ArticleFrontiers in neuroscience2015
Autonomous Parameter Adjustment for SSVEP-Based BCIs with a Novel BCI Wizard.
Article in Frontiers in neuroscience, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 46 citations in OpenAlex.
- TSANet: multibranch attention deep neural network for classifying tactile selective attention in brain-computer interfaces.Biomedical engineering letters · 2024Article
- Brain-Computer Interface Speller Based on Steady-State Visual Evoked Potential: A Review Focusing on the Stimulus Paradigm and Performance.Brain sciences · 2021Review
- Asynchronous c-VEP communication tools-efficiency comparison of low-target, multi-target and dictionary-assisted BCI spellers.Scientific reports · 2020Article
- Comparison of Modern Highly Interactive Flicker-Free Steady State Motion Visual Evoked Potentials for Practical Brain-Computer Interfaces.Brain sciences · 2020Article
- Comparison of Different Visual Feedback Methods for SSVEP-Based BCIs.Brain sciences · 2020Article
- A Hybrid Speller Design Using Eye Tracking and SSVEP Brain-Computer Interface.Sensors (Basel, Switzerland) · 2020Article
- Learning Invariant Representations from EEG via Adversarial Inference.IEEE access : practical innovations, open solutions · 2020Article
- EEG-Based Brain-Computer Interfaces Using Motor-Imagery: Techniques and Challenges.Sensors (Basel, Switzerland) · 2019Review
- Article
- Brain-Computer Interface Spellers: A Review.Brain sciences · 2018Review
- A Novel Hybrid Mental Spelling Application Based on Eye Tracking and SSVEP-Based BCI.Brain sciences · 2017Article
- Driving a Semiautonomous Mobile Robotic Car Controlled by an SSVEP-Based BCI.Computational intelligence and neuroscience · 2016Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Brain-Computer Interfaces (BCIs) transfer human brain activities into computer commands and enable a communication channel without requiring movement. Among other BCI approaches, steady-state visual evoked potential (SSVEP)-based BCIs have the potential to become accurate, assistive technologies for persons with severe disabilities. Those systems require customization of different kinds of parameters (e.g., stimulation frequencies). Calibration usually requires selecting predefined parameters by experienced/trained personnel, though in real-life scenarios an interface allowing people with no experience in programming to set up the BCI would be desirable. Another occurring problem regarding BCI performance is BCI illiteracy (also called BCI deficiency). Many articles reported that BCI control could not be achieved by a non-negligible number of users. In order to bypass those problems we developed a SSVEP-BCI wizard, a system that automatically determines user-dependent key-parameters to customize SSVEP-based BCI systems. This wizard was tested and evaluated with 61 healthy subjects. All subjects were asked to spell the phrase "RHINE WAAL UNIVERSITY" with a spelling application after key parameters were determined by the wizard. Results show that all subjects were able to control the spelling application. A mean (SD) accuracy of 97.14 (3.73)% was reached (all subjects reached an accuracy above 85% and 25 subjects even reached 100% accuracy).
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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.