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Meditation Therapy for Stress Management Using Brainwave Computing and Real Time Virtual Reality Feedback

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Data Management, Analytics and Innovation (ICDMAI 2022)

Abstract

It is a well-accepted fact that today every individual has to perform so many activities simultaneously which leads to a hectic lifestyle. This hectic lifestyle has resulted in an increase in mental stress among people. Meditation has been one of the most widely and effective ways of reducing stress of a person. Apart from stress reduction, meditation also helps to increase the concentration level, control emotions, reduce sleeplessness and enhance the ability of a person to face challenges. Though meditation has several benefits, self-assessing the impact of meditation on stress level has been difficult and challenging. In this paper, we have addressed this problem by designing and developing a Virtual Reality Assisted Meditation Therapy (VRAMT) system. During meditation, this system measures the brainwaves and classifies them to track the state of mind as whether calm or stressed. Based on the classification result, the system provides virtual reality feedback in real-time to the user through which the user can self-assess one’s state of mind.

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References

  1. P. Pechtel, D.A. Pizzagalli, Effects of early life stress on cognitive and affective function: an integrated review of human literature. Psychopharmacology 214(1), 55–70 (2011). https://doi.org/10.1007/s00213-010-2009-2

    Article  Google Scholar 

  2. G.E. Miller, E. Chen, K.J. Parker, Psychological stress in childhood and susceptibility to the chronic diseases of aging: moving towards a model of behavioral and biological mechanisms. Psychol. Bull. 137(6), 959–997 (2011). https://doi.org/10.1037/a0024768

    Article  Google Scholar 

  3. H. Yaribeygi, Y. Panahi, H. Sahraei, T.P. Johnston, A. Sahebkar, EXCLI J. 16, 1057–1072 (2017). https://doi.org/10.17179/excli2017-480. Published online 21 Jul 2017

  4. M. Nakao, Work-Related Stress and Psychosomatic Medicine (Nakao Bio Psycho Social Medicine, 2010)

    Google Scholar 

  5. R. Kanthan, J.-L. Senger, The impact of specially designed digital games-based learning in undergraduate pathology and medical education. Arch. Pathol. Lab. Med. 135 (2011)

    Google Scholar 

  6. A. Schuurmans, K. Nijhof, R. Scholte, A. Popma, R. Otten, Game-based meditation therapy to improve posttraumatic stress and neurobiological stress systems in traumatized adolescents: protocol for a randomized controlled trial. JMIR Res Protoc 9(9), e19881 (2020). https://doi.org/10.2196/19881

  7. T.K. Rana, B. Badlani, M. Basu, C.D. Choudhuri, S. Karmakar, Brainwave sensed chromo therapy based meditation hub, in 2019 3rd International Conference on Electronics, Materials Engineering & Nano-Technology (IEMENTech), 2019, pp. 1–5. https://doi.org/10.1109/IEMENTech48150.2019.8981010

  8. S. Rosenzweig, J.M. Greeson, D.K. Reibel, J.S. Green, S.A. Jasser, D. Beasley, Mindfulness-based stress reduction for chronic pain conditions: variation in treatment outcomes and role of home meditation practice. J. Psychosom. Res. 68, 29–36 (2010)

    Google Scholar 

  9. P. Supoo, P. Sittiprapaporn, Brainwave activity and cognitive performance investigated by meditation yoga, in 2019 16th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), 2019, pp. 482–485. https://doi.org/10.1109/ECTI-CON47248.2019.8955411

  10. D. Lehmann, P.L. Faber, S. Tei, R.D. Pascual-Marqui, P. Milz, K. Kochi, Reduced functional connectivity between cortical sources in five meditation traditions detected with lagged coherence using EEG tomography. Neuroimage 60(2), 1574–1586 (2012)

    Article  Google Scholar 

  11. N. Sulaiman, B.S. Ying, M. Mustafa, M.S. Jadin, Offline LabView-based EEG signals analysis for human stress monitoring, in 2018 9th IEEE Control and System Graduate Research Colloquium (ICSGRC), 2018, pp. 126–131. https://doi.org/10.1109/ICSGRC.2018.8657606

  12. X. Liu, P.-N. Tan, L. Liu, S.J. Simske, Automated classification of EEG signals for predicting students’ cognitive state during learning, in 15th German Conference on Multiagent System Technologies, Leipzig University, Leipzig, Germany, Aug 2017 (in press)

    Google Scholar 

  13. D.P. Lippelt, B. Hommeland, L.S. Colzato, Focused attention, open monitoring and loving kindness meditation: effects on attention, conflict monitoring, and creativity—a review. Front. Psychol. 5 (2014)

    Google Scholar 

  14. M. Abujelala, A. Sharma, C. Abellanoza, F. Makedon, Brain-EE: brain enjoyment evaluation using commercial EEG headband, in The 9th ACM International Conference on Pervasive Technologies Related to Assistive Environments PETRA 2016, Corfu, Greece

    Google Scholar 

  15. G.C. Burdea, P. Coiffet, Virtual Reality Technology, 2nd edn. (Wiley, India)

    Google Scholar 

  16. A. Taneja, S.B. Vishal, V. Mahesh, B. Geethanjali, Virtual reality based neuro-rehabilitation for mental stress reduction, in 2017 Fourth International Conference on Signal Processing, Communication and Networking (ICSCN), 2017, pp. 1–5. https://doi.org/10.1109/ICSCN.2017.8085665

  17. Y. Wu, X. Yang, Y. Li, H. Li, W. Yang,Brainwave analysis in virtual reality based emotional regulation training, in 2018 International Conference on Computational Science and Computational Intelligence (CSCI), 2018, pp. 691–696.https://doi.org/10.1109/CSCI46756.2018.00139

  18. T. Andersen et al., A preliminary study of users’ experiences of meditation in virtual reality. IEEE Virtual Reality (VR) 2017, 343–344 (2017). https://doi.org/10.1109/VR.2017.7892317

    Article  Google Scholar 

  19. M.D.A. Rozmi, D.R.A. Rambli, S. Sulaiman, N. Zamin, N.D.M. Muhaiyuddin, F.O. Mean,Design considerations for a virtual reality-based nature therapy to release stress, in 2019 International Conference on Advances in the Emerging Computing Technologies (AECT), 2020, pp. 1–4.https://doi.org/10.1109/AECT47998.2020.9194175

  20. M.S. Ijjada, H. Thapliya, A. Caban-Holt, H.R. Arabnia, Evaluation of wearable head set devices in older adult populations for research, in International Conference on Computational Science and Computational Intelligence, December 2015

    Google Scholar 

  21. N. Jadhav, R. Manthalkar, Y. Joshi, Effect of meditation on emotional response: an EEG-based study. Biomedical Signal Process. Control 34, 101–113 (2017)

    Google Scholar 

  22. D. Nie, X.-W. Wang, L.-C. Shi, B.-L. Lu, EEG-based emotion recognition during watching movies, in 5th International IEEE EMBS Conference on Neural Engineering, Cancun, Mexico, 2011

    Google Scholar 

  23. O.E. Krigolson, C.C. Williams, A. Norton, C.D. Hassall, F.L. Colino, Choosing MUSE: validation of a low-cost, portable EEG system for ERP research. Front. Neuro Sci. (2017). https://doi.org/10.3389/fnins.2017.00109

    Article  Google Scholar 

  24. A. Choo, A. May, Virtual Mindfulness Meditation: Virtual Reality and Electroencephalography for Health Gamification (Games Media Entertainment (GEM), Toronto, ON, Canada, 2014)

    Google Scholar 

  25. G. Perhakaran, A.M. Yusof, M.E. Rusli, M.Z.M. Yusoff, I. Mahalil, A.R.R. Zainuddin, A Study of Meditation Effectiveness for Virtual Reality Based Stress Therapy Using EEG Measurement and Questionnaire Approaches (Springer, Cham, 2016)

    Google Scholar 

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Acknowledgements

Department of Information Technology, K. J. Somaiya College of Engineering, Vidyavihar Mumbai developed this application in collaboration with Parallax Labs, LLP, Mumbai. We express our immense gratitude to the Somaiya Institute and Parallax Labs for their unwavering support and counsel. Additionally, we would like to appreciate the contribution of Ms. Simran Mehta, Bro. Yash Bheda, Bro. Purvish Shah, Bro. Rajendra Kadam, LY B. Tech. students, Department of Information Technology, K. J. Somaiya College of Engineering, for the success of this research.

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Correspondence to Hardik Jain .

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Pawade, D., Sakhapara, A., Rege, R., Gupta, S., Jain, H., Joshi, K. (2023). Meditation Therapy for Stress Management Using Brainwave Computing and Real Time Virtual Reality Feedback. In: Goswami, S., Barara, I.S., Goje, A., Mohan, C., Bruckstein, A.M. (eds) Data Management, Analytics and Innovation. ICDMAI 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 137. Springer, Singapore. https://doi.org/10.1007/978-981-19-2600-6_45

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