Skip to main content

Control of Smart Environments Using Brain Computer Interface Based on Genetic Algorithm

  • Conference paper
Intelligent Information and Database Systems (ACIIDS 2016)

Abstract

This work deals with the development of an interface to control a smart conference room using passive BCI (Brain Computer Interface). It compares a genetic algorithm developed in a previous project to control the smart conference room with a random control algorithm. The system controls features of the conference room such as air conditioner, lightning systems, electric shutters, entertainment devices, etc. The parameters of the algorithm are extracted from users biosignal using Emotiv Epoc Headset while the user performs an attention test. The tests indicate that the decisions made by the genetic algorithm lead to better results, but in a single execution cannot be considered an effective optimization algorithm.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight 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. Bäck, T.: Evolutionary Algorithms in Theory and Practice: Evolution Strategies, Evolutionary Programming, Genetic Algorithms. Oxford University Press, Oxford (1996)

    MATH  Google Scholar 

  2. Girouard, A.: Adaptive brain-computer interface. In: CHI 09 Extended Abstracts on Human Factors in Computing Systems (CHI EA 2009), USA. ACM (2009)

    Google Scholar 

  3. Zander, T.O., Kothe, C., Welke, S., Roetting, M.: Utilizing Secondary Input from Passive Brain-Computer Interfaces for Enhancing Human-Machine Interaction. Springer, Heidelberg (2009)

    Book  Google Scholar 

  4. Schmidt, A., et al.: Enabling implicit human computer interaction: a wearable RFID-tag reader. In: ISWC, USA. IEEE Computer Society (2000)

    Google Scholar 

  5. George, L., Lcuyer, A.: An overview of research on passive brain-computer interfaces for implicit human-computer interaction. In: ICABB 2010-Workshop W1 (2010)

    Google Scholar 

  6. Whitley, D.: A Genetic Algorithm Tutorial, Computer Science Department, Colorado State University (1989)

    Google Scholar 

  7. Sivanandam, S.N., Deepa, S.N.: Introduction to Genetic Algorithms. Springer, Heidelberg (2008)

    MATH  Google Scholar 

  8. Cutrell, E., Tan, D.: BCI for Passive Input in HCI. Microsoft Research, USA (2008)

    Google Scholar 

  9. Ruscher, G., Kruger, F., Bader, S., Kirste, T.: Controlling smart environments using brain computer interface. In: Proceedings of the 2nd Workshop on Semantic Models for Adaptive Interactive Systems, SEMAIS 2011 (2011)

    Google Scholar 

  10. Haupt, L., Haupt, S.E.: Optimum population size and mutation rate for a simple real genetic algorithm that optimizes array factors. Appl. Comput. Electromagn. Soc. J. 15(2), 92–102 (2000)

    Google Scholar 

  11. Menezes, M., Pereira, C.: Proposed Use of Passive Brain-Computer Interface. Universidade Federal do Rio Grande do Sul (UFRGS) Porto Alegre, RS/Brazil (2015)

    Google Scholar 

  12. Emotiv Software Research Kit User Manual. Emotiv Systems (2014)

    Google Scholar 

  13. Schettini, F., et al.: Assistive device with conventional, alternative, and brain-computer interface inputs to enhance interaction with the environment for people with amyotrophic lateral sclerosis: a feasibility and usability study. Arch. Phys. Med. Rehab. 96(3), S46–S53 (2014)

    Article  Google Scholar 

  14. Neuman, M.R.: Biopotential amplifiers. In: Webster, J.G. (ed.) Medical Instrumentation, pp. 227–288. John Wiley and Sons, New York (1995)

    Google Scholar 

  15. Edlinger, G., Holzner, C., Guger, C.: A hybrid brain-computer interface for smart home control. In: Jacko, J.A. (ed.) Human-Computer Interaction, Part II, HCII 2011. LNCS, vol. 6762, pp. 417–426. Springer, Heidelberg (2011)

    Google Scholar 

  16. Zich, C., De Vos, M., Kranczioch, C., Debener, S.: Wireless EEG with individualized channel layout enables efficient motor imagery training. Clin. Neurophysiol. 126(4), 698–710 (2015)

    Article  Google Scholar 

  17. Castermans, T.: Detecting Biosignals with Emotiv EPOC headset: a critical review. Universit de Mons, web presentation (2011). http://tinyurl.com/p587qr7

  18. Cook, D., Das, S.: Smart Environments. Wiley, New York (2005)

    Google Scholar 

  19. Ducatel, K., et al.: Scenarios for ambient intelligence (ISTAG Report). Institute for Prospective Technological Studies (European Commission), Seville (2001)

    Google Scholar 

  20. Lin, C.-T., Lin, F.-C., Chen, S.-A., Lu, S.-W., Chen, T.-C., Ko, L.-W.: EEG-based brain-computer interface for smart living environmental auto-adjustment. J. Med. Biol. Eng. 30, 237–245 (2010)

    Article  Google Scholar 

  21. Ramirez-Atencia, C., et al.: A hybrid MOGA-CSP for multi-UAV mission planning. In: GECCO (2015)

    Google Scholar 

  22. Ramrez-Atencia, C., Bello-Orgaz, G., R-Moreno, M.D., Camacho, D.: Branching to find feasible solutions in unmanned air vehicle mission planning. In: Corchado, E., Lozano, J.A., QuintiĂ¡n, H., Yin, H. (eds.) IDEAL 2014. LNCS, vol. 8669, pp. 286–294. Springer, Heidelberg (2014)

    Google Scholar 

Download references

Acknowledgment

The authors would like to thank the Home Systems Company, as well as the Brazilian research agencies Capes (project PROCAD), FINEP (project CRIAI) and CNPq for their financial support.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Guilherme Antonio Camelo .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Camelo, G.A., Menezes, M.L., Sant’Anna, A.P., Vicari, R.M., Pereira, C.E. (2016). Control of Smart Environments Using Brain Computer Interface Based on Genetic Algorithm. In: Nguyen, N.T., Trawiński, B., Fujita, H., Hong, TP. (eds) Intelligent Information and Database Systems. ACIIDS 2016. Lecture Notes in Computer Science(), vol 9622. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49390-8_75

Download citation

  • DOI: https://doi.org/10.1007/978-3-662-49390-8_75

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-49389-2

  • Online ISBN: 978-3-662-49390-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics