Evaluation of a congruent auditory feedback for Motor Imagery BCI

05/18/2018

∙

Designing a feedback that helps participants to achieve higher performances is an important concern in brain-computer interface (BCI) research. In a pilot study, we demonstrate how a congruent auditory feedback could improve classification in a electroencephalography (EEG) motor imagery BCI. This is a promising result for creating alternate feedback modality.

READ FULL TEXT

Evaluation of a congruent auditory feedback for Motor Imagery BCI

Classification of Tactile Perception and Attention on Natural Textures from EEG Signals

BCI-Based Strategies on Stroke Rehabilitation with Avatar and FES Feedback

The evolution of AI approaches for motor imagery EEG-based BCIs

Towards identifying optimal biased feedback for various user states and traits in motor imagery BCI

Would Motor-Imagery based BCI user training benefit from more women experimenters?

Performance of OpenBCI EEG Binary Intent Classification with Laryngeal Imagery

Exploring Biofeedback with a Tangible Interface Designed for Relaxation

Evaluation of a congruent auditory feedback for Motor Imagery BCI

Related Research

Classification of Tactile Perception and Attention on Natural Textures from EEG Signals

BCI-Based Strategies on Stroke Rehabilitation with Avatar and FES Feedback

The evolution of AI approaches for motor imagery EEG-based BCIs

Towards identifying optimal biased feedback for various user states and traits in motor imagery BCI

Would Motor-Imagery based BCI user training benefit from more women experimenters?

Performance of OpenBCI EEG Binary Intent Classification with Laryngeal Imagery

Exploring Biofeedback with a Tangible Interface Designed for Relaxation