AIMC Topic: Evoked Potentials, Visual

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BioWolf: A Sub-10-mW 8-Channel Advanced Brain-Computer Interface Platform With a Nine-Core Processor and BLE Connectivity.

IEEE transactions on biomedical circuits and systems
Advancements in digital signal processing (DSP) and machine learning techniques have boosted the popularity of brain-computer interfaces (BCIs), where electroencephalography is a widely accepted method to enable intuitive human-machine interaction. N...

Characterization of the non-stationary nature of steady-state visual evoked potentials using echo state networks.

PloS one
State Visual Evoked Potentials (SSVEPs) arise from a resonance phenomenon in the visual cortex that is produced by a repetitive visual stimulus. SSVEPs have long been considered a steady-state response resulting from purely oscillatory components pha...

Acuity VEP: improved with machine learning.

Documenta ophthalmologica. Advances in ophthalmology
PURPOSE: Acuity-VEP approaches basically all use the information obtained across a number of check sizes (or spatial frequencies) to derive a measure of acuity. Amplitude is always used, sometimes combined with phase or a noise measure. In our approa...

A Convolutional Neural Network for the Detection of Asynchronous Steady State Motion Visual Evoked Potential.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
A key issue in brain-computer interface (BCI) is the detection of intentional control (IC) states and non-intentional control (NC) states in an asynchronous manner. Furthermore, for steady-state visual evoked potential (SSVEP) BCI systems, multiple s...

Discrimination of Motion Direction in a Robot Using a Phenomenological Model of Synaptic Plasticity.

Computational intelligence and neuroscience
Recognizing and tracking the direction of moving stimuli is crucial to the control of much animal behaviour. In this study, we examine whether a bio-inspired model of synaptic plasticity implemented in a robotic agent may allow the discrimination of ...

Cyborg groups enhance face recognition in crowded environments.

PloS one
Recognizing a person in a crowded environment is a challenging, yet critical, visual-search task for both humans and machine-vision algorithms. This paper explores the possibility of combining a residual neural network (ResNet), brain-computer interf...

Combination of high-frequency SSVEP-based BCI and computer vision for controlling a robotic arm.

Journal of neural engineering
OBJECTIVE: Recent attempts in developing brain-computer interface (BCI)-controlled robots have shown the potential of this area in the field of assistive robots. However, implementing the process of picking and placing objects using a BCI-controlled ...

Compact convolutional neural networks for classification of asynchronous steady-state visual evoked potentials.

Journal of neural engineering
OBJECTIVE: Steady-state visual evoked potentials (SSVEPs) are neural oscillations from the parietal and occipital regions of the brain that are evoked from flickering visual stimuli. SSVEPs are robust signals measurable in the electroencephalogram (E...

A novel system of SSVEP-based human-robot coordination.

Journal of neural engineering
OBJECTIVE: Human-robot coordination (HRC) aims to enable human and robot to form a tightly coupled system to accomplish a task. One of its important application prospects is to improve the physical function of the disabled. However, the low level of ...

A Wearable Multi-Modal Bio-Sensing System Towards Real-World Applications.

IEEE transactions on bio-medical engineering
Multi-modal bio-sensing has recently been used as effective research tools in affective computing, autism, clinical disorders, and virtual reality among other areas. However, none of the existing bio-sensing systems support multi-modality in a wearab...