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

BACKGROUND

Recent advancements in virtual reality (VR) and biofeedback (BF) technologies have opened new avenues for breathing training. Breathing training has been suggested as an effective means for mental disorders, but it is difficult to master the technique at the beginning. VR-BF technologies address the problem of breathing, and visualizing breathing may facilitate the learning of breathing training. This study explores the integration of VR and BF to enhance user engagement in self-help breathing training, which is a multifaceted approach encompassing mindful breathing, guided breathing, and breath counting techniques.

OBJECTIVE

We identified 3 common breathing training techniques in previous studies, namely mindful breathing, guided breathing, and breath counting. Despite the availability of diverse breathing training methods, their varying effectiveness and underlying neurological mechanisms remain insufficiently understood. We investigated using electroencephalography (EEG) indices across multiple breathing training modalities to address this gap.

METHODS

Our automated VR-based breathing training environment incorporated real-time EEG, heart rate, and breath signal BF. We examined 4 distinct breathing training conditions (resting, mindful breathing, guided breathing, and breath counting) in a cross-sectional experiment involving 51 healthy young adults, who were recruited through online forum advertisements and billboard posters. In an experimental session, participants practiced resting state and each breathing training technique for 6 minutes. We then compared the neurological differences across the 4 conditions in terms of EEG band power and EEG effective connectivity outflow and inflow with repeated measures ANOVA and paired t tests.

RESULTS

The analyses included the data of 51 participants. Notably, EEG band power across the theta, alpha, low-beta, high-beta, and gamma bands varied significantly over the entire scalp (t ≥1.96, P values <.05). Outflow analysis identified condition-specific variations in the delta, alpha, and gamma bands (P values <.05), while inflow analysis revealed significant differences across all frequency bands (P values <.05). Connectivity flow analysis highlighted the predominant influence of the right frontal, central, and parietal brain regions in the neurological mechanisms underlying the breathing training techniques.

CONCLUSIONS

This study provides neurological evidence supporting the effectiveness of self-help breathing 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 breathing training conditions. There is a huge potential for the use of breathing training with VR-BF techniques in terms of clinical settings, the new living style since COVID-19, and the commercial value of introducing VR-BF breathing training into consumer-level digital products. Furthermore, we propose avenues for future research with an emphasis on the exploration of applications and the gamification potential in combined VR and BF breathing training.

TRIAL REGISTRATION

ClinicalTrials.gov NCT06656741; https://clinicaltrials.gov/study/NCT06656741.