ArticleTechnology2014
The impact of mind-body awareness training on the early learning of a brain-computer interface.
Article in Technology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled 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.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Influence of age, cognitive function, attention, and mental state on the effectiveness of EEG-based brain-computer interface device use: a systematic review.Journal of neuroengineering and rehabilitation · 2025Pooled it
- Motor imagery-based brain-computer interfaces: an exploration of multiclass motor imagery-based control for Emotiv EPOC X.Frontiers in neuroinformatics · 2025Article
- Non-Invasive Brain-Computer Interfaces: State of the Art and Trends.IEEE reviews in biomedical engineering · 2025Review
- Integrating Simultaneous Motor Imagery and Spatial Attention for EEG-BCI Control.IEEE transactions on bio-medical engineering · 2024Article
- Immediate effects of short-term meditation on sensorimotor rhythm-based brain-computer interface performance.Frontiers in human neuroscience · 2022Article
- Frontolimbic alpha activity tracks intentional rest BCI control improvement through mindfulness meditation.Scientific reports · 2021Article
- Mindfulness Improves Brain-Computer Interface Performance by Increasing Control Over Neural Activity in the Alpha Band.Cerebral cortex (New York, N.Y. : 1991) · 2021Article
- Effects of Long-Term Meditation Practices on Sensorimotor Rhythm-Based Brain-Computer Interface Learning.Frontiers in neuroscience · 2020Article
- Multiclass Classification Based on Combined Motor Imageries.Frontiers in neuroscience · 2020Article
- Exploring Training Effect in 42 Human Subjects Using a Non-invasive Sensorimotor Rhythm Based Online BCI.Frontiers in human neuroscience · 2019Article
- Exploring Cognitive Flexibility With a Noninvasive BCI Using Simultaneous Steady-State Visual Evoked Potentials and Sensorimotor Rhythms.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2018Article
- Combined rTMS and virtual reality brain-computer interface training for motor recovery after stroke.Journal of neural engineering · 2018Article
- Differential Subjective Experiences in Learners and Non-learners in Frontal Alpha Neurofeedback: Piloting a Mixed-Method Approach.Frontiers in human neuroscience · 2018Article
- A Study of the Effects of Electrode Number and Decoding Algorithm on Online EEG-Based BCI Behavioral Performance.Frontiers in neuroscience · 2018Article
- Target-directed motor imagery of the lower limb enhances event-related desynchronization.PloS one · 2017Article
- Effects of Soft Drinks on Resting State EEG and Brain-Computer Interface Performance.IEEE access : practical innovations, open solutions · 2017Article
- EEG Source Imaging Enhances the Decoding of Complex Right-Hand Motor Imagery Tasks.IEEE transactions on bio-medical engineering · 2016Article
- A novel channel selection method for optimal classification in different motor imagery BCI paradigms.Biomedical engineering online · 2015Article
- Systems Neuroengineering: Understanding and Interacting with the Brain.Engineering (Beijing, China) · 2015Article
- Noninvasive Brain-Computer Interfaces Based on Sensorimotor Rhythms.Proceedings of the IEEE. Institute of Electrical and Electronics Engineers · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Brain-computer interface (BCI) systems allow users to interact with their environment by bypassing muscular control to tap directly into the users' thoughts. In the present study, we investigate the role of prior experience with yoga and meditation, examples of formalized mind-body awareness training (MBAT), in learning to use a one-dimensional sensorimotor rhythm based BCI. Thirty-six human subjects volunteered to participate in two different cohorts based on past experience with MBAT - experienced MBAT practitioners and controls. All subjects participated in three BCI experiments to achieve competency in controlling the BCI system. The MBAT cohort achieved BCI competency significantly faster than the control cohort. In addition, the MBAT cohort demonstrated enhanced ability to control the system on various measures of BCI performance and improved significantly more over time when compared to control. Our work provides insight into valuable strategies for reducing barriers to BCI fluency that limit the more widespread use of these systems.
Identifiers
What OpenQuestion holds
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.