Skip to main content

Advertisement

Log in

East meets west: a mobile brain-computer system that helps children living in poverty learn to self-regulate

Personal and Ubiquitous Computing Aims and scope Submit manuscript

Abstract

Children living in poverty often suffer multiple forms of trauma, which impedes their ability to effectively self-regulate negative emotions, such as anxiety, and to focus their attention. As a result, many of these children struggle at school. Our work explores the effectiveness of using a mindfulness-oriented, neurofeedback-based, brain-computer system to help teach children living in poverty to self-regulate anxiety and attention. Our system, called Mind-Full, was specifically designed for illiterate girls who attend an NGO-funded school in Pokhara, Nepal. In this paper, we present the results of a waitlist control field experiment with 21 girls who completed an intervention using the Mind-Full system. Our results indicated that a 6-week Mind-Full intervention was viable and that children were able to transfer self-regulation skills learned using our system into real-world settings and continue to self-regulate successfully after 2 months. We present our findings as a validation of the effectiveness of mobile neurofeedback-based interventions to help young children living in poverty develop self-regulation skills. We conclude with a discussion of the results, methodological challenges of working in the developing world, and advice for future investigations of the effectiveness of neurofeedback applications for children.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Notes

  1. https://www.unicef.org/sowc/archive/ENGLISH/The%20State%20of%20the%20World%27s%20Children%202005.pdf

  2. http://neurosky.com

  3. The algorithm for calculating the mediation and attention indices is proprietary; however, we know that the mediation index is based on alpha/theta frequencies and attention on beta frequencies. Various studies have validated their accuracy.

  4. https://www.emotiv.com

  5. www.nepalhousesociety.org

  6. https://www.youtube.com/watch?v=2TbLI6mga38&t=29s

  7. https://play.google.com/store/apps/details?id=com.ttxapps.drivesync&hl=en

  8. http://www.titaniumtrack.com/titanium-backup.html

  9. Note that now that we have defined our measures, we replace descriptive construct names from the initial statement of hypotheses (e.g., behavioral measures of ability to self-regulate anxiety) with our operationalized construct names (e.g., Calm).

  10. Cohen suggested that d = 0.2 be considered a “small” effect size, 0.5 represents a “medium” effect size, and 0.8 a “large” effect size (ADD REF).

  11. See www.mindfullapp.ca for two other Mind-Full apps for different populations of children.

References

  1. Antle AN (2017) The ethics of doing research with vulnerable populations. ACM Interact 24:74–77

    Article  Google Scholar 

  2. Antle AN, Chesick L, Levisohn A, Sridharan SK, Tan P (2015) Using neurofeedback to teach self-regulation to children living in poverty, in: Proceedings of the 14th International Conference on Interaction Design and Children, IDC ‘15. ACM, New York, pp 119–128. https://doi.org/10.1145/2771839.2771852

    Google Scholar 

  3. Antle AN, Chesick L, McLaren ES (2018) Opening up the design space of neurofeedback brain-computer interfaces for children. ACM Trans Comput-Hum Interact 24(6):1–38. https://doi.org/10.1145/3131607

    Article  Google Scholar 

  4. Arns M, de Ridder S, Strehl U, Breteler M, Coenen A (2009) Efficacy of neurofeedback treatment in ADHD: the effects on inattention, impulsivity and hyperactivity: a meta-analysis. Clin EEG Neurosci 40:180–189. https://doi.org/10.1177/155005940904000311

    Article  Google Scholar 

  5. Bhayee S, Tomaszewski P, Lee DH, Moffat G, Pino L, Moreno S, Farb NAS (2016) Attentional and affective consequences of technology supported mindfulness training: a randomised, active control, efficacy trial. BMC Psychol 4(60):60. https://doi.org/10.1186/s40359-016-0168-6

    Article  Google Scholar 

  6. Blankertz B, Tangermann M, Vidaurre C, Fazli S, Sannelli C, Haufe S, Maeder C, Ramsey L, Sturm I, Curio G, Müller K-R (2010) The Berlin brain-computer interface: non-medical uses of BCI technology. Front Neurosci 4. https://doi.org/10.3389/fnins.2010.00198

  7. Child Welfare Information Gateway (2015) Understanding the effects of maltreatment on brain development, issue briefs.

