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Error Potentials for Brain-Computer Interfaces

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A Multifaceted Approach to Covert Attention Brain-Computer Interfaces

Christoph Schneider

Over the last years, brain-computer interfaces (BCIs) have shown their value for assistive technology and neurorehabilitation. Recently, a BCI-approach for the rehabilitation of hemispatial neglect has been proposed on the basis of covert visuospatial atte ...

EPFL2018

Analysing Vibrotactually Stimulated EEG Signals to Comprehend Object Shapes

Anwesha Khasnobish

Tactile feedback has the capability of reducing the workload on the visual channel, during visual feedback in brain-computer interfaces (BCIs). It is requisite to analyse the brain signals corresponding to the tactile stimulations. This work is aimed at an ...

IEEE2018

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Real-time workload estimation can be an important tool to improve human-machine interaction. Despite multiple efforts in this sense, most studies focused on tasks designed to have extreme conditions of workload (high vs low), and these levels remain rather ...

2018

Analysis of EEG Correlates of Perceived Difficulty in Dynamically Changing Flying Tasks

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Ping-Keng Jao

IEEE2018

Background: One of the current challenges in brain-machine interfacing is to characterize and decode upper limb kinematics from brain signals, e.g. to control a prosthetic device. Recent research work states that it is possible to do so based on low freque ...

BioMed Central2017

An EEG-based brain-computer interface for gait training

José del Rocio Millán Ruiz, Kyuhwa Lee, Dong Liu

This work presents an electroencephalography (EEG)-based Brain-computer Interface (BCI) that decodes cerebral activities to control a lower-limb gait training exoskeleton. Motor imagery (MI) of flexion and extension of both legs was distinguished from the ...

2017

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Steady State Visually Evoked Potentials (SSVEP) are signals produced in the occipital part of the brain when someone gaze a light flickering at a fixed frequency. These signals have been used for Brain Machine Interfacing (BMI), where one or more stimuli a ...

2016

Asynchronous Decoding of Error Potentials During the Monitoring of a Reaching Task

Ricardo Andres Chavarriaga Lozano, Inaki Asier Iturrate Gil

Brain-machine interfaces (BMIs) have demonstrated how they can be used for reaching tasks with both invasive and non-invasive signal recording methods. Despite the constant improvements in this field, there still exist diverse factors to overcome before ac ...

2015

Recent works have explored the use of brain signals to directly control virtual and robotic agents in sequential tasks. So far in such brain-computer interfaces (BCI), an explicit calibration phase was required to build a decoder that translates raw electr ...

2014

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