ArticleFrontiers in human neuroscience2020
Wheelchair Control in a Virtual Environment by Healthy Participants Using a P300-BCI Based on Tactile Stimulation: Training Effects and Usability.
Article in Frontiers in human neuroscience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 32 citations in OpenAlex.
- Recording the tactile P300 with the cEEGrid for potential use in a brain-computer interface.Frontiers in human neuroscience · 2024Article
- Enhancing Cross-Subject Motor Imagery Classification in EEG-Based Brain-Computer Interfaces by Using Multi-Branch CNN.Sensors (Basel, Switzerland) · 2023Article
- Brain-Computer Interface Based on Steady-State Visual Evoked Potential Using Quick-Response Code Pattern for Wheelchair Control.Sensors (Basel, Switzerland) · 2023Article
- A Symbols Based BCI Paradigm for Intelligent Home Control Using P300 Event-Related Potentials.Sensors (Basel, Switzerland) · 2022Article
- Identifying potential training factors in a vibrotactile P300-BCI.Scientific reports · 2022Article
- Workshops of the Eighth International Brain-Computer Interface Meeting: BCIs: The Next Frontier.Brain computer interfaces (Abingdon, England) · 2022Article
- Disrupted gut microbiota aggravates working memory dysfunction induced by high-altitude exposure in mice.Frontiers in microbiology · 2022Article
- Immediate effects of short-term meditation on sensorimotor rhythm-based brain-computer interface performance.Frontiers in human neuroscience · 2022Article
- Use of Force Feedback Device in a Hybrid Brain-Computer Interface Based on SSVEP, EOG and Eye Tracking for Sorting Items.Sensors (Basel, Switzerland) · 2021Article
- Summary of over Fifty Years with Brain-Computer Interfaces-A Review.Brain sciences · 2021Review
- A P300 Brain-Computer Interface Paradigm Based on Electric and Vibration Simple Command Tactile Stimulation.Frontiers in human neuroscience · 2021Article
- Feedback Related Potentials for EEG-Based Typing Systems.Frontiers in human neuroscience · 2021Article
- A Comparison of Classification Techniques to Predict Brain-Computer Interfaces Accuracy Using Classifier-Based Latency Estimation.Brain sciences · 2020Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tactile stimulation is less frequently used than visual for brain-computer interface (BCI) control, partly because of limitations in speed and accuracy. Non-visual BCI paradigms, however, may be required for patients who struggle with vision dependent BCIs because of a loss of gaze control. With the present study, we attempted to replicate earlier results by Herweg et al. (2016), with several minor adjustments and a focus on training effects and usability. We invited 16 healthy participants and trained them with a 4-class tactile P300-based BCI in five sessions. Their main task was to navigate a virtual wheelchair through a 3D apartment using the BCI. We found significant training effects on information transfer rate (ITR), which increased from a mean of 3.10-9.50 bits/min. Further, both online and offline accuracies significantly increased with training from 65% to 86% and 70% to 95%, respectively. We found only a descriptive increase of P300 amplitudes at Fz and Cz with training. Furthermore, we report subjective data from questionnaires, which indicated a relatively high workload and moderate to high satisfaction. Although our participants have not achieved the same high performance as in the Herweg et al. (2016) study, we provide evidence for training effects on performance with a tactile BCI and confirm the feasibility of the paradigm.
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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.