  8. Creswell JW (2006) Qualitative inquiry and research design: choosing among five approaches, 2nd ed. Sage Publications, Inc

  9. Gapen M, van der Kolk BA, Hamlin E, Hirshberg L, Suvak M, Spinazzola J (2016) A pilot study of neurofeedback for chronic PTSD. Appl Psychophysiol Biofeedback 41:251–261. https://doi.org/10.1007/s10484-015-9326-5

    Article  Google Scholar 

  10. Gevensleben H, Holl B, Albrecht B, Vogel C, Schlamp D, Kratz O, Studer P, Rothenberger A, Moll GH, Heinrich H (2009) Is neurofeedback an efficacious treatment for ADHD? A randomised controlled clinical trial. J Child Psychol Psychiatry 50:780–789. https://doi.org/10.1111/j.1469-7610.2008.02033.x

    Article  Google Scholar 

  11. Gevensleben H, Kleemeyer M, Rothenberger LG, Studer P, Flaig-Röhr A, Moll GH, Rothenberger A, Heinrich H (2014) Neurofeedback in ADHD: further pieces of the puzzle. Brain Topogr 27:20–32. https://doi.org/10.1007/s10548-013-0285-y

    Article  Google Scholar 

  12. Glewwe P, Kremer M (2006) Chapter 16 Schools, teachers, and education outcomes in developing countries. In: Hanushek E, Welch F (eds), Handbook of the economics of education. Elsevier, p 945–1017

  13. Gruzelier JH (2014) EEG-neurofeedback for optimising performance. III: a review of methodological and theoretical considerations. Neurosci Biobehav Rev 44:159–182. https://doi.org/10.1016/j.neubiorev.2014.03.015

    Article  Google Scholar 

  14. Gruzelier JH, Foks M, Steffert T, Chen ML, Ros T (2014) Beneficial outcome from EEG-neurofeedback on creative music performance, attention and well-being in school children. Biol Psychol 95:86–95

    Article  Google Scholar 

  15. Guger C, Edlinger G, Krausz G (2011) Hardware/software components and applications of BCIs. Recent Adv Brain-Comput Interface Syst 1–24

  16. Hammond DC (2005) Neurofeedback with anxiety and affective disorders. Child Adolesc Psychiatr Clin N Am 14:105–123

    Article  Google Scholar 

  17. Heinrich H, Gevensleben H, Strehl U (2007) Annotation: neurofeedback–train your brain to train behaviour. J Child Psychol Psychiatry 48:3–16

    Article  Google Scholar 

  18. Hemington KS, Reynolds JN (2014) Electroencephalographic correlates of working memory deficits in children with fetal alcohol spectrum disorder using a single-electrode pair recording device. Clin Neurophysiol 125:2364–2371

    Article  Google Scholar 

  19. Huang J, Yu C, Wang Y, Zhao Y, Liu S, Mo C, Liu J, Zhang L, Shi Y (2014) FOCUS: enhancing children’s engagement in reading by using contextual BCI training sessions, in: Proceedings of the 32Nd Annual ACM Conference on Human Factors in Computing Systems, CHI ‘14. ACM, New York, pp 1905–1908. https://doi.org/10.1145/2556288.2557339

    Google Scholar 

  20. Janssen TWP, Bink M, Weeda WD, Geladé K, van Mourik R, Maras A, Oosterlaan J (2017) Learning curves of theta/beta neurofeedback in children with ADHD. Eur Child Adolesc Psychiatry 26:573–582. https://doi.org/10.1007/s00787-016-0920-8

    Article  Google Scholar 

  21. Johnstone SJ, Blackman R, Bruggemann JM (2012) EEG from a single-channel dry-sensor recording device. Clin EEG Neurosci 43:112–120

