ReviewNeuroinformatics2019
EEG-EOG based Virtual Keyboard: Toward Hybrid Brain Computer Interface.
Review in Neuroinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Brain-Computer Interfaces for Children With Complex Communication Needs and Limited Mobility: A Systematic Review.Frontiers in human neuroscience · 2021Pooled it
- Smart Nursing Wheelchairs: A New Trend in Assisted Care and the Future of Multifunctional Integration.Biomimetics (Basel, Switzerland) · 2024Review
- The role of eye movement signals in non-invasive brain-computer interface typing system.Medical & biological engineering & computing · 2024Review
- High-performance and low-power source-gated transistors enabled by a solution-processed metal oxide homojunction.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Emerging Wearable Biosensor Technologies for Stress Monitoring and Their Real-World Applications.Biosensors · 2022Article
- Advances in Materials, Sensors, and Integrated Systems for Monitoring Eye Movements.Biosensors · 2022Review
- Development of a Sensing Platform Based on Hands-Free Interfaces for Controlling Electronic Devices.Frontiers in human neuroscience · 2022Article
- Toward a Brain-Computer Interface- and Internet of Things-Based Smart Ward Collaborative System Using Hybrid Signals.Journal of healthcare engineering · 2022Article
- Review of Riemannian Distances and Divergences, Applied to SSVEP-based BCI.Neuroinformatics · 2021Review
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
No grant is acknowledged in the PubMed record.
Abstract
The past twenty years have ignited a new spark in the research of Electroencephalogram (EEG), which was pursued to develop innovative Brain Computer Interfaces (BCIs) in order to help severely disabled people live a better life with a high degree of independence. Current BCIs are more theoretical than practical and are suffering from numerous challenges. New trends of research propose combining EEG to other simple and efficient bioelectric inputs such as Electro-oculography (EOG) resulting from eye movements, to produce more practical and robust Hybrid Brain Computer Interface systems (hBCI) or Brain/Neuronal Computer Interface (BNCI). Working towards this purpose, existing research in EOG based Human Computer Interaction (HCI) applications, must be organized and surveyed in order to develop a vision on the potential benefits of combining both input modalities and give rise to new designs that maximize these benefits. Our aim is to support and inspire the design of new hBCI systems based on both EEG and EOG signals, in doing so; first the current EOG based HCI systems were surveyed with a particular focus on EOG based systems for communication using virtual keyboard. Then, a survey of the current EEG-EOG virtual keyboard was performed highlighting the design protocols employed. We concluded with a discussion of the potential advantages of combining both systems with recommendations to give deep insight for future design issues for all EEG-EOG hBCI systems. Finally, a general architecture was proposed for a new EEG-EOG hBCI system. The proposed hybrid system completely alters the traditional view of the eye movement features present in EEG signal as artifacts that should be removed; instead EOG traces are extracted from EEG in our proposed hybrid architecture and are considered as an additional input modality sharing control according to the chosen design protocol.
Indexed as
Identifiers
30368637What 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.