AIMC Topic: Evoked Potentials, Visual

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Data augmentation using masked principal component representation for deep learning-based SSVEP-BCIs.

Journal of neural engineering May 28, 2025
Data augmentation has been demonstrated to improve the classification accuracy of deep learning models in steady-state visual evoked potential-based brain-computer interfaces (BCIs), particularly when dealing with limited electroencephalography (EEG)...
Adult Male Deep Learning Humans Principal Component Analysis Brain-Computer Interfaces Electroencephalography Evoked Potentials, Visual Photic Stimulation
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[The supernumerary robotic limbs of brain-computer interface based on asynchronous steady-state visual evoked potential].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Aug 25, 2024
Brain-computer interface (BCI) based on steady-state visual evoked potential (SSVEP) have attracted much attention in the field of intelligent robotics. Traditional SSVEP-based BCI systems mostly use synchronized triggers without identifying whether ...
Evoked Potentials, Visual Algorithms Robotics Electroencephalography Brain-Computer Interfaces Discriminant Analysis Humans
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Advancing SSVEP-BCI Decoding: Cross-Subject Transfer Learning and Short Calibrated Approach with ELM-AE.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
The Steady-State Visually Evoked Potential (SSVEP) is a robust paradigm for developing a high-speed Brain-Computer Interface (BCI). However, one of the challenges of BCI is to face the variability of EEG signals between subjects to reduce or eliminat...
Evoked Potentials, Visual Calibration Brain-Computer Interfaces Algorithms Adult Electroencephalography Signal Processing, Computer-Assisted Male Humans Machine Learning
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A Method of Cross-Subject Transfer Learning for Ultra Short Time SSVEP Classification.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
The steady-state visual evoked potentials (SSVEP) based brain-computer interfaces (BCIs) require extensive training data for efficient classification, but existing algorithms struggle with ultra short time inputs (less than 0.2 seconds), limiting the...
Humans Algorithms Time Factors Electroencephalography Neural Networks, Computer Machine Learning Evoked Potentials, Visual Signal Processing, Computer-Assisted Brain-Computer Interfaces
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Primary color decoding using deep learning on source reconstructed EEG signal responses.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2023
The brain's response to visual stimuli of different colors might be used in a brain-computer interface (BCI) paradigm, for letting a user control their surroundings by looking at specific colors. Allowing the user to control certain elements in its e...
Brain-Computer Interfaces Evoked Potentials, Visual Humans Deep Learning Electroencephalography Neural Networks, Computer
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Comparing the Usability of Alternative EEG Devices to Traditional Electrode Caps for SSVEP-BCI Controlled Assistive Robots.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings] Jul 1, 2022
Despite having the potential to improve the lives of severely paralyzed users, non-invasive Brain Computer Interfaces (BCI) have yet to be integrated into their daily lives. The widespread adoption of BCI-driven assistive technology is hindered by it...
Humans Evoked Potentials Robotics Electrodes Electroencephalography Brain-Computer Interfaces Evoked Potentials, Visual
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Implementation of an SSVEP-based intelligent home service robot system.

Technology and health care : official journal of the European Society for Engineering and Medicine Jan 1, 2021
BACKGROUND: People with severe neuromuscular disorders caused by an accident or congenital disease cannot normally interact with the physical environment. The intelligent robot technology offers the possibility to solve this problem. However, the rob...
Robotics Electroencephalography Evoked Potentials, Visual Humans Brain-Computer Interfaces
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A Convolutional Neural Network for Enhancing the Detection of SSVEP in the Presence of Competing Stimuli.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Stimulus proximity has been shown to have an influence on the classification performance of a steady-state visual evoked potential based brain-computer interface (SSVEP-BCI). Multiple visual stimuli placed close to each other compete for neural repre...
Evoked Potentials, Visual Neural Networks, Computer Humans Photic Stimulation Algorithms Electroencephalography Brain-Computer Interfaces
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Characterization of SSMVEP-based EEG signals using multiplex limited penetrable horizontal visibility graph.

Chaos (Woodbury, N.Y.) Jul 1, 2019
The steady state motion visual evoked potential (SSMVEP)-based brain computer interface (BCI), which incorporates the motion perception capabilities of the human visual system to alleviate the negative effects caused by strong visual stimulation from...
Photic Stimulation Brain-Computer Interfaces Evoked Potentials, Visual Support Vector Machine Models, Neurological Electroencephalography Humans Brain
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Designing a brain computer interface for control of an assistive robotic manipulator using steady state visually evoked potentials.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings] Jun 1, 2019
An assistive robotic manipulator (ARM) can provide independence and improve the quality of life for patients suffering from tetraplegia. However, to properly control such device to a satisfactory level without any motor functions requires a very high...
Brain-Computer Interfaces Evoked Potentials, Visual Robotics Humans Electroencephalography Quality of Life
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