ArticleBrain sciences2017
A Novel Hybrid Mental Spelling Application Based on Eye Tracking and SSVEP-Based BCI.
Article in Brain sciences, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Enhancing EEG-Based Brain Pattern Recognition Through Functional-Network-Level Volume Conduction Mitigation: Spatially Informed Decay Modeling-Residual Correction.Brain sciences · 2026Article
- Supporting effective alternative access for individuals with physical disabilities: state of the science, emerging technologies, and future research directions.Augmentative and alternative communication (Baltimore, Md. : 1985) · 2025Review
- A robotic arm control system with simultaneous and sequential modes combining eye-tracking with steady-state visual evoked potential in virtual reality environment.Frontiers in neurorobotics · 2023Article
- Dual Passive Reactive Brain-Computer Interface: A Novel Approach to Human-Machine Symbiosis.Frontiers in neuroergonomics · 2022Article
- Novel Hybrid Brain-Computer Interface for Virtual Reality Applications Using Steady-State Visual-Evoked Potential-Based Brain-Computer Interface and Electrooculogram-Based Eye Tracking for Increased Information Transfer Rate.Frontiers in neuroinformatics · 2022Article
- Brain-Computer Interface Speller Based on Steady-State Visual Evoked Potential: A Review Focusing on the Stimulus Paradigm and Performance.Brain sciences · 2021Review
- An Open Source-Based BCI Application for Virtual World Tour and Its Usability Evaluation.Frontiers in human neuroscience · 2021Article
- Asynchronous c-VEP communication tools-efficiency comparison of low-target, multi-target and dictionary-assisted BCI spellers.Scientific reports · 2020Article
- Assessment of Human Visual Acuity Using Visual Evoked Potential: A Review.Sensors (Basel, Switzerland) · 2020Review
- Brain-Computer Interface-Based Humanoid Control: A Review.Sensors (Basel, Switzerland) · 2020Review
- A Hybrid Speller Design Using Eye Tracking and SSVEP Brain-Computer Interface.Sensors (Basel, Switzerland) · 2020Article
- Classification of Drowsiness Levels Based on a Deep Spatio-Temporal Convolutional Bidirectional LSTM Network Using Electroencephalography Signals.Brain sciences · 2019Article
- EEG-Based Brain-Computer Interfaces Using Motor-Imagery: Techniques and Challenges.Sensors (Basel, Switzerland) · 2019Review
- Robust Fusion of c-VEP and Gaze.IEEE sensors letters · 2019Article
- Article
- Brain-Computer Interface Spellers: A Review.Brain sciences · 2018Review
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Steady state visual evoked potentials (SSVEPs)-based Brain-Computer interfaces (BCIs), as well as eyetracking devices, provide a pathway for re-establishing communication for people with severe disabilities. We fused these control techniques into a novel eyetracking/SSVEP hybrid system, which utilizes eye tracking for initial rough selection and the SSVEP technology for fine target activation. Based on our previous studies, only four stimuli were used for the SSVEP aspect, granting sufficient control for most BCI users. As Eye tracking data is not used for activation of letters, false positives due to inappropriate dwell times are avoided. This novel approach combines the high speed of eye tracking systems and the high classification accuracies of low target SSVEP-based BCIs, leading to an optimal combination of both methods. We evaluated accuracy and speed of the proposed hybrid system with a 30-target spelling application implementing all three control approaches (pure eye tracking, SSVEP and the hybrid system) with 32 participants. Although the highest information transfer rates (ITRs) were achieved with pure eye tracking, a considerable amount of subjects was not able to gain sufficient control over the stand-alone eye-tracking device or the pure SSVEP system (78.13% and 75% of the participants reached reliable control, respectively). In this respect, the proposed hybrid was most universal (over 90% of users achieved reliable control), and outperformed the pure SSVEP system in terms of speed and user friendliness. The presented hybrid system might offer communication to a wider range of users in comparison to the standard techniques.
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