Skip to main content
SpringerLink
Log in

BCI-Based Expressive Arts: Moving Toward Mind-Body Alignment

  • Chapter
  • First Online:
Brain Art

Abstract

The aim of this chapter is to review the state of the art of BCI-based expressive arts, and review the possibilities as well as challenges involved in artistic expression and therapeutic applications of BCIs. We introduce the field of artistic BCI, its history, most common taxonomies and points of intersection with expressive arts-based therapies. We then discuss matching the artistic BCI technologies with different modalities of art-based interventions, and with different client categories, with the focus on mind-body alignment. We will conclude with a list of open problems and recommendations crucial for establishing a beneficial impact of BCI technology on artistic expression and therapeutic efforts.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
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

References

  • Aparicio A (2015) Immobilis in mobili: performing arts, BCI, and locked-in syndrome. Brain Comput Interfaces 2(2–3):150–159. https://doi.org/10.1080/2326263x.2015.1100366

    Article  Google Scholar 

  • Aparicio A, Cádiz RF (2017) Wheels within wheels: brain-computer interfaces as tools for artistic practice as research. Augmented cognition. In: Schmorrow D., Fidopiastis C (eds) Augmented cognition. Enhancing cognition and behavior in complex human environments. AC 2017. Lecture notes in computer science, vol 10285. Springer, Cham, pp 266–281

    Google Scholar 

  • Barnstaple RE (2017) Movement in mind: dance, self-awareness and sociality—an investigation of dance as treatment/therapy. Dissertation, York University

    Google Scholar 

  • Bearss KA et al (2017) Improvements in balance and gait speed after a 12 week dance intervention for Parkinsons disease. Adv Integr Med 4(1):10–13. https://doi.org/10.1016/j.aimed.2017.02.002

    Article  Google Scholar 

  • Belkofer CM (2012) The impact of visual art making on the brain. Dissertation, Lesley University

    Google Scholar 

  • Blum T (1989) Review: biofeedback and the arts: results of early experiments by David Rosenboom. Comput Music J 13:86–88

    Google Scholar 

  • Botrel L et al (2015) Brain painting V2: evaluation of P300-based brain-computer interface for creative expression by an end-user following the user-centered design. Brain Comput Interfaces 2(2–3):135–149. https://doi.org/10.1080/2326263x.2015.1100038

    Article  Google Scholar 

  • Brouwer A et al (2015) Using neurophysiological signals that reflect cognitive or affective state: six recommendations to avoid common pitfalls. Front Neurosci 9. https://doi.org/10.3389/fnins.2015.00136

  • Contreras-Vidal JL et al (2017) Towards a whole body brain-machine interface system for decoding expressive movement intent challenges and opportunities. In: 5th international winter conference on brain-computer interface, BCI 2017. Institute of Electrical and Electronics Engineers Inc., pp 1–4. https://doi.org/10.1109/iww-bci.2017.7858142

  • Crawford C, Cioli N, Holloman A (2018) NeuroBrush: a competitive, artistic multi-modal BCI application. In: Conference: CHI: artistic BCI workshop

    Google Scholar 

  • Cruz-Garza JG (2014) Neural decoding of expressive human movement from scalp electroencephalography (EEG). Front Hum Neurosci 8. https://doi.org/10.3389/fnhum.2014.00188

  • Daly I (2018) Affective brain–computer interfacing and methods for affective state detection. In: Nam C et al (eds) Brain-computer interfaces handbook: technological and theoretical advances. CRC Press, Taylor & Francis Group, Boca Raton, FL, pp 147–163

    Google Scholar 

  • Daly I et al (2016) Affective brain-computer music interfacing. J Neural Eng 13(4):046022. https://doi.org/10.1088/1741-2560/13/4/046022

    Article  Google Scholar 

  • Eaton J, Miranda E (2013) BCMI systems for musical performance. In: 10th international symposium on computer music multidisciplinary research, sound, music motion

    Google Scholar 

  • Eaton J et al (2015) The space between us: evaluating a multi-user affective brain-computer music interface. Brain Comput Interfaces 2(2–3):103–116. https://doi.org/10.1080/2326263x.2015.1101922

    Article  Google Scholar 

  • Estrella K (2007) Expressive therapy: an integrated arts approach. In: Malchiodi C (ed) Expressive therapies. The Guildford Press, New York, pp 183–209

    Google Scholar 

  • Folgieri R, Lucciari C (2016) Creative thinking: a brain computer interface of art. In: International conference on live interfaces. https://doi.org/10.13140/rg.2.2.31683.40489

  • Franks DD (2006) The neuroscience of emotions. In: Stets JE, Turner JH (eds) Handbook of the sociology of emotions. Springer, New York, pp 38–62

