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Concept

BrainGate

Related publications (29)

Wireless Power Transfer and Data Communication for Implantable Autonomous Monitoring and Detection of Epilepsy In Vivo

Kerim Türe

The impact of technological advancement became significant and still has an essential role to play in the diagnosis and treatment of diseases. Nowadays, personalized medicine and therapy are on the rise as a consequence of the developed and cheaper medical ...

EPFL2019

Brain-actuated functional electrical stimulation elicits lasting arm motor recovery after stroke

Hua Zhang, José del Rocio Millán Ruiz, Robert Leeb, Inaki Asier Iturrate Gil, Serafeim Perdikis, Andrea Biasiucci, Tiffany Corbet, Thomas Schmidlin, Dragana Viceic

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 ...

Nature Research2018

Analysing Vibrotactually Stimulated EEG Signals to Comprehend Object Shapes

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

Restoring Motor Functions After Stroke: Multiple Approaches and Opportunities

Friedhelm Christoph Hummel, Estelle Emeline Raffin

More than 1.5 million people suffer a stroke in Europe per year and more than 70% of stroke survivors experience limited functional recovery of their upper limb, resulting in diminished quality of life. Therefore, interventions to address upper-limb impair ...

2018

Brain-computer interfaces for post-stroke motor rehabilitation: a meta-analysis

José del Rocio Millán Ruiz, Gangadhar Garipelli

Brain‐computer interfaces (BCIs) can provide sensory feedback of ongoing brain oscillations, enabling stroke survivors to modulate their sensorimotor rhythms purposefully. A number of recent clinical studies indicate that repeated use of such BCIs might tr ...

2018

System for active skull replacement for brain interface and method of using the same

Catherine Dehollain, Kanber Mithat Silay, Gürkan Yilmaz

An active skull replacement system including an implant having an area A, an upper surface, and a bottom surface, adapted to be implanted at least in part into a skull of a subject so to substitute a portion of the skull, the bottom surface arranged to fac ...

2017

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, Ricardo Andres Chavarriaga Lozano, Dong Liu, Kyuhwa Lee, 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

Harnessing prefrontal cognitive signals for brain-machine interfaces

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano

Brain-machine interfaces (BMIs) enable humans to interact with devices by modulating their brain signals. Despite impressive technological advancements, several obstacles remain. The most commonly used BMI control signals are derived from the brain areas i ...

Elsevier2017