Skip to main content

Internet of Things Based Gesture Controlled Wheel Chair for Physically Disabled

  • Conference paper
  • First Online:
Intelligent Computing Paradigm and Cutting-edge Technologies (ICICCT 2020)

Part of the book series: Learning and Analytics in Intelligent Systems ((LAIS,volume 21))

  • 371 Accesses

Abstract

A gesture-controlled wheelchair is beneficial to a physically disabled person. Though there is an incredible leap in the field of wheelchair technology, these advances haven’t been able to help steer wheelchair unaided—the wheelchair which can be operated by effortless hand signals. The user can control the wheelchair using the have movements and construes the motion calculated by the user and directs the wheelchair accordingly. It also aims at making the system wireless by using ZigBee that creates a personal area network for transfer of data wirelessly.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Saharia, T., Bauri, J., & Bhagabati, C. (2017). Joystick controlled wheelchair. International Research Journal of Engineering and Technology (IRJET), 4, 235–237.

    Google Scholar 

  2. Gulati, S., & Kuipers, B. (2008). High-performance control for the graceful motion of an intelligent wheelchair. In IEEE International Conference on Robotics and Automation, May 19–23, Pasadena, CA, USA (pp. 3932–3938).

    Google Scholar 

  3. Kumar, S., & Raja, P. (2015). Ultrasonic sensor with accelerometer based smart wheel chair using microcontroller. International Research Journal of Engineering and Technology (IRJET), 2(09), 537–543.

    Google Scholar 

  4. Meeravali, S., & Aparna, M. (2013). Design and development of a hand-glove controlled wheel chair based on MEMS. International Journal of Engineering Trends and Technology (IJETT), 4(8), 3706–3712.

    Google Scholar 

  5. Singh, A., Kumar, D., Srikanth, P., Karanam, S., & Acharya, N. (2012). An Intelligent multi-gesture spotting robot to assist persons with disabilities. International Journal of Computer Theory and Engineering, 4(6), 998.

    Article  Google Scholar 

  6. Sinha, U., & Kanthi, M. (2016). Mind controlled wheelchair. International Journal of Control Theory and Applications, 9(39), 19–28.

    Google Scholar 

  7. Chen, Y. L. (2001). Application of tilt sensors in human-computer mouse interface for people with disabilities. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 9(3), 289–294.

    Article  Google Scholar 

  8. Gray, J. O., Jia, P., Hu, H. H., Lu, T., & Yuan, K. (2007). Head gesture recognition for hands-free control of an intelligent wheelchair. Industrial Robot: An International Journal, 34(1), 60–68.

    Article  Google Scholar 

  9. Yanco, H. A., Hazel, A., Peacock, A., Smith, S., & Wintermute, H. (1995). An initial report on Wheelesley: A robotic wheelchair system. In International Joint Conference on Artificial Intelligence, August, Montreal, Canada (pp. 1–5).

    Google Scholar 

  10. Simpson, R., LoPresti, E., Hayashi, S., Nourbakhsh, I., & Miller, D. (2004). The smart wheelchair component system. Journal of Rehabilitation Research & Development, 41(38), 429–442.

    Article  Google Scholar 

  11. Röfer, T., & Lankenau, A. (2000). Architecture and applications of the Bremen Autonomous Wheelchair. Information Sciences, 126(1–4), 1–20.

    Article  Google Scholar 

  12. Rao, R. S., Conn, K., Jung, S. H., Katupitiya, J., Kientz, T., Kumar, V., et al. (2002). Human robot interaction: Application to smart wheelchairs. In IEEE International Conference on Robotics and Automation (Cat. No. 02CH37292), May 11–15, Washington, DC, USA (Vol. 4, pp. 3583–3588).

    Google Scholar 

  13. Prassler, E., Scholz, J., Strobel, M., & Fiorini, P. (1999). MAid: A robotic wheelchair operating in public environments. In Sensor based intelligent robots (pp. 68–95). Berlin, Heidelberg: Springer.

    Google Scholar 

  14. Nakanishi, S., Kuno, Y., Shimada, N., & Shirai, Y. (1999). Robotic wheelchair based on observations of both user and environment. In IEEE/RSJ International Conference on Intelligent Robots and Systems. Human and Environment Friendly Robots with High Intelligence and Emotional Quotients (Cat. No. 99CH36289), October 17–21 (Vol. 2, pp. 912–917).

    Google Scholar 

  15. Levine, S. P., Bell, D. A., Jaros, L. A., Simpson, R. C., Koren, Y., & Borenstein, J. (1999). The NavChair assistive wheelchair navigation system. IEEE Transactions on Rehabilitation Engineering, 7(4), 443–451.

    Article  Google Scholar 

  16. Gomi, T., & Griffith, A. (1998). Developing intelligent wheelchairs for the handicapped. In Assistive Technology and Artificial Intelligence (Vol. 1458, pp. 150–178). Berlin, Heidelberg: Springer.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to B. Prabadevi .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Miharia, A., Prabadevi, B., Rajagopal, S., Alhadidi, B. (2021). Internet of Things Based Gesture Controlled Wheel Chair for Physically Disabled. In: Favorskaya, M.N., Peng, SL., Simic, M., Alhadidi, B., Pal, S. (eds) Intelligent Computing Paradigm and Cutting-edge Technologies. ICICCT 2020. Learning and Analytics in Intelligent Systems, vol 21. Springer, Cham. https://doi.org/10.1007/978-3-030-65407-8_9

Download citation

Publish with us

Policies and ethics