    Chapter  Google Scholar 

  • Friedrich EV et al (2014) Brain-computer interface game applications for combined neurofeedback and biofeedback treatment for children on the autism spectrum. Front Neuroeng 7. https://doi.org/10.3389/fneng.2014.00021

  • Garner RL (2017) Introduction. Digital art therapy: material, methods and applications. Jessica Kingsley, London, pp 9–20

    Google Scholar 

  • Grierson M (2008) Composing with brainwaves: minimal trial P300 recognition as an indication of subjective preference for the control of a musical. In: International computer music conference

    Google Scholar 

  • Grierson M, Kiefer C, Yee-King M (2011) Progress report on the EAVI BCI toolkit for music: musical applications of algorithms for use with consumer brain computer interfaces. In: Proceedings of the international computer music conference 2011, pp 110–113

    Google Scholar 

  • Hinz LD (2009) Overview of the expressive therapies continuum. In: Expressive therapies continuum: a framework for using art in therapy. Routledge, New York, pp 3–19

    Google Scholar 

  • Holz EM et al (2015a) Independent home use of Brain Painting improves quality of life of two artists in the locked-in state diagnosed with amyotrophic lateral sclerosis. Brain Comput Interfaces 2(2–3):117–134

    Article  Google Scholar 

  • Holz EM, Botrel L, Kaufmann T, KĂĽbler A (2015b) Long-term independent brain-computer interface home use improves quality of life of a patient in the locked-in state: a case study. Arch Phys Med Rehabil. https://doi.org/10.1016/j.apmr.2014.03.035

  • Kaiser D, Deaver S (2013) Establishing a research agenda for art therapy: a Delphi study. Art Ther 30(3):114–121. https://doi.org/10.1080/07421656.2013.819281

    Article  Google Scholar 

  • Kamiya J (2011) The first communications about operant conditioning of the EEG. J Neurother 15:65–73. https://doi.org/10.1080/10874208.2011.545764

    Article  Google Scholar 

  • King JL (2016) Art therapy: a brain-based profession. In: The Wiley Blackwell handbook of art therapy. Wiley, Chichester, pp 77–89

    Google Scholar 

  • Knill PJ (2010) Foundations of a theory of practice. In: Knill PJ et al (eds) Principles and practice of expressive arts therapy toward a therapeutic aesthetics. Jessica Kingsley, London, pp 79–170

    Google Scholar 

  • Kruk KA et al (2014) Comparison of brain activity during drawing and clay sculpting: a preliminary qEEG study. Art Ther. 31(2):52–60. https://doi.org/10.1080/07421656.2014.903826

    Article  Google Scholar 

  • Lieblein R, Hunter C, Garcia S et al (2017) Augmented cognition. Enhancing Cogn Behav Complex Hum Environ 10285:345–353. https://doi.org/10.1007/978-3-319-58625-0

    Article  Google Scholar 

  • Malchiodi CA (2007) Expressive therapies: history, theory, and practice. In: Expressive therapies. The Guildford Press, New York, pp 1–15

    Google Scholar 

  • Matthias J, Ryan N (2007) Cortical songs: musical performance events triggered by artificial spiking neurons. Body Space Technol 7(1). http://doi.org/10.16995/bst.157

  • McNiff S (1981) Overview. In: The arts and psychotherapy. Thomas, Springfield, IL, pp v–xxiii

    Google Scholar 

  • Miranda R, Castet J (eds) (2014) Guide to brain-computer music interfacing. Springer, London

    Google Scholar 

  • Moon CH (2010) A history of materials and media in art therapy. In: Materials & media in art therapy: critical understandings of diverse artistic vocabularies. Routledge Taylor & Francis Group, New York, pp 3–47

    Google Scholar 

  • MĂĽnĂźinger JI, Halder S, Kleih SC et al (2010) Brain painting: first evaluation of a new brain-computer interface application with ALS-patients and healthy volunteers. Front Neurosci 4:182. https://doi.org/10.3389/fnins.2010.00182

    Article  Google Scholar 

  • Nijholt A, Nam CS (2015) Arts and brain-computer interfaces (BCIs). Brain Comput Interfaces 2:57–59. https://doi.org/10.1080/2326263X.2015.1100514

    Article  Google Scholar 

  • Ogden P, Minton K (2000) Sensorimotor psychotherapy: one method for processing traumatic memory. Traumatology 6(3):149–173. https://doi.org/10.1177/153476560000600302

    Article  Google Scholar 

  • Pineda J et al (2012) Self-regulation of brain oscillations as a treatment for aberrant brain connections in children with autism. Med Hypotheses 79(6):790–798. https://doi.org/10.1016/j.mehy.2012.08.031

