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Analysing Vibrotactually Stimulated EEG Signals to Comprehend Object Shapes

Publications associées (61)

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Processing of electroencephalographic (EEG) signals has mostly focused on analysing correlates that are time-locked to an observable event. However, when the signal is acquired in less controlled environment, like in the context of a brain-computer interfa ...

EPFL2012

Decoding Self-paced Upper Limb Reaching Movements from Brain Signals

José del Rocio Millán Ruiz, Eileen Lew Yi Lee

Future emerging technologies in upper limb neuroprosthetic devices will require decoding and executing the user's intended movement. Previous studies, using invasive and non-invasive brain signals, have shown promising results in decoding movement directio ...

EPFL2012

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In this paper we use the cortical current density based inverse solution to classify Event Related Potential, in particular for error-related potential elicited during Brain-Computer Interface experiment. We selected discriminant cortical sources for compa ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2011

Neurofeedback therapies are an emerging technique used to treat neuropsychological disorders and to enhance cognitive performance. The feedback stimuli presented during the therapy are a key factor, serving as guidance throughout the entire learning proces ...

2011

Evidence Accumulation in asynchronous BCI

José del Rocio Millán Ruiz, Robert Leeb, Serafeim Perdikis, Hamidreza Bayati

The non-invasive Brain-Computer Interface (BCI) developed in our lab targets asynchronous operation of devices by monitoring electroencephalographic (EEG) activity and identifying oscillatory patterns that the user can voluntary modulate through the execut ...

2011

The Impact of Expertise on Brain Computer Interface Based Salient Image Retrieval

Touradj Ebrahimi, Jean-Marc Vesin, Ashkan Yazdani

Autonomous decision making modules in computer vision application allow recognition and classification of different objects, persons, and events in images and video sequences and also make it possible to classify different sensor readings (e.g. images) acc ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2010

Discriminative Channel Selection Method for the Recognition of Anticipation related Potentials from CCD estimated Cortical Activity

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Gangadhar Garipelli

Recognition of brain states and subject's intention from electroencephalogram (EEG) is a challenging problem for brain-computer interaction. Signals recorded from each of EEG electrodes represent noisy spatio-temporal overlapping of activity arising from v ...

2009

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A brain computer interface (BCI) is a communication system, which translates brain activity into commands for a computer or other devices. Nearly all BCIs contain as a core component a classification algorithm, which is employed to discriminate different b ...

IEEE2009

This paper describes a new non-invasive brain-actuated wheelchair that relies on a P300 neurophysiological protocol and automated navigation. In operation, the subject faces a screen with a real-time virtual reconstruction of the scenario, and concentrates ...

2009

An efficient P300-based brain-computer interface for disabled subjects

Touradj Ebrahimi, Jean-Marc Vesin, Ulrich Hoffmann

A brain-computer interface (BCI) is a communication system that translates brain-activity into commands for a computer or other devices. In other words, a BCI allows users to act on their environment by using only brain-activity, without using peripheral n ...

2008