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Accepted for/Published in: JMIR Formative Research

Date Submitted: Dec 14, 2023
Open Peer Review Period: Dec 13, 2023 - Feb 7, 2024
Date Accepted: Oct 31, 2024
(closed for review but you can still tweet)

The final, peer-reviewed published version of this preprint can be found here:

Neurological Evidence of Diverse Self-Help Breathing Training With Virtual Reality and Biofeedback Assistance: Extensive Exploration Study of Electroencephalography Markers

Ng HyH, Wu CW, Hsu HC, Huang CM, Hsu AL, Chao YP, Jung TP, Chuang CH

Neurological Evidence of Diverse Self-Help Breathing Training With Virtual Reality and Biofeedback Assistance: Extensive Exploration Study of Electroencephalography Markers

JMIR Form Res 2024;8:e55478

DOI: 10.2196/55478

PMID: 39642375

PMCID: 11662191

Neurological Evidence of Diverse Self-Help Breathing Trainings with Virtual Reality and Bio-Feedback Assistance: An Extensive Exploration of EEG Markers

  • Hei-yin Hydra Ng; 
  • Changwei Wesley Wu; 
  • Hao-Che Hsu; 
  • Chih-Mao Huang; 
  • Ai-Ling Hsu; 
  • Yi-Ping Chao; 
  • Tzyy-Ping Jung; 
  • Chun-Hsiang Chuang

ABSTRACT

Background:

Recent advancements in Virtual Reality (VR) and Bio-feedback (BF) technologies have opened new avenues for breath training, particularly in individuals with psychological disorders. This study explores the integration of VR and BF to enhance user engagement in self-help breath training—a multifaceted approach encompassing mindful breathing, guided breathing, and breath counting techniques.

Objective:

Despite the availability of diverse breath training methods, their varying effectiveness and the underlying neuro-mechanisms remain insufficiently understood. We investigated using electroencephalography (EEG) indices across multiple breath training modalities to address this gap.

Methods:

Our VR-based breath training environment incorporated real-time EEG, heart rate, and breath signals monitoring. We examined four distinct breath training conditions in a cross-sectional experiment involving 51 healthy young adults.

Results:

Notably, EEG band power across theta, alpha, low-beta, high-beta, and gamma bands varied significantly over the entire scalp. Outflow analysis identified condition-specific variations in the delta, alpha, and gamma bands, while inflow analysis revealed significant differences across all frequency bands. Connectivity flow analysis highlighted the predominant influence of the right frontal, central, and parietal brain regions in the neuro-mechanisms underlying the breath training techniques.

Conclusions:

This study contributes neurological evidence supporting the effectiveness of self-help breath training through the combined use of VR and BF technologies. Our findings suggest the involvement of internal–external attention focus and the dorsal attention network in different breath training conditions. Furthermore, we propose avenues for future research, emphasizing the exploration of applications and gamification potential in combined VR and BF-guided breath training. Clinical Trial: The data collection process in this study did not meet the criteria of randomized controlled trial registration.


 Citation

Please cite as:

Ng HyH, Wu CW, Hsu HC, Huang CM, Hsu AL, Chao YP, Jung TP, Chuang CH

Neurological Evidence of Diverse Self-Help Breathing Training With Virtual Reality and Biofeedback Assistance: Extensive Exploration Study of Electroencephalography Markers

JMIR Form Res 2024;8:e55478

DOI: 10.2196/55478

PMID: 39642375

PMCID: 11662191

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