Skip to main content

Neural Control Interfaces

  • Chapter

Part of the book series: Human-Computer Interaction Series ((HCIS))

Abstract

The control interface is the primary component of a Brain-Computer Interface (BCI) system that provides user interaction. The control interface supplies cues for performing mental tasks, reports system status and task feedback, and often displays representations of the user’s brain signals. Control interfaces play a significant role in determining the usability of a BCI, and some of the traditional human-computer interaction design methods apply. However, the very specialized input methods and display paradigms of a BCI require consideration to create optimal usability for a BCI system. This chapter outlines some of the issues and challenges that make designing control interfaces for BCIs unique.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   149.00
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   109.99
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

Learn about institutional subscriptions

References

  • Achtman N, Afshar A, Santhanam G, Yu BM, Ryu SI, Shenoy KV (2007) Free-paced high-performance brain-computer interfaces. J Neural Eng 4(3):336–347

    Article  Google Scholar 

  • Allison B, Moore Jackson M (2005) Practical applications of brain computer interface systems using selective attention. Paper presented at the Human Computer Interaction International

    Google Scholar 

  • Allison B, Pineda J (2006) Effects of SOA and flash pattern manipulations on ERPs, performance, and preference: Implications for a BCI system. Int J Psychophysiol 59:127–140

    Article  Google Scholar 

  • Bin GY, Gao XR, Yan Z, Hong B, Gao SK (2009) An online multi-channel SSVEP-based brain-computer interface using a canonical correlation analysis method. J Neural Eng 6:046002

    Article  Google Scholar 

  • Birbaumer N (2006) Breaking the silence: Brain-computer interfaces (BCI) for communication and motor control. Psychophysiology 43(6):517–532

    Article  Google Scholar 

  • Borisoff JF, Mason SG, Birch GE (2006) Brain interface research for asynchronous control applications. IEEE Trans Neural Syst Rehabil Eng 14(2):160–164

    Article  Google Scholar 

  • Card S, Moran T, Newell A (1986) The Model Human Processor: An Engineering Model of Human Performance. Xerox Palo Alto Research Center (PARC), Palo Alto, CA

    Google Scholar 

  • Clancey W (1997) On Human Knowledge and Computer Representations. Press Syndicate of the University of Cambridge, Cambridge, UK

    Google Scholar 

  • Daly JJ, Wolpaw JR (2008) Brain-computer interfaces in neurological rehabilitation. Lancet Neurol 7(11):1032–1043

    Article  Google Scholar 

  • Farwell LA, Donchin E (1988) Talking off the top of your head—toward a mental prosthesis utilizing event-related brain potentials. Electroencephalogr Clin Neurophysiol 70(6):510–523

    Article  Google Scholar 

  • Felton EA, Lewis NL, Wills SA, Radwin RG, Williams JC (2007) Neural signal based control of the dasher writing system. Paper presented at the Neural Engineering, 2007. CNE ’07. 3rd International IEEE/EMBS Conference on

    Google Scholar 

  • Felton EA, Radwin RG, Wilson JA, Williams JC (2009) Evaluation of a modified Fitts law brain-computer interface target acquisition task in able and motor disabled individuals. J Neural Eng 6(5):56002

    Article  Google Scholar 

  • Foley JD, Van Dam A (1982) Fundamentals of Interactive Computer Graphics. Addison-Wesley Pub. Co, Reading, Mass.

    Google Scholar 

  • John B, Kieras D (1996) The GOMS family of user interface analysis techniques: Comparison and contrast. ACM Trans Comput Hum Interact 3(4):320–351

    Article  Google Scholar 

  • Lalor EC, Kelly SP, Finucane C, Burke R, Smith R, Reilly RB, et al. (2005) Steady-state VEP-based brain-computer interface control in an immersive 3D gaming environment. Eurasip J Appl Signal Process 2005(19):3156–3164

    Article  MATH  Google Scholar 

  • Mappus R, Venkatesh G, Shastry C, Israeli A, Moore Jackson M (2009) An fNIR-based BMI for letter construction using continuous control. Paper presented at the Computer Human Interface (SIGCHI)

    Google Scholar 

  • Mason SG, Birch GE (2003) A general framework for brain-computer interface design. IEEE Trans Neural Syst Rehabil Eng 11(1):70–85

    Article  Google Scholar 

  • Mason SG, Birch GE (2000) A brain-controlled switch for asynchronous control applications. IEEE Trans Biomed Eng 47(10):1297–1307

    Article  Google Scholar 

  • Mason SG, Kronegg J, Huggins J, Fatourechi M, Navarro K, Birch GE (2006) Evaluating the performance of self-paced brain computer interface technology

    Google Scholar 

  • McFarland DJ, Wolpaw JR (2003) EEG-based communication and control: Speed-accuracy relationships. Appl Psychophysiol Biofeedback 28(3):217–231

