Publication
Brain-Computer Interfaces
Related publications (45)
Engineering Hydrogel-coated Neural Interfaces for Chronic Deep Brain Recording
Implanted brain electrodes provide a unique way of electrically interfacing with individual neurons in vivo. However, chronic recording or stimulating capabilities of neural implants are often impaired by a strong immune response resulting in a fibrous sca ...
EPFL2023Motor state transitions and Breathing in Brain Machine Interfaces
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 ...
EPFL2021The Human-Computer Connection An Overview Of Brain-Computer Interfaces
This article introduces the field of brain-computer interfaces (BCI), which allows the control of devices without the generation of any active motor output but directly from the decoding of the user's brain signals. Here we review the current state of the ...
UNIV VALENCIA, BOTANICAL GARDEN UV2019Non-invasive, Brain-controlled Functional Electrical Stimulation for Locomotion Rehabilitation in Individuals with Paraplegia
Mohamed Bouri, Solaiman Shokur, Miguel Nicolelis
Spinal cord injury (SCI) impairs the flow of sensory and motor signals between the brain and the areas of the body located below the lesion level. Here, we describe a neurorehabilitation setup combining several approaches that were shown to have a positive ...
2019Harnessing 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 ...
Elsevier2017EEG topographies provide subject-specific correlates of motor control
Dimitri Nestor Alice Van De Ville, José del Rocio Millán Ruiz, Silvestro Micera, Elvira Pirondini, Martina Coscia, Jesús Minguillón Campos
Electroencephalography (EEG) of brain activity can be represented in terms of dynamically changing topographies (microstates). Notably, spontaneous brain activity recorded at rest can be characterized by four distinctive topographies. Despite their well-es ...
Nature Publishing Group2017A 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 ...
Elsevier2017Motor and cognitive brain circuits of brain-machine interactions
Brain-machine interfaces (BMIs) allow the user to control an external device such as a robotic arm, a cursor, or an avatar in a virtual world through the real-time decoding of brain signals and without the involvement of the musculoskeletal system. Althoug ...
EPFL2016