Evidence map›Paper›PMID 39642375›Full record

Trial reportJMIR formative research2024

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

Hei-Yin Hydra Ng, Changwei W Wu, Hao-Che Hsu, Chih-Mao Huang, Ai-Ling Hsu, Yi-Ping Chao, Tzyy-Ping Jung, Chun-Hsiang Chuang

Registry-linked trialAbstract readClinical Trial
In one paragraph

Trial report in JMIR formative research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06656741 (Neurological Evidence of Diverse Self-Help Breathing Trainings with Virtual Reality and Bio-Feedback Assistance), which is not on this map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT06656741 nacompletednot on this map

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

TypeinterventionalSponsorHei-Yin Hydra NgRan2021 to 2022Enrolled53ConditionsBreath Training StylesArmsResting State, Mindful Breathing, Guided Breathing, Breath Counting
3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Hei-Yin Hydra NgResearch Center for Education and Mind Sciences, College of Education, National Tsing Hua University, Hsinchu, Taiwan.ORCID 0000-0001-6547-7211
Changwei W WuGraduate Institute of Mind, Brain and Consciousness, Taipei Medical University, New Taipei, Taiwan.ORCID 0000-0001-8968-9366
Hao-Che HsuResearch Center for Education and Mind Sciences, College of Education, National Tsing Hua University, Hsinchu, Taiwan.ORCID 0000-0003-2108-4701
Chih-Mao HuangDepartment of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu, Taiwan.ORCID 0000-0002-6209-2575
Ai-Ling HsuCollege of Intelligent Computing, Chang Gung University, Taoyuan, Taiwan.ORCID 0000-0002-6801-4658
Yi-Ping ChaoDepartment of Computer Science and Information Engineering, Chang Gung University, Taoyuan, Taiwan.ORCID 0000-0002-1681-5410
Tzyy-Ping JungInstitute for Neural Computation and Institute of Engineering in Medicine, University of California, San Diego, La Jolla, CA, United States.ORCID 0000-0002-8377-2166
Chun-Hsiang ChuangResearch Center for Education and Mind Sciences, College of Education, National Tsing Hua University, Hsinchu, Taiwan.ORCID 0000-0002-5043-8380

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRecent 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.

objectiveWe 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.

methodsOur 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.

resultsThe 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.

conclusionsThis 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 registrationClinicalTrials.gov NCT06656741; https://clinicaltrials.gov/study/NCT06656741.

Indexed as

Biofeedback, PsychologyBreathing ExercisesElectroencephalographyVirtual RealityAdultCross-Sectional StudiesFemaleHumansMaleYoung Adultbiofeedbackbreathing trainingEEGeffective connectivityelectroencephalographyvirtual reality

Identifiers

PMID39642375
PMCPMC11662191

What OpenQuestion holds

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LicenceCC BY
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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.