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Brain–machine interface based on deep learning to control asynchronously a lower-limb robotic exoskeleton: a case-of-study [PDF]

Journal of NeuroEngineering and Rehabilitation
Background This research focused on the development of a motor imagery (MI) based brain–machine interface (BMI) using deep learning algorithms to control a lower-limb robotic exoskeleton.
Laura Ferrero, Paula Soriano-Segura, Jacobo Navarro, Oscar Jones, Mario Ortiz, Eduardo Iáñez, José M. Azorín, José L. Contreras-Vidal   +7 more
doaj   +4 more sources

Brain-machine interface based on transfer-learning for detecting the appearance of obstacles during exoskeleton-assisted walking [PDF]

Frontiers in Neuroscience, 2023
IntroductionBrain-machine interfaces (BMIs) attempt to establish communication between the user and the device to be controlled. BMIs have great challenges to face in order to design a robust control in the real field of application.
Vicente Quiles, Vicente Quiles, Laura Ferrero, Laura Ferrero, Laura Ferrero, Eduardo Iáñez, Eduardo Iáñez, Mario Ortiz, Mario Ortiz, Mario Ortiz, Ángel Gil-Agudo, José M. Azorín, José M. Azorín, José M. Azorín, José M. Azorín   +14 more
doaj   +2 more sources

Brain–machine interface for eye movements [PDF]

Proceedings of the National Academy of Sciences, 2014
A number of studies in tetraplegic humans and healthy nonhuman primates (NHPs) have shown that neuronal activity from reach-related cortical areas can be used to predict reach intentions using brain–machine interfaces (BMIs) and therefore assist ...
Andersen, Richard A., Graf, Arnulf B. A.
core   +5 more sources

Combining Brain-Computer Interfaces and Assistive Technologies: State-of-the-Art and Challenges [PDF]

Frontiers in Neuroscience, 2010
In recent years, new research has brought the field of EEG-based Brain-Computer Interfacing (BCI) out of its infancy and into a phase of relative maturity through many demonstrated prototypes such as brain-controlled wheelchairs, keyboards, and computer ...
José del R. Millán, Rüdiger Rupp, Gernot Mueller-Putz, Roderick Murray-Smith, Claudio Giugliemma, Michael Tangermann, Carmen Vidaurre, Febo Cincotti, Andrea Kubler, Robert Leeb, Christa Neuper, Klaus R Mueller, Donatella Mattia   +12 more
doaj   +9 more sources

Review of tDCS Configurations for Stimulation of the Lower-Limb Area of Motor Cortex and Cerebellum

Brain Sciences, 2022
This article presents an exhaustive analysis of the works present in the literature pertaining to transcranial direct current stimulation(tDCS) applications.
Vicente Quiles, Laura Ferrero, Eduardo Iáñez, Mario Ortiz, José M. Azorín   +4 more
doaj   +1 more source

A BMI Based on Motor Imagery and Attention for Commanding a Lower-Limb Robotic Exoskeleton: A Case Study

Applied Sciences, 2021
Lower-limb robotic exoskeletons are wearable devices that can be beneficial for people with lower-extremity motor impairment because they can be valuable in rehabilitation or assistance.
Laura Ferrero, Vicente Quiles, Mario Ortiz, Eduardo Iáñez, José M. Azorín   +4 more
doaj   +1 more source

Decoding of Turning Intention during Walking Based on EEG Biomarkers

Biosensors, 2022
In the EEG literature, there is a lack of asynchronous intention models that realistically propose interfaces for applications that must operate in real time.
Vicente Quiles, Laura Ferrero, Eduardo Iáñez, Mario Ortiz, José M. Azorín   +4 more
doaj   +1 more source

Improving Motor Imagery of Gait on a Brain–Computer Interface by Means of Virtual Reality: A Case of Study

IEEE Access, 2021
Motor imagery (MI) is one of the most common paradigms used in brain-computer interfaces (BCIs). This mental process is defined as the imagination of movement without any motion.
L. Ferrero, M. Ortiz, V. Quiles, E. Ianez, J. M. Azorin   +4 more
doaj   +1 more source

Assessing Footwear Comfort by Electroencephalography Analysis

IEEE Access, 2021
Footwear comfort is one of the determinant factors in a buyout decision. The understanding of which brain patterns are involved in the comfort perception of footwear could be an important element to develop the consumer neuroscience field, and could even
M. Ortiz, P. Vicente, E. Ianez, E. Montiel, J. M. Azorin   +4 more
doaj   +1 more source

Detecting the Speed Change Intention from EEG Signals: From the Offline and Pseudo-Online Analysis to an Online Closed-Loop Validation

Applied Sciences, 2022
Control of assistive devices by voluntary user intention is an underdeveloped topic in the Brain–Machine Interfaces (BMI) literature. In this work, a preliminary real-time BMI for the speed control of an exoskeleton is presented.
Vicente Quiles, Laura Ferrero, Eduardo Iáñez, Mario Ortiz, José M. Cano, José M. Azorín   +5 more
doaj   +1 more source