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Moving Brain-Controlled Devices Outside the Lab: Principles and Applications

Publications associées (59)

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Learning to control a BMI-driven wheelchair for people with severe tetraplegia

José del Rocio Millán Ruiz, Kyuhwa Lee, Serafeim Perdikis, Luca Tonin, Bastien Orset

Mind-controlled wheelchairs are an intriguing assistive mobility solution applicable in complete paralysis. Despite progress in brain-machine interface (BMI) technology, its translation remains elusive. The primary objective of this study is to probe the h ...

Cambridge2022

Motor state transitions and Breathing in Brain Machine Interfaces

Bastien Orset

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

Brain-Computer Interface Racing at the Cybathlon 2016

Brain-computer interfaces measure the electricity produced by the brain and translate it into commands that are sent to a machine. However, it is often difficult to judge how quickly a user will be able to perform a task using a brain-computer interface wi ...

2019

Neuroprosthetics to support impaired hand functions: A multidisciplinary approach combining brain-machine interfaces and wearable exoskeletons

Luca Randazzo

Neuroprosthetics, the discipline that aims at interfacing neural systems to artificially engineered devices, has witnessed in recent years important advancements towards the ultimate goal of augmenting and restoring human functions through technology and a ...

EPFL2018

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During the last years, several studies have suggested that Brain-Computer Interface (BCI) can play a critical role in the field of motor rehabilitation. In this case report, we aim to investigate the feasibility of a covert visuospatial attention (CVSA) dr ...

Frontiers Research Foundation2017

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

An Approach to a Phase Model for Steady State Visually Evoked Potentials

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Jaiber Evelio Cardona Aristizabal, Wilfredo Alfonso Morales

One of the most used signals in Brain Machine Interfaces (BMI) is the Steady State Visually Evoked Potentials (SSVEP). In a SSVEP-based BMI, a visual stimulus that flickers in a constant frequency is presented to the user, and the system has to detect if t ...

Springer International Publishing Ag2017

Motor and cognitive brain circuits of brain-machine interactions

Silvia Marchesotti

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

Reliability and Adaptive Assistance in Brain-Computer Interfaces

Sareh Saeedi

Brain-computer interfaces (BCIs) aim at offering an interaction modality for people with severe motor disabilities. Despite promising advances, BCIs are still confronted with multiple challenges in determining user's intentions reliably, mainly due to high ...

EPFL2016

Context-aware adaptive spelling in motor imagery BCI

José del Rocio Millán Ruiz, Robert Leeb, Serafeim Perdikis

Objective. This work presents a first motor imagery-based, adaptive brain–computer interface (BCI) speller, which is able to exploit application-derived context for improved, simultaneous classifier adaptation and spelling. Online spelling experiments with ...

Institute of Physics2016