ArticleFrontiers in neurorobotics2020
A Hybrid BCI Based on SSVEP and EOG for Robotic Arm Control.
Article in Frontiers in neurorobotics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed, 63 citations in OpenAlex.
- Rethinking Brain-Computer Interfaces for Soft Robotic Systems: A Unified Framework and Perspective.Sensors (Basel, Switzerland) · 2026Article
- SSVEP-based brain-computer interface enabling graded dyspnoea self-report: proof-of-concept study in healthy volunteers.Journal of neuroengineering and rehabilitation · 2026Article
- Intersession Robust Hybrid Brain-Computer Interface: Safe and User-Friendly Approach with LED Activation Mechanism.Micromachines · 2025Article
- High-Resolution EEG Source Reconstruction from PCA-Corrected BEM-FMM Reciprocal Basis Funcions: A Study with Visual Evoked Potentials from Intermittent Photic Stimulation.bioRxiv : the preprint server for biology · 2025Article
- Performance investigation of MVMD-MSI algorithm in frequency recognition for SSVEP-based brain-computer interface and its application in robotic arm control.Medical & biological engineering & computing · 2025Article
- A Safe and Efficient Brain-Computer Interface Using Moving Object Trajectories and LED-Controlled Activation.Micromachines · 2025Article
- A Complementary Dual-Mode Ion-Electron Conductive Hydrogel Enables Sustained Conductivity for Prolonged Electroencephalogram Recording.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Multiclass Classification of Visual Electroencephalogram Based on Channel Selection, Minimum Norm Estimation Algorithm, and Deep Network Architectures.Sensors (Basel, Switzerland) · 2024Article
- A comparison of visual and auditory EEG interfaces for robot multi-stage task control.Frontiers in robotics and AI · 2024Article
- Electroencephalogram-based adaptive closed-loop brain-computer interface in neurorehabilitation: a review.Frontiers in computational neuroscience · 2024Review
- A flexible speller based on time-space frequency conversion SSVEP stimulation paradigm under dry electrode.Frontiers in computational neuroscience · 2023Article
- An online hybrid BCI combining SSVEP and EOG-based eye movements.Frontiers in human neuroscience · 2023Article
- 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
- EEG-controlled tele-grasping for undefined objects.Frontiers in neurorobotics · 2023Article
- Investigating User Proficiency of Motor Imagery for EEG-Based BCI System to Control Simulated Wheelchair.Sensors (Basel, Switzerland) · 2022Article
- Cross-Platform Implementation of an SSVEP-Based BCI for the Control of a 6-DOF Robotic Arm.Sensors (Basel, Switzerland) · 2022Article
- Steady-State Visual Evoked Potential-Based Brain-Computer Interface Using a Novel Visual Stimulus with Quick Response (QR) Code Pattern.Sensors (Basel, Switzerland) · 2022Article
- Multimodal Human-Exoskeleton Interface for Lower Limb Movement Prediction Through a Dense Co-Attention Symmetric Mechanism.Frontiers in neuroscience · 2022Article
- Control of a Robotic Arm With an Optimized Common Template-Based CCA Method for SSVEP-Based BCI.Frontiers in neurorobotics · 2022Article
- An asynchronous artifact-enhanced electroencephalogram based control paradigm assisted by slight facial expression.Frontiers in neuroscience · 2022Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Brain-computer interface (BCI) for robotic arm control has been studied to improve the life quality of people with severe motor disabilities. There are still challenges for robotic arm control in accomplishing a complex task with a series of actions. An efficient switch and a timely cancel command are helpful in the application of robotic arm. Based on the above, we proposed an asynchronous hybrid BCI in this study. The basic control of a robotic arm with six degrees of freedom was a steady-state visual evoked potential (SSVEP) based BCI with fifteen target classes. We designed an EOG-based switch which used a triple blink to either activate or deactivate the flash of SSVEP-based BCI. Stopping flash in the idle state can help to reduce visual fatigue and false activation rate (FAR). Additionally, users were allowed to cancel the current command simply by a wink in the feedback phase to avoid executing the incorrect command. Fifteen subjects participated and completed the experiments. The cue-based experiment obtained an average accuracy of 92.09%, and the information transfer rates (ITR) resulted in 35.98 bits/min. The mean FAR of the switch was 0.01/min. Furthermore, all subjects succeeded in asynchronously operating the robotic arm to grasp, lift, and move a target object from the initial position to a specific location. The results indicated the feasibility of the combination of EOG and SSVEP signals and the flexibility of EOG signal in BCI to complete a complicated task of robotic arm control.
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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.