[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ Skip to main content

Advertisement

Springer Nature Link
Log in

Wireless Brain Computer Interface for Smart Home and Medical System

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

The number of aged and disabled people has been increasing worldwide. To look after these people is a big challenge in this era. However, scientists overcome the problems of handicapped people with the help of the latest communication technologies. The smart home and medical systems are a predominant concept in research and development, specially utilizing the brain-computer interface (BCI) technology to control the daily use appliances. BCI acquires the brain signals that transmit to a digital device for analyzing and interpreting into further command or action but this approach limits the communication range between the brain and the system and becomes bulky because of the wired interface of a brain with the system. Therefore, the main purpose of this research was to design and evaluate a system that empowered the immobilized, handicapped or elderly people to carry out their basic routine tasks wirelessly, for instance, operating home appliances and monitoring vital signs without any dependency. In addition, the subject should have a properly functioning brain and controlled with eye muscle movement. In this research work, wireless BCI (WBCI) technology that is a commercial electroencephalogram headset is used to control home and medical appliances such as a light bulb, a fan, a digital blood pressure monitor and an Infrared deep pain therapeutic belt for dependent people. An Android application is developed name “Smart Home Monitor” that monitors the data from the headset. The designed device is tested on younger (50-year-old) and older (> 50-year-old) individuals to achieve an attention level (0–100). The younger male reached attention level 74.78 within 26.20 s; quicker than younger female and older people. Overall, this research work is unique for the reason that it is suitable for all those people, whose brain and eye muscles are functional even if the rest of the body is paralyzed. This analysis evaluated WBCI device enables the system to be wireless, handy, portable and reliable. Thus, the whole system can be commercialized for immobilized or handicapped people to provide better care and facility at home. Especially, the disable people appreciated this system and want to see its implementation as soon as possible.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (United Kingdom)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Hundia, R. (2015). Brain computer interface-controlling devices utilizing the alpha brain waves. International Journal of Scientific and Technology Research, 4(1), 281–285.

    Google Scholar 

  2. Ferreira, A. L. S., de Miranda, L. C., de Miranda, E. E. C., & Sakamoto, S. G. (2013). A survey of interactive systems based on brain-computer interfaces. SBC Journal on Interactive Systems, 4(1), 3–13.

    Google Scholar 

  3. Leeb, R., Perdikis, S., Tonin, L., Biasiucci, A., Tavella, M., Creatura, M., et al. (2013). Transferring brain–computer interfaces beyond the laboratory: Successful application control for motor-disabled users. Artificial Intelligence in Medicine, 59(2), 121–132.

    Article  Google Scholar 

  4. Giovanni, Z., Maliheh, G., Eleonora, F., & Alberto, D. M. (2016). The smart home services diffusion process: A system dynamics model. In The 34th international conference of the system dynamics society, Delft, The Netherlands.

  5. Adair, B., Miller, K., Ozanne, E., Hansen, R., Pearce, A. J., Santamaria, N., et al. (2013). Smart-home technologies to assist older people to live well at home. Journal of Aging Science, 1(1), 1–9.

    Google Scholar 

  6. Sanei, S., & Chambers, J. A. (2013). EEG signal processing. New York: Wiley.

    Google Scholar 

  7. Yuan, H., & He, B. (2014). Brain–computer interfaces using sensorimotor rhythms: current state and future perspectives. IEEE Transactions on Biomedical Engineering, 61(5), 1425–1435.

    Article  Google Scholar 

  8. Amiri, S., Rabbi, A., & Azinfar, L. (2013). A review of P300 SSVEP and hybrid P300/SSVEP brain-computer interface systems. In Brain-Computer Interface Systems—Recent Progress and Future Prospects (pp. 195–209).

  9. Graimann, B., Allison, B. Z., & Pfurtscheller, G. (Eds.). (2010). Brain-computer interfaces: Revolutionizing human-computer interaction. Berlin: Springer.

    Google Scholar 

  10. Lee, W. T., Nisar, H., Malik, A. S., & Yeap, K. H. (2013). A brain computer interface for smart home control. In IEEE 17th international symposium on consumer electronics (ISCE) (pp. 35–36).

  11. Abin, K. T. & Ramachandraiah, U. (2015). Brain computer interface based smart living environmental auto adjustment control system using internet of things (Iot) networking. International Journal of Emerging Technology in Computer Science and Electronics (IJETCSE), 13(1), 360–366.

    Google Scholar 

  12. Wang, Y. T., Wang, Y., & Jung, T. P. (2010). A cell-phone based brain-computer interface for communication in daily life. AICI 2010, Part II, LNAI, 6320, 233–240.

    Google Scholar 

  13. Liao, L. D., Chen, C. Y., Wang, I. J., Chen, S. F., Li, S. Y., Chen, B. W., et al. (2012). Gaming control using a wearable and wireless EEG-based brain-computer interface device with novel dry foam-based sensors. Journal of Neuroengineering and Rehabilitation. https://doi.org/10.1186/1743-0003-9-5.

