SynthesisPloS one2017
A systematic review of hybrid brain-computer interfaces: Taxonomy and usability perspectives.
Synthesis in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 4 of them syntheses that pooled it.
What it found
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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.
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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.
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Who cites it
37 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Knowledge mapping and research trends of brain-computer interface technology in rehabilitation: a bibliometric analysis.Frontiers in human neuroscience · 2024Pooled it
- EEG-based Brain-Computer Interfaces for people with Disorders of Consciousness: Features and applications. A systematic review.Frontiers in human neuroscience · 2022Pooled it
- A systematic review of research on augmentative and alternative communication brain-computer interface systems for individuals with disabilities.Frontiers in human neuroscience · 2022Pooled it
- Brain-Computer Interfaces for Children With Complex Communication Needs and Limited Mobility: A Systematic Review.Frontiers in human neuroscience · 2021Pooled it
- Technical system of electroencephalography-based brain-computer interface: Advances, applications, and challenges.Neural regeneration research · 2026Article
- Harnessing Neuroplasticity: The Role of Priming in Enhancing Post Stroke Motor Function.Restorative neurology and neuroscience · 2026Review
- Dual-Mode Visual System for Brain-Computer Interfaces: Integrating SSVEP and P300 Responses.Sensors (Basel, Switzerland) · 2025Article
- Assessing the data quality of AdHawk MindLink eye-tracking glasses.Behavior research methods · 2024Article
- User Evaluation of a Shared Robot Control System Combining BCI and Eye Tracking in a Portable Augmented Reality User Interface.Sensors (Basel, Switzerland) · 2024Article
- Considerations and discussions on the clear definition and definite scope of brain-computer interfaces.Frontiers in neuroscience · 2024Review
- What stakeholders with neurodegenerative conditions value about speech and accuracy in development of BCI systems for communication.Brain computer interfaces (Abingdon, England) · 2024Article
- Recording the tactile P300 with the cEEGrid for potential use in a brain-computer interface.Frontiers in human neuroscience · 2024Article
- Human factors engineering of BCI: an evaluation for satisfaction of BCI based on motor imagery.Cognitive neurodynamics · 2023Article
- Brain-computer interface paradigms and neural coding.Frontiers in neuroscience · 2023Review
- Identifying Thematics in a Brain-Computer Interface Research.Computational intelligence and neuroscience · 2023Review
- A case for hybrid BCIs: combining optical and electrical modalities improves accuracy.Frontiers in human neuroscience · 2023Article
- Investigating User Proficiency of Motor Imagery for EEG-Based BCI System to Control Simulated Wheelchair.Sensors (Basel, Switzerland) · 2022Article
- A novel multiple time-frequency sequential coding strategy for hybrid brain-computer interface.Frontiers in human neuroscience · 2022Article
- EEG-fNIRS-based hybrid image construction and classification using CNN-LSTM.Frontiers in neurorobotics · 2022Article
- EEG hybrid brain-computer interfaces: A scoping review applying an existing hybrid-BCI taxonomy and considerations for pediatric applications.Frontiers in human neuroscience · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A new Brain-Computer Interface (BCI) technique, which is called a hybrid BCI, has recently been proposed to address the limitations of conventional single BCI system. Although some hybrid BCI studies have shown promising results, the field of hybrid BCI is still in its infancy and there is much to be done. Especially, since the hybrid BCI systems are so complicated and complex, it is difficult to understand the constituent and role of a hybrid BCI system at a glance. Also, the complicated and complex systems make it difficult to evaluate the usability of the systems. We systematically reviewed and analyzed the current state-of-the-art hybrid BCI studies, and proposed a systematic taxonomy for classifying the types of hybrid BCIs with multiple taxonomic criteria. After reviewing 74 journal articles, hybrid BCIs could be categorized with respect to 1) the source of brain signals, 2) the characteristics of the brain signal, and 3) the characteristics of operation in each system. In addition, we exhaustively reviewed recent literature on usability of BCIs. To identify the key evaluation dimensions of usability, we focused on task and measurement characteristics of BCI usability. We classified and summarized 31 BCI usability journal articles according to task characteristics (type and description of task) and measurement characteristics (subjective and objective measures). Afterwards, we proposed usability dimensions for BCI and hybrid BCI systems according to three core-constructs: Satisfaction, effectiveness, and efficiency with recommendations for further research. This paper can help BCI researchers, even those who are new to the field, can easily understand the complex structure of the hybrid systems at a glance. Recommendations for future research can also be helpful in establishing research directions and gaining insight in how to solve ergonomics and HCI design issues surrounding BCI and hybrid BCI systems by usability evaluation.
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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.