JRM Vol.22 No.4 pp. 439-446
doi: 10.20965/jrm.2010.p0439


Electric Wheelchair Controlled by Human Body Motion -Classification of Body Motion and Improvement of Control Method-

Sho Yokota*, Hiroshi Hashimoto**, Yasuhiro Ohyama***,
and Jinhua She***

*Faculty Science and Engineering, Setsunan University

**Advanced Institute Industrial Technology

***School of Computer Science, Tokyo University of Technology

January 3, 2010
April 15, 2010
August 20, 2010
interface, wheelchair, human body motion, self-organizing map, SD-method

This paper classifies human body movements when an electric wheelchair was controlled using a Human Body Motion Interface (HBMI) by a Self-Organizing Map (SOM) and proposes control based on classification results. The Human Body Motion Interface (HBMI) uses body movement following voluntary motion. This study focuses on electric wheelchair control as an application of the HBMI. The viability of the HBMI was confirmed using Center Of Weight (C.O.W.) from pressure distribution information on backrest in the wheelchair to control it. If body movement concentrated on a single point at C.O.W. in pressure distribution, a problem occurred because the system would recognize even different body-movement patterns as the same movement. We call body movement taking the same C.O.W. even if it has a different body-movement pattern movement confusion. We solve the movement confusion problem and enhance wheelchair control, classifying body movement using the SOM and reflecting this classification result to improve wheelchair control. Experimental results showed that movement confusion is solved and wheelchair control improved.

Cite this article as:
Sho Yokota, Hiroshi Hashimoto, Yasuhiro Ohyama, and
and Jinhua She, “Electric Wheelchair Controlled by Human Body Motion -Classification of Body Motion and Improvement of Control Method-,” J. Robot. Mechatron., Vol.22, No.4, pp. 439-446, 2010.
Data files:
  1. [1] J. Kono and J. Inada, “Special Characteristics of Tooth Brushing Movement in Elementary School and the Elderly,” The Japanese Society for Dental Health, Vol.58, No.3(19950625), pp. 91-92, 1995. (in Japanese)
  2. [2] R. C. Simpon and S. P. Levine, “Adaptive shared control of a smart wheelchair operated by voice control,” Proc. of IEEE Int. Conf. Intelligent Robots and Systems, pp. 622-626, 1997.
  3. [3] Y. Ichinose, M. Wakumoto, K. Honda, T. Azuma, and J. Sato, “Human Interface Using a Wireless Tongue-Palate Contact Pressure Sensor System and Its Application to the Control of an Electric Wheelchair,” The Trans. of the Institute of Electronics, Information and Communication Engineers, Vol.J86-D-II, No.2, pp. 364-367, 2003. (in Japanese)
  4. [4] I. Moon, M. Lee, J. Chu, and M. Mun, “Wearable EMG-based HCI for Electric-Powered Wheelchair Users with Motor Disabilities,” Proc. of the 2005 IEEE Int. Conf. on Robotics and Automation, pp. 2649-2654, 2005.
  5. [5] M. Kamata, H. Nishino, H. Yoshida, T. Someya, and M. Suzuki, “Development of a Wheelchair of Head Operation with Gyro Sensor,” JSME Proc. of the Welfare Engineering Symposium 2001, p. 420, 2001. (in Japanese)
  6. [6] T. Kigoshi et al., “Electric wheelchair control with eye position and face inclination,” Technical report of IEICE (ISSN:09135685), Vol.107, No.72(20070518), pp. 13-16, 2007.
  7. [7] S. Yokota, Y. Ohyama, H. Hashimoto, and J.-H. She, “The Electric Wheelchair Controlled by Human Body Motion –Design of the prototype and basic experiment–”, Proc. of the 17th IEEE Int. Symposium on Robot and Human Interactive Communication ROMAN2008, pp. 303-308, 2008.
    ISBN: 987-1-42442213-5
  8. [8] S. Yokota, H. Hashimoto, Y. Ohyama, and J.-H. She, “Electric Wheelchair Controlled by Human Body Motion Interface,” IEEJ Trans. EIS, Vol.129, No.10, pp. 1874-1880, 2009. (in Japanese)
  9. [9] T. Kohonen, “Self-Organizing Maps,” Springer, 1997.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Mar. 05, 2021