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Behavioral and cortical effects during attention driven brain-computer interface operations in spatial neglect: A feasibility case study

Publications associées (45)

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The rise of neurotechnologies, especially in combination with artificial intelligence (AI)-based methods for brain data analytics, has given rise to concerns around the protection of mental privacy, mental integrity and cognitive liberty - often framed as ...

CAMBRIDGE UNIV PRESS2023

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Intracortical brain-machine interfaces decode motor commands from neural signals and translate them into actions, enabling movement for paralysed individuals. The subjective sense of agency associated with actions generated via intracortical brain-machine ...

NATURE PORTFOLIO2022

Transcranial magnetic stimulation of the brain: What is stimulated? - A consensus and critical position paper

Traian Popa

Transcranial (electro)magnetic stimulation (TMS) is currently the method of choice to non-invasively induce neural activity in the human brain. A single transcranial stimulus induces a time-varying electric field in the brain that may evoke action potentia ...

ELSEVIER IRELAND LTD2022

Brain-Machine interfaces aim to create a direct neural link between user's brain and machines. This goal has pushed scientists to investigate a large spectrum of applications in the realm of assistive and rehabilitation technologies. However, despite great ...

EPFL2021

Towards everyday brain-computer interfacing through decoding visual cognition

Ruslan Aydarkhanov

Decoding visual cognition from non-invasive measurements of brain activity has shown valuable applications. Vision-based Brain-Computer Interfaces (BCI) systems extend from spellers to database search and spatial navigation. Despite the high performance of ...

EPFL2020

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Brain-computer interfaces (BCI) are used in stroke rehabilitation to translate brain signals into intended movements of the paralyzed limb. However, the efficacy and mechanisms of BCI-based therapies remain unclear. Here we show that BCI coupled to functio ...

2018

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

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

A Brain-Controlled Exoskeleton with Cascaded Event-Related Desynchronization Classifiers

José del Rocio Millán Ruiz, Kyuhwa Lee, Ricardo Andres Chavarriaga Lozano, Dong Liu

This paper describes a brain-machine interface for the online control of a powered lower-limb exoskeleton based on electroencephalogram (EEG) signals recorded over the user’s sensorimotor cortical areas. We train a binary decoder that can distinguish two d ...

Elsevier2017

Over the last decade, technological advances in the field of functional magnetic resonance imaging (fMRI) have made it possible to obtain localized measures of brain activity in real-time. This allows for applications such as online quality control of the ...

EPFL2017