.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Brashear, H., Starner, T., Lukowicz, P., Junker, H.: Using Multiple Sensors for Mobile Sign Language Recognition. In: Proc. IEEE International Symposium on Wearable Computers, pp. 45–52. IEEE Computer Society Press, Los Alamitos (2003)
Randell, C., Muller, H.: Context Awareness by Analyzing Accelerometer Data. In: Proc. IEEE International Symposium on Wearable Computers, pp. 175–176. IEEE Computer Society Press, Los Alamitos (2000)
Lee, H.K., Kim, J.H.: An HMM-based threshold model approach for gesture recognition. Transactions on Pattern Analysis and Machine Intelligence, 961–973 (1999)
Yamato, J., Ohya, J., Ishii, K.: Recognizing Human Actions in Time-Sequential Images Using Hidden Markov Models. In: Proc. Computer Vision and Pattern Recognition, pp. 379–385 (1992)
Schlenzig, J., Hunter, E., Jain, R.: Recursive Identification of Gesture Inputs Using Hidden Markov Models. In: Proc. Conference on Applications of Computer Vision, pp. 187–194 (1994)
Campbell, L., Becker, D., Azarbayejani, A., Bobick, A., Pentland, A.: Invariant Features for 3-d Gesture Recognition. In: Proc. International Conference on Face and Gesture Recognition, pp. 157–162 (1996)
Pylyanainen, T.: Accelerometer Based Gesture Recognition Using Continuous HMMs. In: Proc. International Conference on Pattern Recognition and Image Analysis, pp. 639–646 (2005)
Jang, I.J., Park, W.B.: A Gesture-Based Control for Handheld Devices Using Accelerometer. In: Proc. International Conference on Progress in Pattern Recognition, Image Analysis and Applications, pp. 259–266 (2004)
Rekimoto, J.: GestureWrist and GesturePad: Unobtrusive Wearable Interaction Devices. In: Proc. IEEE International Symposium on Wearable Computers, pp. 21–27. IEEE Computer Society Press, Los Alamitos (2001)
Baudel, T., Beaudouin-Lafon, M.: Charade: Remote Control of Objects Using Free-hand Gestures. Communications of the ACM 36, 28–35 (1993)
Starner, T., Auxier, J., Ashbrook, D., Gandy, M.: The Gesture Pendant: A Self-Illuminating, wearable, Infrared Computer Vision System for Home Automation Control and Medical Monitoring. In: Proc. International Symposium on Wearable Computers, pp. 87–94 (2000)
Fukumoto, M., Tonomura, Y.: Body Coupled FingerRing: Wireless Wearable Keyboard. In: Proc. CHI, pp. 147–154 (1997)
Perng, J.K., Fisher, B., Hollar, S., Pister, K.S.J.: Acceleration Sensing Glove (ASG). In: Proc. International Symposium on Wearable Computers, pp. 178–180 (1999)
Kionix, Inc. USB Demo Board Kit User’s Manual. User’s manual, Kionix Inc. (2006)
Kortuem, G., Segall, Z., Bauer, M.: Context-Aware, Adaptive Wearable Computers as Remote Interfaces to Intelligent’ Environments. In: Proc. IEEE International Symposium on Wearable Computers, pp. 58–65. IEEE Computer Society Press, Los Alamitos (2000)
Thomas, B., Grimmer, K., Mackovec, D., Zucco, J., Gunther, B.: Determination of Placement of a Body-attached Mouse as a Pointing Device for Wearable Computers. In: Proc. International Symposium on Wearable Computers, pp. 193–194 (1999)
Ahn, H.J., Cho, M.H., Jung, M.J., Kim, Y.H., Kim, J.M., Lee, C.H.: UbiFOS: A Small Real-Time Operating System for Embedded Systems. ETRI Journal 29(3) (submitted for publication, 2007)
HTK Hidden Markov Model Toolkit home page, http://htk.eng.cam.ac.uk/
Khotake, N., Rekimoto, J., Anzai, Y.: InfoStick: an interaction device for Inter-Appliance Computing. In: Proc. International Symposium on Handheld and Ubiquitous Computing, pp. 246–258 (1999)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Cho, IY., Sunwoo, J., Son, YK., Oh, MH., Lee, CH. (2007). Development of a Single 3-Axis Accelerometer Sensor Based Wearable Gesture Recognition Band. In: Indulska, J., Ma, J., Yang, L.T., Ungerer, T., Cao, J. (eds) Ubiquitous Intelligence and Computing. UIC 2007. Lecture Notes in Computer Science, vol 4611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73549-6_5
Download citation
DOI: https://doi.org/10.1007/978-3-540-73549-6_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73548-9
Online ISBN: 978-3-540-73549-6
eBook Packages: Computer ScienceComputer Science (R0)