    Google Scholar 

  14. Nicolas-Alonso, L. F., & Gomez-Gil, J. (2012). Brain computer interfaces, a review. Sensors, 12(2), 1211–1279.

    Article  Google Scholar 

  15. Rao, T. K., Lakshmi, M. R., & Prasad, T. V. (2012). An exploration on brain computer interface and its recent trends. International Journal of Advanced Research in Artificial Intelligence, 1(8), 17–22.

    Google Scholar 

  16. Abdulkader, S. N., Atia, A., & Mostafa, M. S. M. (2015). Brain computer interfacing: Applications and challenges. Egyptian Informatics Journal, 16(2), 213–230.

    Article  Google Scholar 

  17. Arafat, I. (2013). Brain-computer interface: Past, present & future. International Islamic University Chittagong (IIUC), Chittagong, Bangladesh. http://s3.amazonaws.com/academia.edu.documents/8502113/Update_bci_research_for_international_conference_by_arafat.pdf. Accessed Sept 02, 2018.

  18. Hassib, M., & Schneegass, S. (2015). Brain computer interfaces for mobile interaction: Opportunities and challenges. In Proceedings of the 17th international conference on human-computer interaction with mobile devices and services adjunct (pp. 959–962).

  19. Deshmukh, G. S., Rathod, B. P., Zagade, T. S., Parkhe, N. D., & Waghmare, P. L. (2014). Human thought controlled electrical switching using fast Fourier transform. International Journal of Advanced Research in Computer and Communication Engineering, 3(12), 8762–8765.

    Article  Google Scholar 

  20. Dobosz, K., & Wittchen, P. (2015). Brain-computer interface for mobile devices. Journal of Medical Informatics and Technologies, 24, 215–222.

    Google Scholar 

  21. Tseng, K. C., Lin, B. S., Wong, A. M. K., & Lin, B. S. (2015). Design of a mobile brain computer interface-based smart multimedia controller. Sensors, 15(3), 5518–5530.

    Article  Google Scholar 

  22. Lin, J. S., & Hsieh, C. H. (2014). A BCI control system for TV channels selection. International Journal of Communications, 3, 71–75.

    Google Scholar 

  23. Huang, D., Qian, K., Fei, D. Y., Jia, W., Chen, X., & Bai, O. (2012). Electroencephalography (EEG)-based brain–computer interface (BCI): A 2-D virtual wheelchair control based on event-related desynchronization/synchronization and state control. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 20(3), 379–388.

    Article  Google Scholar 

  24. Kaysa, W. A., & Widyotriatmo, A. (2013). Design of brain-computer interface platform for semi real-time commanding electrical wheelchair simulator movement. In Proceedings of the 2013 3rd international conference on instrumentation control and automation (ICA) (pp. 39–44). IEEE.

  25. Lin, J. S., & Yang, W. C. (2012). Wireless brain-computer interface for electric wheelchairs with EEG and eye-blinking signals. International Journal of Innovative Computing, Information and Control, 8(9), 6011–6024.

    Google Scholar 

  26. Alshbatat, A. I. N., Vial, P. J., Premaratne, P., & Tran, L. C. (2014). EEG-based brain-computer interface for automating home appliances. Journal of Computers, 9(9), 2159–2166.

    Article  Google Scholar 

  27. Munir, M. W., Shahid, N., Omair, S. M., Munir, G., & Haque, M. U. (2017). Comparative investigation of remote tracking devices for aging care. International Journal of Information Technology (Springer), 9(3), 261–266.

    Article  Google Scholar 

Download references

Acknowledgements

We dedicate this research work to our co-author Mr. Talha Rafi, who is no more among us. We will be thankful to Syed Muhammad Omair and Hira Sohail for their guidance and support in carrying out this research work.

Author information

Authors and Affiliations

  1. Biomedical Engineering Department, Sir Syed University of Engineering and Technology, Karachi, Pakistan

    Syed Rehan Abbas Jafri, Tehreem Hamid, Rabia Mahmood, Muhammad Asjad Alam & Talha Rafi

  2. Department of Biomedical Engineering, Barrett Hodgson University, The Salim Habib Campus, NC-24 Deh Dih, Korangi Creek, Karachi, 74900, Pakistan

    Muhammad Zeeshan Ul Haque & Muhammad Wasim Munir

Authors
  1. Syed Rehan Abbas Jafri
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tehreem Hamid
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Rabia Mahmood
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Muhammad Asjad Alam
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Talha Rafi
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Muhammad Zeeshan Ul Haque
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Muhammad Wasim Munir
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Muhammad Wasim Munir.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jafri, S.R.A., Hamid, T., Mahmood, R. et al. Wireless Brain Computer Interface for Smart Home and Medical System. Wireless Pers Commun 106, 2163–2177 (2019). https://doi.org/10.1007/s11277-018-5932-x

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-018-5932-x

Keywords

Search

Navigation