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JACIII Vol.14 No.7 pp. 784-792
doi: 10.20965/jaciii.2010.p0784
(2010)

Paper:

Directional Intention Identification for Running Control of an Omnidirectional Walker

Yinlai Jiang*, Shuoyu Wang*, Kenji Ishida**, Takeshi Ando***,
and Masakatsu G. Fujie***

*Department of Intelligent Mechanical Systems Engineering, Kochi University of Technology, 185 Miyanokuti, Tosayamada, Kami, Kochi 782-8502, Japan

**Department of Physical Medicine and Rehabilitation, Kochi University, 2-5-1 Akebono-cho, Kochi 780-8520, Japan

***Department of Modern Mechanical Engineering, Waseda University, 59-309, 3-4-1 Okubo, Shinjyuku, Tokyo 169-8555, Japan

Received:
April 15, 2010
Accepted:
July 28, 2010
Published:
November 20, 2010
Keywords:
walking support, omnidirectional walker, directional intention identification, distance-type fuzzy reasoning method, knowledge radius
Abstract
Walking is a vital exercise for health promotion and a fundamental ability necessary for everyday life. In previous work, we developed an OmniDirectional Walker (ODW) for walking rehabilitation and walking support. In walking support, it is necessary for the ODW to know the direction the user intends to go based on user manipulation. Actual directional intent must, however, be identified from physical manipulation because a user’s directional intent and physical manipulation are not always mutually consistent. In this paper, a novel interface is proposed to recognize a user’s directional intention according to the forearm pressures exerted to the ODW by the user with wrists and elbows. The forearm pressures are measured by 4 sensors embedded in the ODW’s armrest. The relationship between forearm pressure and directional intention was extracted as fuzzy rules and an algorithm was proposed for directional intention identification based on distance-type fuzzy reasoning method. The effectiveness of the algorithm was verified by experimental reasoning results demonstrated to be consistent with intended directions.
Cite this article as:
Y. Jiang, S. Wang, K. Ishida, T. Ando, and M. Fujie, “Directional Intention Identification for Running Control of an Omnidirectional Walker,” J. Adv. Comput. Intell. Intell. Inform., Vol.14 No.7, pp. 784-792, 2010.
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References
  1. [1] D. Chugo, W. Matsuoka, S. Jia, and K. Takase, “Rehabilitation Walker with Standing-Assistance Device,” J. of Robotics and Mechatronics, Vol.19, No.6, pp. 604-611, 2007.
  2. [2] C. Y. Lee and J. J. Lee, “Walking-support robot system for walking rehabilitation: design and control,” Artificial Life and Robotics, Vol.4, No.4, pp. 206-211, 2006.
  3. [3] S. Wang, H. Guo, K. Kawata, Y. Inoue, M. Nagano, K. Ishida, and T. Kimura, “Development of Omni-directional Mobile Walker for Rehabilitation,” The JSME Symposium on Welfare Engineering, pp. 11-12, 2004 (in Japanese).
  4. [4] K. Ishida, S.Wang, M. Nagano, and K. Kishi, “The effectiveness of rehabilitation using an omni-directional walker,” Sports and Physical Therapy, Vol.19, No.4, pp. 246-250, 2008 (in Japanese).
  5. [5] Y. Wang and S. Makeig, “Predicting Intended Movement Direction Using EEG from Human Posterior Parietal Cortex,” Proc. of the 5th Int. Conf. on Foundations of Augmented Cognition, pp. 437-446, 2009.
  6. [6] C. Vidaurre, A. Schlögl, R. Cabeza, R. Scherer, and G. Pfurtscheller, “A fully on-line adaptive BCI,” IEEE Trans. on Biomedical Engineering, Vol.53, No.6, pp. 1214-1219, 2006.
  7. [7] J. N. Mak and J. R. Wolpaw, “Clinical Applications of Brain – Computer Interfaces: Current State and Future Prospects,” IEEE Reviews in Biomedical Engineering, Vol.2, pp. 187-199, 2009.
  8. [8] S. Wang, T. Tsuchiya, and M. Mizumoto, “Distance-Type Fuzzy Reasoning Method,” J. of Biomedical Fuzzy Systems Association, Vol.1, No.1, pp. 61-78, 1999 (in Japanese).
  9. [9] R. R. Yager and D. P. Filev, “Essentials of Fuzzy Modeling and Control,” Wiley-Interscience, 1994.
  10. [10] E. H. Mamdani, “Applications of Fuzzy Algorithms for Control of Simple Dynamic Plant,” Proc. of IEEE, Vol.121, No.12, pp. 1585-1588, 1974.
  11. [11] T. Takagi and M. Sugeno, “Fuzzy Identification of Systems and its Applications to Modeling and Control,” IEEE Trans. on Systems, Man, and Cybernetics, 1985.
  12. [12] C. Lee, “Fuzzy Logic in Control Systems:Fuzzy Logic Controller,” Parts I and II, IEEE Trans. on Systems, Man and Cybernetics, Vol.20, No.2, pp. 404-432, 1990.
  13. [13] S. Wang, T. Tsuchiya, and M. Mizumoto, “A Learning Algorithm for Distance-type Fuzzy Reasoning Method,” Biomedical Soft Computing and Human Sciences, Vol.6, No.1, pp. 61-68, 2000.
  14. [14] T. Shang and S. Wang, “A Novel Imitation Approach on Human’s Obstacle Avoidance Ability Considering Knowledge Radius,” Proc. of 2005 IEEE Int. Conf. on Robotics and Biomimetics, pp. 736-741, 2005.
  15. [15] T. Shang and S. Wang, “An Identification Method of Knowledge Radius for the Imitation of Human’s Action Strategy,” Proc. of Intelligent System Symposium, pp. 453-458, 2005 (in Japanese).
  16. [16] O. Chuy Jr., Y. Hirata, and K. Kosuge, “A New Control Approach for a Robotic Walking Support System in Adapting User Characteristics,” IEEE Trans. on Systems, Man, and Cybernetics, Vol.36, No.6, pp. 725-733, 2006.

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