skip to main content
10.1145/3340764.3344884acmotherconferencesArticle/Chapter ViewAbstractPublication PagesmundcConference Proceedingsconference-collections
short-paper

MindTrain: How to Train Your Mind with Interactive Technologies

Authors Info & Claims
Published:08 September 2019Publication History

ABSTRACT

Technological products for training the mind that support subjective well-being are gaining popularity in our daily lives. Using Electroencephalographic (EEG) signals for neurofeedback is helpful for learning and a promising approach to train the mind. We introduce MindTrain, a novel, gamified neurofeedback training environment that allows users to learn the skill to voluntarily self-regulate their brain activity in Virtual Reality (VR). MindTrain combines the concept of implicit control with a mobile consumer EEG-wearable in an interactive and immersive VR-environment for visualising the feedback. We tested the feasibility of MindTrain for training to control states of relaxation and concentration. Our results prove that MindTrain is a promising novel method that warrants further investigation within a larger study. Furthermore, the use of the mobile EEG-wearable demonstrates the potential for bringing MindTrain out of the laboratory into a real-world context.

References

  1. Kai Keng Ang, Zheng Yang Chin, Haihong Zhang, and Cuntai Guan. 2008. Filter bank common spatial pattern (FBCSP) in brain-computer interface. In 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence). IEEE, 2390--2397.Google ScholarGoogle Scholar
  2. Benjamin Blankertz, Laura Acqualagna, Sven Dähne, Stefan Haufe, Matthias Schultze-Kraft, Irene Sturm, Marija Ušćumlic, Markus A Wenzel, Gabriel Curio, and Klaus-Robert Müller. 2016. The Berlin brain-computer interface: progress beyond communication and control. Frontiers in Neuroscience 10 (2016), 530.Google ScholarGoogle ScholarCross RefCross Ref
  3. Sophie Bostock, Alexandra D Crosswell, Aric A Prather, and Andrew Steptoe. 2019. Mindfulness on-the-go: Effects of a mindfulness meditation app on work stress and well-being. Journal of occupational health psychology 24 (2019), 127--138.Google ScholarGoogle ScholarCross RefCross Ref
  4. HTC Corporation. 2015. VIVE VR SYSTEM. https://www.vive.com/us/product/vive-virtual-reality-system/Google ScholarGoogle Scholar
  5. John Gruzelier. 2009. A theory of alpha/theta neurofeedback, creative performance enhancement, long distance functional connectivity and psychological integration. Cognitive processing 10, 1 (2009), 101--109.Google ScholarGoogle Scholar
  6. Headspace. 2019. Headspace - Your guide to health and happiness. Retrieved June 6, 2019 from https://www.headspace.com/Google ScholarGoogle Scholar
  7. Joerg Hipp and Markus Siegel. 2013. Dissociating neuronal gammaband activity from cranial and ocular muscle activity in EEG. Frontiers in Human Neuroscience 7 (2013), 338.Google ScholarGoogle ScholarCross RefCross Ref
  8. Annika Howells, Itai Ivtzan, and Francisco Jose Eiroa-Orosa. 2016. Putting the 'app' in happiness: a randomised controlled trial of a smartphone-based mindfulness intervention to enhance wellbeing. Journal of Happiness Studies 17, 1 (2016), 163--185.Google ScholarGoogle ScholarCross RefCross Ref
  9. Interaxon. 2014. Muse. https://choosemuse.com/Google ScholarGoogle Scholar
  10. Ilkka Kosunen, Mikko Salminen, Simo Järvelä, Antti Ruonala, Niklas Ravaja, and Giulio Jacucci. 2016. RelaWorld: neuroadaptive and immersive virtual reality meditation system. In Proceedings of the 21st International Conference on Intelligent User Interfaces. ACM, New York, NY, USA, 208--217. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Christian Kothe. 2018. Lab streaming layer. https://github.com/sccn/labstreaminglayer.Google ScholarGoogle Scholar
  12. Natasha Kovacevic, Petra Ritter, William Tays, Sylvain Moreno, and Anthony Randal McIntosh. 2015. 'My virtual dream': Collective neurofeedback in an immersive art environment. PloS ONE 10, 7 (2015), e0130129.Google ScholarGoogle ScholarCross RefCross Ref
  13. Jason Kowaleski. 2019. BlueMuse. https://github.com/kowalej/BlueMuse.Google ScholarGoogle Scholar
