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Analysing Vibrotactually Stimulated EEG Signals to Comprehend Object Shapes

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Comparing BCI performance using scalp EEG-and inverse solution-based features

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Mohit Kumar Goel

Several studies have proposed the use of inverse solutions based features to improve the decoding performance of brain-computer interfaces. Most of these studies have compared the performance of inverse solutions features over scalp activity in a small set ...

2014

Workshops of the Fifth International Brain-Computer Interface Meeting: Defining the Future

Ricardo Andres Chavarriaga Lozano, Robert Leeb

The Fifth International Brain-Computer Interface (BCI) Meeting met on 3rd June 2013 at the Asilomar Conference Grounds, Pacific Grove, California, USA. The conference included 19 workshops covering topics in brain-computer interface and brain-machine inter ...

2014

Towards Implementation of Motor Imagery using Brain Connectivity Features

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Huaijian Zhang

This study aims to explore modulation of the connectivity pattern when people perform left hand versus right hand motor imagery and probe the feasibility of adopting connectivity information to discriminate these tasks. Nine subjects were recorded with 16- ...

2014

Exploiting Recognition of Natural Visual Stimuli for Brain Computer Interfacing

Marija Uscumlic

Visual search is a good illustration about how the brain coordinates a variety of functions such as visual clues extraction from the scene, coordination of the eye-movements, accumu- lation of visual information and visual recognition. It has an important ...

EPFL2013

Inverse Solutions for Brain Computer Interface

José del Rocio Millán Ruiz, Mohit Kumar Goel

Inverse solution allows to estimate sources that generate a given scalp EEG topography. Recently, it has been used in Brain Computer Interfaces (BCIs) to extract robust features based on the hypothesis that projection onto the source space (high dimensiona ...

EPFL2013

Covert visuospatial attention Brain-Computer Interface for control and rehabilitation

Luca Tonin

At the current stage, Brain-Computer Interfaces (BCIs) represent a promising technology for communication and control of assistive devices as well as for the clinical motor rehabilitation after a stroke. Current BCI systems may be divided in two main typol ...

EPFL2013

Shared electrophysiology mechanisms of body ownership and motor imagery

Olaf Blanke, Nathaniel Evans

Although we feel, see, and experience our hands as our own (body or hand ownership), recent research has shown that illusory hand ownership can be induced for fake or virtual hands and may useful for neuroprosthetics and brain-computer interfaces. Despite ...

Academic Press Inc Elsevier Science2013

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The idea to use EEG correlates of errors to correct or reinforce BCI operation has been proposed over a decade ago. Since then a body of evidence has corroborated this approach. In this paper we give an overview of our recent work exploring the possibiliti ...

Graz University of Technology Publishing House2013

Controlling a device via a brain-computer interface (BCI) requires the participant to look and to split the attention between the device and the BCI feedback, which is partly contradictory. Therefore, a stimulation system based on 6 coin-motors is develope ...

Graz University of Technology Publishing House2013

Brain-Computer Interface in Multimedia Systems

Ashkan Yazdani

A brain-computer interface (BCI) is a system that allows a user to communicate with the environment only through cerebral activity, without using muscular output channels. To establish a direct link between the brain and a computer, the electroencephalogra ...

EPFL2012