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Inferring subjective preferences on robot trajectories using EEG signals

Publications associées (64)

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Classification of upper limb center-out reaching tasks by means of EEG-based continuous decoding techniques

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano

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

Visual backward masking in siblings of schizophrenia patients: evidence for a compensation mechanism

Michael Herzog, Maya Roinishvili, Patricia Figueiredo

Visual backward masking (VBM) is a very sensitive endophenotype of schizophrenia. Masking deficits are highly correlated with reduced EEG amplitudes. In VBM, a target stimulus is followed by a mask, which decreases performance on the target. Here, we inves ...

2017

Neural correlates of visual backward masking in psychosis

Michael Herzog, Christine Mohr, Maya Roinishvili, Ophélie Gladys Favrod

In visual backward masking (VBM), a target is followed by a mask, which deteriorates performance on the target. Schizophrenia and first episodes patients show strong behavioral deficits, reflected in strongly reduced amplitudes of the EEG as compared to co ...

2017

Scalp electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) have highly complementary domains, and their combination has been actively sought within neuroscience research. The important gains in fMRI sensitivity achieved with higher ...

EPFL2016

BCI based on Neural Correlates of Anticipatory Behavior during Driving

Zahra Khaliliardali

Anticipation of events such as, changes in traffic light signals and preparing to brake or accelerate are critical behaviors during driving. Smart vehicles, equipped with on-board Brain-Computer Interface (BCI), could decode the driver's intention to perfo ...

EPFL2016

Quantifying the role of motor imagery in brain-machine interfaces

Olaf Blanke, Hannes Bleuler, Andrea Serino, Michela Bassolino, Silvia Marchesotti

Despite technical advances in brain machine interfaces (BMI), for as-yet unknown reasons the ability to control a BMI remains limited to a subset of users. We investigate whether individual differences in BMI control based on motor imagery (MI) are related ...

2016

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

Connectivity Analysis of Brain States and Applications in Brain-Computer Interfaces

Huaijian Zhang

Human brain is organized by a large number of functionally correlated but spatially distributed cortical neurons. Cognitive processes are usually associated with dynamic interactions among multiple brain regions. Therefore, the understanding of brain funct ...

EPFL2015

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Psychophysical studies have reported correlation between neural activity in frontal and parietal areas and subject's reaction time in simple tasks. Here we study whether similar correlates can also be identified in driver's electroencephalography (EEG) act ...

2015

Quantifying electrode reliability during Brain-Computer Interface operation

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Serafeim Perdikis, Hesam Sagha

One of the problems of non-invasive Brain-Computer Interface (BCI) applications is the occurrence of anomalous (unexpected) signals that might degrade BCI performance. This situation might slip the operator’s attention since raw signals are not usually con ...

Institute of Electrical and Electronics Engineers2015