Enhancing Wheelchair’s Control Operation of a Severe Impairment User

  • Mohd Razali Md TomariEmail author
  • Yoshinori Kobayashi
  • Yoshinori Kuno
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 291)


Users with severe motor ability are unable to control their wheelchair using standard joystick and hence an alternative control input is preferred. However, using such an input, undoubtedly the navigation burden for the user is significantly increased. In this paper a method on how to reduce such a burden with the help of smart navigation platform is proposed. Initially, user information is inferred using an IMU sensor and a bite-like switch. Then information from the environment is obtained using combination of laser and Kinect sensors. Eventually, both information from the environment and the user is analyzed to decide the final control operation that according to the user intention, safe and comfortable to the people in the surrounding. Experimental results demonstrate the feasibility of the proposed approach.


Wheelchair Severe impairment user Control operation 


  1. 1.
    Simpson RC, LoPresti EF, Cooper RA (2008) How many people would benefit from a smart wheelchair? J Rehabil Res Dev 45(1):53–72CrossRefGoogle Scholar
  2. 2.
    Simpson RC (2005) Smart wheelchairs: a literature review. J Rehabil Res Dev 42(4):423–436CrossRefGoogle Scholar
  3. 3.
    Grasse R, Morere Y, Pruski A (2010) Assisted navigation for person with reduced mobility: path recognition through particle filtering (condensation algorithm). J Intell Robot Syst 60:19–57CrossRefzbMATHGoogle Scholar
  4. 4.
    Cowan RE, Fregly BJ, Boninger ML, Chan L, Rodgers MM, Reikensmeyer DJ (2012) Recent trends in assistive technology for mobility. J NeuroEng Rehabil 9:20CrossRefGoogle Scholar
  5. 5.
    Bates RA (2002) Computer input device selection methodology for users with high-level spinal cord injuries. In: Proceeding of the 1st Cambridge workshop on universal access and assistive technologyGoogle Scholar
  6. 6.
    Fehr L, Langbein W, Skaar S (2000) Adequacy of power wheelchair control interfaces for persons with severe disabilities: a clinical survey. J Rehabil Res Dev 37(3):353–360Google Scholar
  7. 7.
    Wan LM, Tam E (2010) Power wheelchair assessment and training for people with motor impairment. In: Proceedings of 12th international conference on mobility and transport for elderly and disabled personGoogle Scholar
  8. 8.
    Perrin X (2009) Semi-autonomous navigation of an assistive robot using low throughput interfaces. PhD Thesis, ETH ZurichGoogle Scholar
  9. 9.
    Nisbet PD (2002) Who’s intelligent? wheelchair, driver or both? In: Proceedings of IEEE international conference on control and application, pp 760–765Google Scholar
  10. 10.
    Tomari R, Kobayashi Y, Kuno Y (2012) Empirical framework for autonomous wheelchair systems in human-shared environments. In: Proceedings of IEEE international conference on mechatronic and automation (ICMA), pp 493–498Google Scholar
  11. 11.
    Tomari R, Kobayashi Y, Kuno Y (2013) Enhancing wheelchair maneuverability for severe impairment user. Int J Adv Robot Syst 10:1–13CrossRefGoogle Scholar
  12. 12.
    Ulrich I, Borenstein J (1998) VFH+: reliable obstacle avoidance for fast mobile robots. In: Proceedings of IEEE international conference on robotics and automation, pp 1572–1577Google Scholar

Copyright information

© Springer Science+Business Media Singapore 2014

Authors and Affiliations

  • Mohd Razali Md Tomari
    • 1
    Email author
  • Yoshinori Kobayashi
    • 2
    • 3
  • Yoshinori Kuno
    • 2
  1. 1.Advanced Mechatronics Research Group (ADMIRE), Department of Mechatronics and Robotics Engineering, Faculty of Electrical and Electronic EngineeringUniversiti Tun Hussein Onn MalaysiaParit Raja, Batu PahatMalaysia
  2. 2.Graduate School of Science and EngineeringSaitama UniversitySakura-KuJapan
  3. 3.Japan Science Technology AgencyPRESTOSaitamaJapan

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