ArticleFrontiers in neuroinformatics2011
Tools for Brain-Computer Interaction: A General Concept for a Hybrid BCI.
Article in Frontiers in neuroinformatics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed.
- Novel hold-release functionality in a P300 brain-computer interface.Journal of neural engineering · 2014Trial
- Towards unlocking motor control in spinal cord injured by applying an online EEG-based framework to decode motor intention, trajectory and error processing.Scientific reports · 2024Article
- Considerations and discussions on the clear definition and definite scope of brain-computer interfaces.Frontiers in neuroscience · 2024Review
- A hybrid brain-muscle-machine interface for stroke rehabilitation: Usability and functionality validation in a 2-week intensive intervention.Frontiers in bioengineering and biotechnology · 2024Article
- Design-development of an at-home modular brain-computer interface (BCI) platform in a case study of cervical spinal cord injury.Journal of neuroengineering and rehabilitation · 2022Article
- Feel Your Reach: An EEG-Based Framework to Continuously Detect Goal-Directed Movements and Error Processing to Gate Kinesthetic Feedback Informed Artificial Arm Control.Frontiers in human neuroscience · 2022Review
- ROS-Neuro: An Open-Source Platform for Neurorobotics.Frontiers in neurorobotics · 2022Article
- BioPyC, an Open-Source Python Toolbox for Offline Electroencephalographic and Physiological Signals Classification.Sensors (Basel, Switzerland) · 2021Article
- Affective Neurofeedback Under Naturalistic Conditions: A Mini-Review of Current Achievements and Open Challenges.Frontiers in neuroergonomics · 2021Review
- SimBSI: An open-source Simulink library for developing closed-loop brain signal interfaces in animals and humans.Biomedical physics & engineering express · 2020Article
- "You Have Reached Your Destination": A Single Trial EEG Classification Study.Frontiers in neuroscience · 2020Article
- Passive Brain-Computer Interfaces for Enhanced Human-Robot Interaction.Frontiers in robotics and AI · 2020Review
- Hybrid Human-Machine Interface for Gait Decoding Through Bayesian Fusion of EEG and EMG Classifiers.Frontiers in neurorobotics · 2020Article
- Physiological Responses During Hybrid BNCI Control of an Upper-Limb Exoskeleton.Sensors (Basel, Switzerland) · 2019Article
- Article
- Decoding finger movement in humans using synergy of EEG cortical current signals.Scientific reports · 2017Article
- Plug&Play Brain-Computer Interfaces for effective Active and Assisted Living control.Medical & biological engineering & computing · 2017Article
- Workshops of the Sixth International Brain-Computer Interface Meeting: brain-computer interfaces past, present, and future.Brain computer interfaces (Abingdon, England) · 2017Article
- Classification of Movement and Inhibition Using a Hybrid BCI.Frontiers in neurorobotics · 2017Article
- Development of Single-Channel Hybrid BCI System Using Motor Imagery and SSVEP.Journal of healthcare engineering · 2017Article
Corrections and comments
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Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aim of this work is to present the development of a hybrid Brain-Computer Interface (hBCI) which combines existing input devices with a BCI. Thereby, the BCI should be available if the user wishes to extend the types of inputs available to an assistive technology system, but the user can also choose not to use the BCI at all; the BCI is active in the background. The hBCI might decide on the one hand which input channel(s) offer the most reliable signal(s) and switch between input channels to improve information transfer rate, usability, or other factors, or on the other hand fuse various input channels. One major goal therefore is to bring the BCI technology to a level where it can be used in a maximum number of scenarios in a simple way. To achieve this, it is of great importance that the hBCI is able to operate reliably for long periods, recognizing and adapting to changes as it does so. This goal is only possible if many different subsystems in the hBCI can work together. Since one research institute alone cannot provide such different functionality, collaboration between institutes is necessary. To allow for such a collaboration, a new concept and common software framework is introduced. It consists of four interfaces connecting the classical BCI modules: signal acquisition, preprocessing, feature extraction, classification, and the application. But it provides also the concept of fusion and shared control. In a proof of concept, the functionality of the proposed system was demonstrated.
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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.