    Article  Google Scholar 

  • McFarland DJ, Sarnacki WA, Wolpaw JR (2003) Brain-computer interface (BCI) operation: Optimizing information transfer rates. Biol Psychol 63(3):237–251

    Article  Google Scholar 

  • McFarland DJ, Sarnacki WA, Vaughan TM, Wolpaw JR (2005) Brain-computer interface (BCI) operation: Signal and noise during early training sessions. Clin Neurophysiol 116(1):56–62

    Article  Google Scholar 

  • Millán JR, Mouriño J (2003) Asynchronous BCI and local neural classifiers: An overview of the adaptive brain interface project. IEEE Trans Neural Syst Rehabil Eng 11(2):159–161

    Article  Google Scholar 

  • Moore Jackson M, Mappus R, Barba E, Hussein S, Venkatesh G, Shastry C, et al (2009) Continuous control paradigms for direct brain interfaces. Paper presented at the Human Computer Interaction International

    Google Scholar 

  • Naito M, Michioka Y, Ozawa K, Ito Y, Kiguchi M, Kanazawa T (2007) A communication means for totally locked-in ALS patients based on changes in cerebral blood volume measured with near-infrared light. IEICE Trans Inf Syst E90-D7:1028–1036

    Article  Google Scholar 

  • Nardi B (1996) Context and Consciousness: Activity Theory and Human-Computer Interaction. MIT Press, Boston, MA

    Google Scholar 

  • Perelmouter J, Birbaumer N (2000) A binary spelling interface with random errors. IEEE Trans Rehabil Eng 8(2):227–232

    Article  Google Scholar 

  • Roberts AH (1985) Biofeedback—research, training, and clinical roles. Am Psychol 40(8):938–941

    Article  Google Scholar 

  • Salvaris M, Sepulveda F (2009) Visual modifications on the P300 speller BCI paradigm. J Neural Eng 6(4)

    Google Scholar 

  • Schalk G, McFarland DJ, Hinterberger T, Birbaumer N, Wolpaw JR (2004) BCI2000: A general-purpose, brain-computer interface (BCI) system. IEEE Trans Biomed Eng 51(6):1034–1043

    Article  Google Scholar 

  • Schalk G, Miller KJ, Anderson NR, Wilson JA, Smyth MD, Ojemann JG, et al. (2008) Two-dimensional movement control using electrocorticographic signals in humans. J Neural Eng 5(1):75–84

    Article  Google Scholar 

  • Scherer R, Müller-Putz GR, Pfurtscheller G (2007) Self-initiation of EEG-based brain-computer communication using the heart rate response. J Neural Eng 4:L23–L29

    Article  Google Scholar 

  • Scherer R, Lee F, Schlögl A, Leeb R, Bischof H, Pfurtscheller G (2008) Toward self-paced brain-computer communication: Navigation through virtual worlds. IEEE Trans Biomed Eng 55(2):675–682

    Article  Google Scholar 

  • Sellers E, Donchin E (2006) A P300-based brain-computer interface: Initial tests by ALS patients. Clin Neurophysiol 117:538–548

    Article  Google Scholar 

  • Shenoy P, Krauledat M, Blankertz B, Rao RP, Müller KR (2006) Towards adaptive classification for BCI. J Neural Eng 3(1):R13–23

    Article  Google Scholar 

  • Solis-Escalante T, Gentiletti GG, Yanez-Suarez O (2006) Single trial P300 detection based on the empirical mode decomposition. Conf Proc IEEE Eng Med Biol Soc 1:1157–1160

    Google Scholar 

  • Van Gerven M, Farquhar J, Schaefer R, Vlek R, Geuze J, Nijholt A, et al. (2009) The brain-computer interface cycle. J Neural Eng 6(4):1–10

    Article  Google Scholar 

  • Vaughan TM, McFarland DJ, Schalk G, Sarnacki W, Robinson L, Wolpaw JR (2001) EEG-based brain-computer interface: Development of a speller. Paper presented at the Society for Neuroscience

    Google Scholar 

  • Wolpaw JR, McFarland DJ, Vaughan TM, Schalk G (2003) The Wadsworth Center brain-computer interface (BCI) research and development program. IEEE Neural Syst Syst Rehabil Eng 11(2):203–207

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Melody Moore Jackson .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag London Limited

About this chapter

Cite this chapter

Moore Jackson, M., Mappus, R. (2010). Neural Control Interfaces. In: Tan, D., Nijholt, A. (eds) Brain-Computer Interfaces. Human-Computer Interaction Series. Springer, London. https://doi.org/10.1007/978-1-84996-272-8_2

Download citation

  • DOI: https://doi.org/10.1007/978-1-84996-272-8_2

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-84996-271-1

  • Online ISBN: 978-1-84996-272-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics