ReviewComputational intelligence and neuroscience2019
Advances in Hybrid Brain-Computer Interfaces: Principles, Design, and Applications.
Review in Computational intelligence and neuroscience, 2019. 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.
- Brain-computer interfaces: innovations and challenges in the field of cerebral palsy rehabilitation.Italian journal of pediatrics · 2026Review
- A Wearable Multimodal Assistive Interface for Virtual Cursor Control in Stroke Survivors with Upper-Limb Impairment.Sensors (Basel, Switzerland) · 2026Article
- Evolving Therapeutic Landscape of Intracerebral Hemorrhage: Emerging Cutting-Edge Advancements in Surgical Robots, Regenerative Medicine, and Neurorehabilitation Techniques.Translational stroke research · 2025Review
- RSVP keyboard with inquiry preview: mixed performance and user experience with an adaptive, multimodal typing interface combining EEG and switch input.Journal of neural engineering · 2025Article
- A motor imagery classification model based on hybrid brain-computer interface and multitask learning of electroencephalographic and electromyographic deep features.Frontiers in physiology · 2024Article
- EEG Amplitude Modulation Analysis across Mental Tasks: Towards Improved Active BCIs.Sensors (Basel, Switzerland) · 2023Article
- Metaheuristic Optimization-Based Feature Selection for Imagery and Arithmetic Tasks: An fNIRS Study.Sensors (Basel, Switzerland) · 2023Article
- Brain-computer interface paradigms and neural coding.Frontiers in neuroscience · 2023Review
- EEG-EMG coupling as a hybrid method for steering detection in car driving settings.Cognitive neurodynamics · 2022Article
- Brain-Computer Interfaces for Awareness Detection, Auxiliary Diagnosis, Prognosis, and Rehabilitation in Patients with Disorders of Consciousness.Seminars in neurology · 2022Review
- EEG hybrid brain-computer interfaces: A scoping review applying an existing hybrid-BCI taxonomy and considerations for pediatric applications.Frontiers in human neuroscience · 2022Article
- Improved classification performance of EEG-fNIRS multimodal brain-computer interface based on multi-domain features and multi-level progressive learning.Frontiers in human neuroscience · 2022Article
- A Human-Machine Interface Based on an EOG and a Gyroscope for Humanoid Robot Control and Its Application to Home Services.Journal of healthcare engineering · 2022Article
- Mind the gap: State-of-the-art technologies and applications for EEG-based brain-computer interfaces.APL bioengineering · 2021Review
- Hybrid Deep Learning (hDL)-Based Brain-Computer Interface (BCI) Systems: A Systematic Review.Brain sciences · 2021Review
- Hybrid Systems to Boost EEG-Based Real-Time Action Decoding in Car Driving Scenarios.Frontiers in neuroergonomics · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Conventional brain-computer interface (BCI) systems have been facing two fundamental challenges: the lack of high detection performance and the control command problem. To this end, the researchers have proposed a hybrid brain-computer interface (hBCI) to address these challenges. This paper mainly discusses the research progress of hBCI and reviews three types of hBCI, namely, hBCI based on multiple brain models, multisensory hBCI, and hBCI based on multimodal signals. By analyzing the general principles, paradigm designs, experimental results, advantages, and applications of the latest hBCI system, we found that using hBCI technology can improve the detection performance of BCI and achieve multidegree/multifunctional control, which is significantly superior to single-mode BCIs.
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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.