  14. Laurens R Krol, Sarah-Christin Freytag, and Thorsten O Zander. 2017. Meyendtris: a hands-free, multimodal tetris clone using eye tracking and passive BCI for intuitive neuroadaptive gaming. In Proceedings of the 19th ACM International Conference on Multimodal Interaction. ACM, New York, NY, USA, 433--437. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Anatole Lécuyer, Fabien Lotte, Richard B Reilly, Robert Leeb, Michitaka Hirose, and Mel Slater. 2008. Brain-computer interfaces, virtual reality, and videogames. Computer 41, 10 (2008), 66--72. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Choon Guan Lim, Tih Shih Lee, Cuntai Guan, Daniel Shuen Sheng Fung, Yudong Zhao, Stephanie Sze Wei Teng, Haihong Zhang, and K Ranga Rama Krishnan. 2012. A brain-computer interface based attention training program for treating attention deficit hyperactivity disorder PloS ONE 7,10 (2012), e46692.Google ScholarGoogle Scholar
  17. Mindfulness Everywhere Ltd. 2019. Buddhify: Meditation & Mindfulness App. https://buddhify.com/Google ScholarGoogle Scholar
  18. NeuroSky. 2004. NeuroSky - Body and Mind. Quantified. http://neurosky.com/Google ScholarGoogle Scholar
  19. Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, Mathieu Blondel, Peter Prettenhofer, Ron Weiss, Vincent Dubourg, et al. 2011. Scikit-learn: Machine learning in Python. Journal of machine learning research 12 (2011), 2825--2830. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Sebastian Raschka. 2019. Sequential Feature Selector. http://rasbt.github.io/mlxtend/user_guide/feature_selection/SequentialFeatureSelector/.Google ScholarGoogle Scholar
  21. Alaa Tharwat, Tarek Gaber, Abdelhameed Ibrahim, and Aboul Ella Hassanien. 2017. Linear discriminant analysis: A detailed tutorial. AI communications 30, 2 (2017), 169--190.Google ScholarGoogle Scholar
  22. Bastian Venthur, Sven Dähne, Johannes Höhne, Hendrik Heller, and Benjamin Blankertz. 2015. Wyrm: A brain-computer interface toolbox in python. Neuroinformatics 13, 4 (2015), 471--486.Google ScholarGoogle ScholarCross RefCross Ref
  23. Oculus VR. 2018. Oculus Go. https://www.oculus.com/go/Google ScholarGoogle Scholar
  24. Oculus VR. 2019. Oculus Rift - S. https://www.oculus.com/rift-s/Google ScholarGoogle Scholar
  25. Jonathan R Wolpaw and Dennis J McFarland. 2004. Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans. Proceedings of the national academy of sciences 101, 51 (2004), 17849--17854.Google ScholarGoogle ScholarCross RefCross Ref
  26. Sarah Wyckoff and Niels Birbaumer. 2014. Neurofeedback and brain-computer interfaces. The Handbook of Behavioral Medicine 1112 (2014), 275--312.Google ScholarGoogle ScholarCross RefCross Ref
  27. Maryam Binte Zafar, Khadija Akbar Shah, and Hassan Adnan Malik. 2017. Prospects of sustainable ADHD treatment through Brain-Computer Interface systems. In 2017 International Conference on Innovations in Electrical Engineering and Computational Technologies (ICIEECT). IEEE, 1--6.Google ScholarGoogle ScholarCross RefCross Ref
  28. Thorsten O Zander and Christian Kothe. 2011. Towards passive brain--computer interfaces: applying brain--computer interface technology to human--machine systems in general. Journal of neural engineering 8, 2 (2011), 025005.Google ScholarGoogle ScholarCross RefCross Ref
  29. Nan Zeng, Zachary Pope, Jung Lee, and Zan Gao. 2018. Virtual reality exercise for anxiety and depression: A preliminary review of current research in an emerging field. Journal of clinical medicine 7, 3 (2018), 1--13.Google ScholarGoogle ScholarCross RefCross Ref

Index Terms

  1. MindTrain: How to Train Your Mind with Interactive Technologies

        Recommendations

        Comments

        Login options

        Check if you have access through your login credentials or your institution to get full access on this article.

        Sign in
        • Published in

          cover image ACM Other conferences
          MuC '19: Proceedings of Mensch und Computer 2019
          September 2019
          863 pages
          ISBN:9781450371988
          DOI:10.1145/3340764

          Copyright © 2019 ACM

          Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 8 September 2019

          Permissions

          Request permissions about this article.

          Request Permissions

          Check for updates

          Qualifiers

          • short-paper
          • Research
          • Refereed limited

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader