AIMC Topic: Brain-Computer Interfaces

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Multi-Channel Convolutional Neural Networks Architecture Feeding for Effective EEG Mental Tasks Classification.

Sensors (Basel, Switzerland)
Mental tasks classification is increasingly recognized as a major challenge in the field of EEG signal processing and analysis. State-of-the-art approaches face the issue of spatially unstable structure of highly noised EEG signals. To address this p...

Improving Performance of Devanagari Script Input-Based P300 Speller Using Deep Learning.

IEEE transactions on bio-medical engineering
The performance of an existing Devanagari script (DS) input-based P300 speller with conventional machine learning techniques suffers from low information transfer rate (ITR). This occurs due to its required large size of display, i.e., 8 × 8 row-colu...

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...

Exploring spatial-frequency-sequential relationships for motor imagery classification with recurrent neural network.

BMC bioinformatics
BACKGROUND: Conventional methods of motor imagery brain computer interfaces (MI-BCIs) suffer from the limited number of samples and simplified features, so as to produce poor performances with spatial-frequency features and shallow classifiers.

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 ...

Robust Closed-Loop Control of a Cursor in a Person with Tetraplegia using Gaussian Process Regression.

Neural computation
Intracortical brain computer interfaces can enable individuals with paralysis to control external devices through voluntarily modulated brain activity. Decoding quality has been previously shown to degrade with signal nonstationarities-specifically, ...

Human-agent co-adaptation using error-related potentials.

Journal of neural engineering
OBJECTIVE: Error-related potentials (ErrP) have been proposed as an intuitive feedback signal decoded from the ongoing electroencephalogram (EEG) of a human observer for improving human-robot interaction (HRI). While recent demonstrations of this app...

A Novel Method of Segmentation and Classification for Meditation in Health Care Systems.

Journal of medical systems
Meditation improves positivity in behavioral as well as psychological changes, which are brought elucidated by knowing neuro-physiological consequences of meditation. In the field of cognitive science, neuroscience and physiological research, Electro...

Classification of Overt and Covert Speech for Near-Infrared Spectroscopy-Based Brain Computer Interface.

Sensors (Basel, Switzerland)
People suffering from neuromuscular disorders such as locked-in syndrome (LIS) are left in a paralyzed state with preserved awareness and cognition. In this study, it was hypothesized that changes in local hemodynamic activity, due to the activation ...

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...