    Article  Google Scholar 

  22. Johnstone SJ, Roodenrys SJ, Johnson K, Bonfield R, Bennett SJ (2017) Game-based combined cognitive and neurofeedback training using Focus Pocus reduces symptom severity in children with diagnosed AD/HD and subclinical AD/HD. Int J Psychophysiol 116:32–44

    Article  Google Scholar 

  23. Knox M, Lentini J, Cummings TS, McGrady A, Whearty K, Sancrant L (2011) Game-based biofeedback for paediatric anxiety and depression. Ment Health Fam Med 8:195

    Google Scholar 

  24. van der Kolk BA, Hodgdon H, Gapen M, Musicaro R, Suvak MK, Hamlin E, Spinazzola J (2016) A randomized controlled study of neurofeedback for chronic PTSD. PLoS One 11:e0166752. https://doi.org/10.1371/journal.pone.0166752

    Article  Google Scholar 

  25. Lansbergen MM, van Dongen-Boomsma M, Buitelaar JK, Slaats-Willemse D (2011) ADHD and EEG-neurofeedback: a double-blind randomized placebo-controlled feasibility study. J Neural Transm 118:275–284. https://doi.org/10.1007/s00702-010-0524-2

    Article  Google Scholar 

  26. Lee J, Semple RJ, Rosa D, Miller L (2008) Mindfulness-based cognitive therapy for children: results of a pilot study. J Cogn Psychother 22:15–28. https://doi.org/10.1891/0889.8391.22.1.15

    Article  Google Scholar 

  27. Lim CG, Lee TS, Guan C, Fung DSS, Zhao Y, Teng SSW, Zhang H, Krishnan KRR (2012) A brain-computer interface based attention training program for treating attention deficit hyperactivity disorder. PLoS One 7:e46692. https://doi.org/10.1371/journal.pone.0046692

    Article  Google Scholar 

  28. Lofthouse N, Arnold LE, Hersch S, Hurt E, DeBeus R (2012) A review of neurofeedback treatment for pediatric ADHD. J Atten Disord 16:351–372. https://doi.org/10.1177/1087054711427530

    Article  Google Scholar 

  29. Lubar JF, Shouse MN (1976) EEG and behavioral changes in a hyperkinetic child concurrent with training of the sensorimotor rhythm (SMR). Biofeedback and Self-Regulation 1(3):293–306

  30. Mandryk RL, Dielschneider S, Kalyn MR, Bertram CP, Gaetz M, Doucette A, Taylor BA, Orr AP, Keiver K (2013) Games as neurofeedback training for children with FASD, in: Proceedings of the 12th International Conference on Interaction Design and Children, IDC ‘13. ACM, New York, pp 165–172. https://doi.org/10.1145/2485760.2485762

    Google Scholar 

  31. Nijholt A, Bos DP, Reuderink B (2009) Turning shortcomings into challenges: brain–computer interfaces for games. Entertainment Computing 1(2):85–94

  32. O'Hara K, Sellen A, Harper R (2011) Embodiment in brain-computer interaction. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI 2011. ACM, New York, pp. 353–362. https://doi.org/10.1145/1978942.1978994

  33. Rebolledo-Mendez G, Dunwell I, Martínez-Mirón EA, Vargas-Cerdán MD, de Freitas S, Liarokapis F, García-Gaona AR (2009) Assessing NeuroSky’s usability to detect attention levels in an assessment exercise. In: Jacko JA (ed) Human-computer interaction. Lect Notes Comput Sci Springer Berlin Heidelberg, New Trends, pp 149–158

    Google Scholar 

  34. Reiner R (2008) Integrating a portable biofeedback device into clinical practice for patients with anxiety disorders: results of a pilot study. Appl Psychophysiol Biofeedback 33:55–61. https://doi.org/10.1007/s10484-007-9046-6

    Article  Google Scholar 

  35. Reiter K, Andersen SB, Carlsson J (2016) Neurofeedback treatment and posttraumatic stress disorder: effectiveness of neurofeedback on posttraumatic stress disorder and the optimal choice of protocol. J Nerv Ment Dis 204:69–77. https://doi.org/10.1097/NMD.0000000000000418

    Article  Google Scholar 

  36. Schoneveld EA, Malmberg M, Lichtwarck-Aschoff A, Verheijen GP, Engels RCME, Granic I (2016) A neurofeedback video game (MindLight) to prevent anxiety in children: a randomized controlled trial. Comput Hum Behav 63:321–333. https://doi.org/10.1016/j.chb.2016.05.005

    Article  Google Scholar 

  37. Simkin DR, Thatcher RW, Lubar J (2014) Quantitative EEG and neurofeedback in children and adolescents: anxiety disorders, depressive disorders, comorbid addiction and attention-deficit/hyperactivity disorder, and brain injury. Child Adolesc Psychiatr Clin 23:427–464. https://doi.org/10.1016/j.chc.2014.03.001

    Article  Google Scholar 

  38. Steiner NJ, Frenette EC, Rene KM, Brennan RT, Perrin EC (2014) Neurofeedback and cognitive attention training for children with attention-deficit hyperactivity disorder in schools. J Dev Behav Pediatr 35:18–27

    Article  Google Scholar 

  39. Stinson B, Arthur D (2013) A novel EEG for alpha brain state training, neurobiofeedback and behavior change. Complement Ther Clin Pract 19:114–118. https://doi.org/10.1016/j.ctcp.2013.03.003

    Article  Google Scholar 

  40. The Universe Inside Your Head [WWW Document] (n.d.) URL http://www.brainfacts.org/brain-anatomy-and-function/anatomy/2013/the-universe-inside-your-head (accessed 11.19.17)

  41. Walsh R, Shapiro SL (2006) The meeting of meditative disciplines and western psychology: a mutually enriching dialogue. Am Psychol 61:227–239. https://doi.org/10.1037/0003-066X.61.3.227

    Article  Google Scholar 

  42. Wijnhoven LAMW, Creemers DHM, Engels RCME, Granic I (2015) The effect of the video game Mindlight on anxiety symptoms in children with an autism spectrum disorder. BMC Psychiatry 15:138. https://doi.org/10.1186/s12888-015-0522-x

    Article  Google Scholar 

  43. Zelazo PD, Lyons KE (2011) Mindfulness training in childhood. Hum Dev 54:61–65. https://doi.org/10.1159/000327548

    Article  Google Scholar 

Download references

Acknowledgments

We appreciate the support of the Nepal House Society (Canada). Special thanks to Basante, Shiva, Laxmi, and Buddhi at the Nepal House Kaski for taking a risk and for all their time. Thanks to Shiva for motorcycle rides to the Tibetan Refugee camp when we needed a break. Thanks also to the Nepal House Kaski teachers, and to Dr. Patrice Keats and Dr. Vicky Hannam for helping assess the children. Special appreciation to Levi Antle for motivating me to learn how to design interactive technologies to support self-regulation and for coming to Nepal and to Kate Antle for technical and media support especially her ingenuity with video cameras and shoelaces. Thanks to Perry Tan for 3 a.m. Skype calls for technical troubleshooting. And most of all thanks to 23 young Nepali girls for trying something so very different from their everyday lives.

Funding

This research was supported by grants from the Natural Science and Engineering Research Council of Canada (NSERC), the Social Science and Humanities Research Council (SSHRC), the GRAND Network Centre of Excellence (Canada), and Microsoft Research.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Alissa N. Antle.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Antle, A.N., Chesick, L., Sridharan, S.K. et al. East meets west: a mobile brain-computer system that helps children living in poverty learn to self-regulate. Pers Ubiquit Comput 22, 839–866 (2018). https://doi.org/10.1007/s00779-018-1166-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00779-018-1166-x

Keywords

Navigation