    Article  Google Scholar 

  • Pinegger A, Hiebel H, Wriessnegger SC, MĂĽller-Putz GR (2017) Composing only by thought: novel application of the P300 brain-computer interface. PLoS One 12:1–20. https://doi.org/10.1371/journal.pone.0181584

    Article  Google Scholar 

  • Pistoia F et al (2017) Commentary: embodied medicine: mens sana in corpore virtuale sano. Front Hum Neurosci 11. https://doi.org/10.3389/fnhum.2017.00381

  • Prpa M, Pasquier P (2018) BCI art: brain computer interfaces in contemporary art. Available via ResearchGate, https://www.researchgate.net/publication/324705672_BCI_art_brain-computer_interfaces_in_contemporary_art. Accessed 30 Oct 2018

  • Rogers N (1993) A path to wholeness: person-centered expressive arts therapy. In: The creative connection: expressive arts as healing. Science and Behavior Books, Palo Alto, CA, pp 1–9

    Google Scholar 

  • Rosenboom D (1997) Extended musical interface with the human nervous system. Leonardo monograph series, supplemental issue

    Google Scholar 

  • Shafir T (2018) Measuring brain mechanisms underlying dance-therapy: past & future directions. In: Proceedings of the 3rd international mobile brain/body imaging. https://depositonce.tu-berlin.de/bitstream/11303/8075/3/proceedings_MoBi2018.pdf. Accessed 10 Nov 2018

  • Sherman RA et al (1984) Chronic phantom and stump pain among American veterans: results of a survey. Pain 18(1):83–95. https://doi.org/10.1016/0304-3959(84)90128-3

    Article  Google Scholar 

  • Van De Laar B, Brugman I, Nijboer F et al (2013) BrainBrush, a multimodal application for creative expressivity. In: ACHI 2013 sixth international conference on advances in computer-human interactions, pp 62–67

    Google Scholar 

  • Wadeson A, Nijholt A, Nam CS (2015) Artistic brain-computer interfaces: state-of-the-art control mechanisms. Brain Comput Interfaces 2(2–3):70–75. https://doi.org/10.1080/2326263x.2015.1103155

    Article  Google Scholar 

  • Williams D et al (2015) Affective calibration of a computer-aided composition system by listener evaluation. In: Proceedings of the ninth triennial conference of the European Society for the cognitive sciences of music (ESCOM2015). http://cmr.soc.plymouth.ac.uk/publications/ESCOM15-DW.pdf. Accessed 04 Jan 2019

  • Williams DA, Miranda ER (2018) BCI for music making: then, now, and next. In: Nam C et al (eds) Brain-computer interfaces handbook: technological and theoretical advances. CRC Press, Taylor & Francis Group, Boca Raton, FL, pp 193–205

    Google Scholar 

  • Zickler C, Halder S, Kleih SC et al (2013) Brain painting: usability testing according to the user-centered design in end users with severe motor paralysis. Artif Intell Med 59:99–110. https://doi.org/10.1016/j.artmed.2013.08.003

    Article  Google Scholar 

  • Zioga P et al (2018) Enheduanna—a manifesto of falling. Live brain-computer cinema performance: performer and audience participation cognition and emotional engagement using multi-brain BCI interaction. Front Neurosci 12. https://doi.org/10.3389/fnins.2018.00191

Download references

Author information

Authors and Affiliations

  1. Department of Social Work and Social Administration, University of Hong Kong, Pokfulam, Hong Kong

    Rainbow Tin Hung Ho

  2. Centre on Behavioral Health, University of Hong Kong, Pokfulam, Hong Kong

    Rainbow Tin Hung Ho & Sunee H. Markosov

  3. Department of Industrial and Systems Engineering, North Carolina State University, Raleigh, USA

    Nathan Sanders & Chang S. Nam

Authors
  1. Rainbow Tin Hung Ho
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sunee H. Markosov
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Nathan Sanders
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Chang S. Nam
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Rainbow Tin Hung Ho .

Editor information

Editors and Affiliations

  1. Human Media Interaction, Faculty of EEMCS, Universiteit Twente, Enschede, The Netherlands

    Anton Nijholt

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Ho, R.T.H., Markosov, S.H., Sanders, N., Nam, C.S. (2019). BCI-Based Expressive Arts: Moving Toward Mind-Body Alignment. In: Nijholt, A. (eds) Brain Art. Springer, Cham. https://doi.org/10.1007/978-3-030-14323-7_13

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-14323-7_13

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-14322-0

  • Online ISBN: 978-3-030-14323-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation