Slow Breathing Exercise with Multimodal Virtual Reality: A Feasibility Study
Abstract
:1. Introduction
2. Related Work
2.1. Breathing Control Training
2.2. Respiratory Feedback
2.3. Virtual Realty
3. Method
3.1. System Architecture
3.2. Hardware
3.2.1. VR Headset
3.2.2. EGG Sensor
3.2.3. T-Shirt with a Heating Pad and a Pressure Sensor
3.2.4. Computation Module
3.3. Sensor Data Collection and Visualization
3.3.1. Breathing Data
3.3.2. Visualization
3.4. User Preparation
4. Experiment and Result
- Can the proposed system improve the breathing control of the user?
- Does the proposed system have any effect on the meditation, in terms of the changes of EEG alpha and theta bands [28]?
4.1. Experiment Procedure
4.2. Results
5. Discussion
6. Conclusions and Future Work
Author Contributions
Funding
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Sivakumar, G.; Prabhu, K.; Baliga, R.; Pai, M.K.; Manjunatha, S. Acute effects of deep breathing for a short duration (2–10 minutes) on pulmonary functions in healthy young volunteers. Indian J. Physiol. Pharmacol. 2012, 55, 154–159. [Google Scholar]
- Jerath, R.; Edry, J.W.; Barnes, V.A.; Jerath, V. Physiology of long pranayamic breathing: Neural respiratory elements may provide a mechanism that explains how slow deep breathing shifts the autonomic nervous system. Med. Hypotheses 2006, 67, 566–571. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Brown, R.P.; Gerbarg, P.L. Sudarshan Kriya Yogic Breathing in the Treatment of Stress, Anxiety, and Depression: Part I—Neurophysiologic Model. J. Altern. Complement. Med. 2005, 11, 189–201. [Google Scholar] [CrossRef]
- Joseph, C.N.; Porta, C.; Casucci, G.; Casiraghi, N.; Maffeis, M.; Rossi, M.; Bernardi, L. Slow Breathing Improves Arterial Baroreflex Sensitivity and Decreases Blood Pressure in Essential Hypertension. Hypertension 2005, 46, 714–718. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Zautra, A.J.; Fasman, R.; Davis, M.C.; Craig, A.D. The effects of slow breathing on affective responses to pain stimuli: An experimental study. Pain 2010, 149, 12–18. [Google Scholar] [CrossRef]
- Mason, H.; Vandoni, M.; DeBarbieri, G.; Codrons, E.; Ugargol, V.; Bernardi, L. Cardiovascular and Respiratory Effect of Yogic Slow Breathing in the Yoga Beginner: What Is the Best Approach? Evid. Based Complement. Altern. Med. 2013, 2013, 743504. [Google Scholar] [CrossRef] [Green Version]
- Pal, G.K.; Velkumary, S.; Madanmohan, A. Effect of short-term practice of breathing exercises on autonomic functions in normal human volunteers. Indian J. Med. Res. 2004, 120, 115. [Google Scholar]
- Radaelli, A.; Raco, R.; Perfetti, P.; Viola, A.; Azzellino, A.; Signorini, M.G.; Ferrari, A.U. Effects of slow, controlled breathing on baroreceptor control of heart rate and blood pressure in healthy men. J. Hypertens. 2004, 22, 1361–1370. [Google Scholar] [CrossRef]
- Wang, S.-Z.; Li, S.; Xu, X.-Y.; Lin, G.-P.; Shao, L.; Zhao, Y.; Wang, T.H. Effect of Slow Abdominal Breathing Combined with Biofeedback on Blood Pressure and Heart Rate Variability in Prehypertension. J. Altern. Complement. Med. 2010, 16, 1039–1045. [Google Scholar] [CrossRef]
- Ma, X.; Yue, Z.-Q.; Gong, Z.-Q.; Zhang, H.; Duan, N.-Y.; Shi, Y.-T.; Wei, G.-X.; Li, Y.-F.; Li, Y. The Effect of Diaphragmatic Breathing on Attention, Negative Affect and Stress in Healthy Adults. Front. Psychol. 2017, 8, 874. [Google Scholar] [CrossRef] [Green Version]
- Frank, D.L.; Khorshid, L.; Kiffer, J.F.; Moravec, C.S.; McKee, M.G. Biofeedback in medicine: Who, when, why and how? Ment. Health Fam. Med. 2010, 7, 85–91. [Google Scholar]
- Blum, J.; Rockstroh, C.; Göritz, A.S. Heart Rate Variability Biofeedback Based on Slow-Paced Breathing With Immersive Virtual Reality Nature Scenery. Front. Psychol. 2019, 10, 2172. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Rockstroh, C.; Blum, J.; Göritz, A.S. A mobile VR-based respiratory biofeedback game to foster diaphragmatic breathing. Virtual Real. 2021, 25, 539–552. [Google Scholar] [CrossRef]
- Cummings, J.J.; Bailenson, J.N. How immersive is enough? A meta-analysis of the effect of immersive technology on user presence. Med. Psychol. 2016, 19, 272–309. [Google Scholar] [CrossRef]
- Sanchez-Vives, M.V.; Slater, M. From presence to consciousness through virtual reality. Nat. Rev. Neurosci. 2005, 6, 332–366. [Google Scholar] [CrossRef] [PubMed]
- Kaplan, S. The restorative benefits of nature: Toward an integrative framework. J. Environ. Psychol. 1995, 15, 169–182. [Google Scholar] [CrossRef]
- Amihai, I.; Kozhevnikov, M. The Influence of Buddhist Meditation Traditions on the Autonomic System and Attention. BioMed. Res. Int. 2015, 2015, 731579. [Google Scholar] [CrossRef] [PubMed]
- Takahashi, T.; Murata, T.; Hamada, T.; Omori, M.; Kosaka, H.; Kikuchi, M.; Yoshida, H.; Wada, Y. Changes in EEG and autonomic nervous activity during meditation and their association with personality traits. Int. J. Psychophysiol. 2005, 55, 199–207. [Google Scholar] [CrossRef]
- Murata, T.; Takahashi, T.; Hamada, T.; Omori, M.; Kosaka, H.; Yoshida, H.; Wada, Y. Individual Trait Anxiety Levels Characterizing the Properties of Zen Meditation. Neuropsychobiology 2004, 50, 189–194. [Google Scholar] [CrossRef] [PubMed]
- Arambula, P.; Peper, E.; Kawakami, M.; Gibney, K.H. The Physiological Correlates of Kundalini Yoga Meditation: A Study of a Yoga Master. Appl. Psychophysiol. Biofeedback 2001, 26, 147–153. [Google Scholar] [CrossRef] [PubMed]
- Kamei, T.; Toriumi, Y.; Kimura, H.; Kumano, H.; Ohno, S.; Kimura, K. Decrease in Serum Cortisol during Yoga Exercise is Correlated with Alpha Wave Activation. Percept. Mot. Ski. 2000, 90, 1027–1032. [Google Scholar] [CrossRef] [PubMed]
- Belman, M.J.; Thomas, S.G.; Lewis, M.I. Resistive Breathing Training in Patients with Chronic Obstructive Pulmonary Disease. Chest 1986, 90, 662–669. [Google Scholar] [CrossRef] [Green Version]
- Russo, M.A.; Santarelli, D.; O’Rourke, D. The physiological effects of slow breathing in the healthy human. Breathe 2017, 13, 298–309. [Google Scholar] [CrossRef]
- Sackner, M.A.; Gonzalez, H.F.; Jenouri, G.; Rodriguez, M. Effects of abdominal and thoracic breathing on breathing pattern components in normal Trainees and in patients with chronic obstructive pulmonary disease. Am. Rev. Respir. Dis. 1984, 130, 584–587. [Google Scholar] [PubMed]
- Zhang, Z.; Wu, H.; Wang, W.; Wang, B. A smartphone based respiratory biofeedback system. In Proceedings of the 2010 3rd International Conference on Biomedical Engineering and Informatics, Yantai, China, 16–18 October 2010; Volume 2, pp. 717–720. [Google Scholar]
- Pastor, M.C.; Menéndez, F.J.; Sanz, M.T.; Abad, E.V. The Influence of Respiration on Biofeedback Techniques. Appl. Psychophysiol. Biofeedback 2008, 33, 49–54. [Google Scholar] [CrossRef]
- Uhlmann, C.; Fröscher, W. Biofeedback treatment in patients with refractory epilepsy: Changes in depression and control orientation. Seizure 2001, 10, 34–38. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Tinga, A.M.; Nyklíček, I.; Jansen, M.-P.; De Back, T.T.; Louwerse, M.M. Respiratory Biofeedback Does Not Facilitate Lowering Arousal in Meditation through Virtual Reality. Appl. Psychophysiol. Biofeedback 2019, 44, 51–59. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- MCQE. Astronomy VR. 2019. Available online: https://store.steampowered.com/app/1062690/Astronomy_VR/ (accessed on 1 June 2019).
- PaleBlue XYZ. Number Hunt. 2018. Available online: https://store.steampowered.com/app/851770/Number_Hunt/ (accessed on 1 June 2019).
- STRIVR. 30 Percentage Point Increase in Recall of Topics After Using STRIVR. 2017. Available online: https://www.strivr.com/30-percent-increase-in-recall/ (accessed on 1 June 2019).
- EON Reality. EON Sports VR Project OPS with Jason Giambi. 2015. Available online: https://www.youtube.com/watch?v=KTOrNNqtTTE (accessed on 1 June 2019).
- Balfour Beatty. Virtual Reality Is Shaping the Future of Construction. 2016. Available online: https://www.youtube.com/watch?v=R4gWpXuPAXo (accessed on 1 June 2019).
- Ford Motor Company. Virtual Reality at Ford Motor Company. 2012. Available online: https://www.youtube.com/watch?v=zmeR-u-DioE (accessed on 1 June 2019).
- Powers, M.B.; Emmelkamp, P. Virtual reality exposure therapy for anxiety disorders: A meta-analysis. J. Anxiety Disord. 2008, 22, 561–569. [Google Scholar] [CrossRef]
- Cho, B.H.; Lee, J.M.; Ku, J.H.; Jang, D.P.; Kim, J.S.; Kim, I.Y.; Lee, J.H.; Kim, S.I. Attention Enhancement System using virtual reality and EEG biofeedback. In Proceedings of the IEEE Virtual Reality 2002, Orlando, FL, USA, 24–28 March 2002; pp. 156–163. [Google Scholar]
- Wake, N.; Sano, Y.; Oya, R.; Sumitani, M.; Kumagaya, S.-I.; Kuniyoshi, Y. Multimodal virtual reality platform for the rehabilitation of phantom limb pain. In Proceedings of the 2015 7th International IEEE/EMBS Conference on Neural Engineering (NER), Montpellier, France, 22–24 April 2015; pp. 787–790. [Google Scholar]
- Vitense, H.S.; Jacko, J.A.; Emery, V. Multimodal feedback: An assessment of performance and mental workload. Ergonomics 2003, 46, 68–87. [Google Scholar] [CrossRef] [PubMed]
- Haas, J.K. A History of the Unity Game Engine; Worcester Polytechnic Institute: Worcester, MA, USA, 2014. [Google Scholar]
- Available online: https://www.youtube.com/watch?v=tRVq8Tmf8KY (accessed on 1 June 2019).
- Chiesa, A. Zen Meditation: An Integration of Current Evidence. J. Altern. Complement. Med. 2009, 15, 585–592. [Google Scholar] [CrossRef] [PubMed]
- Available online: https://store.neurosky.com/ (accessed on 1 June 2019).
- FSR 406 Data Sheet. Available online: https://cdn.sparkfun.com/assets/c/4/6/8/b/2010-10-26-DataSheet-FSR406-Layout2.pdf (accessed on 1 June 2019).
- Pettinati, P.M. Meditation, yoga, and guided imagery. Nurs. Clin. N. Am. 2001, 36, 11342401. [Google Scholar]
- Kozhevnikov, M.; Elliott, J.; Shephard, J.; Gramann, K. Neurocognitive and Somatic Components of Temperature Increases during g-Tummo Meditation: Legend and Reality. PLoS ONE 2013, 8, e58244. [Google Scholar] [CrossRef] [Green Version]
- Elgendi, M.; Norton, I.; Brearley, M.; Abbott, D.; Schuurmans, D. Systolic Peak Detection in Acceleration Photoplethysmograms Measured from Emergency Responders in Tropical Conditions. PLoS ONE 2013, 8, e76585. [Google Scholar] [CrossRef] [Green Version]
- TAFI AVATARS. MCS Male. 2017. Available online: https://assetstore.unity.com/packages/3d/characters/humanoids/mcs-male-45805 (accessed on 1 June 2019).
- Aris, S.A.M.; Lias, S.; Taib, M.N. The relationship of alpha waves and theta waves in EEG during relaxation and IQ test. In Proceedings of the 2010 2nd International Congress on Engineering Education, Kuala Lumpur, Malaysia, 8–9 December 2010; pp. 69–72. [Google Scholar] [CrossRef]
- Park, Y.-J. Clinical utility of paced breathing as a concentration meditation practice. Complement. Ther. Med. 2012, 20, 393–399. [Google Scholar] [CrossRef] [PubMed]
- Nargundkar, S.; Manage, P.; Desai, V. A Survey on Effects of Various Meditation Interventions on Overall Performance of College Students. In Proceedings of the 2020 IEEE Bangalore Humanitarian Technology Conference (B-HTC), Vijiyapur, India, 8–10 October 2020; pp. 1–6. [Google Scholar]
- Schleicher, R.; Galley, N.; Briest, S.; Galley, L. Blinks and saccades as indicators of fatigue in sleepiness warnings: Looking tired? Ergonomics 2008, 51, 982–1010. [Google Scholar] [CrossRef]
- Caffier, P.P.; Erdmann, U.; Ullsperger, P. Experimental evaluation of eye-blink parameters as a drowsiness measure. Graefe’s Arch. Clin. Exp. Ophthalmol. 2003, 89, 319–325. [Google Scholar] [CrossRef] [PubMed]
- Chang, W.-D.; Cha, H.-S.; Kim, K.; Im, C.-H. Detection of eye blink artifacts from single prefrontal channel electroencephalogram. Comput. Methods Programs Biomed. 2016, 124, 19–30. [Google Scholar] [CrossRef]
- Rani, M.S.B.A.; Mansor, W.B. Detection of eye blinks from EEG signals for home lighting system activation. In Proceedings of the 2009 6th International Symposium on Mechatronics and Its Applications, Sharjah, United Arab Emirates, 23–26 March 2009; pp. 1–4. [Google Scholar] [CrossRef]
- Nguyen, T.; Nguyen, T.H.; Truong, K.Q.D.; Van Vo, T. A Mean Threshold Algorithm for Human Eye Blinking Detection Using EEG. In 4th International Conference on Biomedical Engineering in Vietnam; Toi, V., Toan, N., Dang Khoa, T., Lien Phuong, T., Eds.; IFMBE Proceedings; Springer: Berlin/Heidelberg, Germany, 2013; Volume 49. [Google Scholar]
- Romano, D.M.; Brna, P. Presence and Reflection in Training: Support for Learning to Improve Quality Decision-Making Skills under Time Limitations. CyberPsychol. Behav. 2001, 4, 265–277. [Google Scholar] [CrossRef]
- Gopher, D. Skill training in Multimodal virtual environments. Work 2012, 41, 2284–2287. [Google Scholar] [CrossRef] [Green Version]
- Kim, Y.I.; Jung, S.-Y.; Min, S.; Seol, E.; Seo, S.; Hur, J.-W.; Jung, D.; Lee, H.-J.; Lee, S.; Kim, G.J.; et al. Visuo-Haptic-Based Multimodal Feedback Virtual Reality Solution to Improve Anxiety Symptoms: A Proof-of-Concept Study. Psychiatry Investig. 2019, 16, 167–171. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Badarny, S.; Aharon-Peretz, J.; Susel, Z.; Habib, G.; Baram, Y. Virtual Reality Feedback Cues for Improvement of Gait in Patients with Parkinson’s Disease. Tremor Other Hyperkinet. Mov. 2014, 4, 225. [Google Scholar] [CrossRef]
- Griffin, H.J.; Greenlaw, R.; Limousin, P.; Bhatia, K.; Quinn, N.P.; Jahanshahi, M. The effect of real and virtual visual cues on walking in Parkinson’s disease. J. Neurol. 2011, 258, 991–1000. [Google Scholar] [CrossRef]
- Kishi, T.; Ogata, T.; Ora, H.; Shigeyama, R.; Nakayama, M.; Seki, M.; Orimo, S.; Miyake, Y. Synchronized Tactile Stimulation on Upper Limbs Using a Wearable Robot for Gait Assistance in Patients With Parkinson’s Disease. Front. Robot. AI. 2020, 7, 10–21. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- van Rooij, M.; Lobel, A.; Harris, O.; Smit, N.; Granic, I. DEEP: A biofeedback virtual reality game for children at-risk for anxiety. In Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems, San Jose, CA, USA, 7–12 May 2016; pp. 1989–1997. [Google Scholar]
Study | Application |
---|---|
[24] | Effects of abdominal and thoracic breathing on breathing pattern components |
[25] | Smartphone-based respiration training |
[26] | The relationship between respiratory patterns and SCL (Skin conductance level) |
[27] | Effect of respiratory feedback for patients with refractory epilepsy |
[28] | Respiratory feedback through virtual reality |
Number of subjects | 20 (10 for control group and 10 for feedback group) |
Environment condition |
|
Inclusion criteria |
|
Duration of experiments | Eight 20 min training sessions were carried out within 2 weeks (four sessions per week). |
Time | Between 2 pm and 5 pm |
Notes to the subject before the experiment begins |
|
Baseline trial |
|
Training session |
|
1. I find this breathing control experiment enjoyable |
2. I was able to focus on my breathing without any distraction |
3. During the experiment, I felt that my breathing rate was reduced |
4. I think it is easy to use this system (clothes, sensors, etc.) |
5. I do not think I need technical support to use this system |
6. I will continue doing meditation training in the future |
7. This system is suitable for meditation-related applications |
8. I do not need to learn anything before I can use this system |
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Lan, K.-C.; Li, C.-W.; Cheung, Y. Slow Breathing Exercise with Multimodal Virtual Reality: A Feasibility Study. Sensors 2021, 21, 5462. https://doi.org/10.3390/s21165462
Lan K-C, Li C-W, Cheung Y. Slow Breathing Exercise with Multimodal Virtual Reality: A Feasibility Study. Sensors. 2021; 21(16):5462. https://doi.org/10.3390/s21165462
Chicago/Turabian StyleLan, Kun-Chan, Che-Wei Li, and Yushing Cheung. 2021. "Slow Breathing Exercise with Multimodal Virtual Reality: A Feasibility Study" Sensors 21, no. 16: 5462. https://doi.org/10.3390/s21165462
APA StyleLan, K.-C., Li, C.-W., & Cheung, Y. (2021). Slow Breathing Exercise with Multimodal Virtual Reality: A Feasibility Study. Sensors, 21(16), 5462. https://doi.org/10.3390/s21165462