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

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Related publications (30)

Towards BCI-Based Interfaces for Augmented Reality: Feasibility, Design and Evaluation

Nicolas Julien Roussel, Camille Marie Jeunet

Brain-Computer Interfaces (BCIs) enable users to interact with computers without any dedicated movement, bringing new hands-free interaction paradigms. In this paper we study the combination of BCI and Augmented Reality (AR). We first tested the feasibilit ...

2020

Hybrid Human-Machine Interface for Gait Decoding Through Bayesian Fusion of EEG and EMG Classifiers

Luca Tonin, Silvestro Micera, Fiorenzo Artoni, Stefano Tortora

Despite the advances in the field of brain computer interfaces (BCI), the use of the sole electroencephalography (EEG) signal to control walking rehabilitation devices is currently not viable in clinical settings, due to its unreliability. Hybrid interface ...

2020

Longitudinal neural and vascular structural dynamics produced by chronic microelectrode implantation

Andrea Lozzi

Implanted microelectrode arrays sense local neuronal activity, signals which are used as control commands for brain computer interface (BCI) technology. Patients with tetraplegia have used BCI technology to achieve an extraordinary degree of interaction wi ...

2020

A hybrid Body-Machine Interface integrating signals from muscles and motions

Camilla Pierella

Objective.Body-Machine Interfaces (BoMIs) establish a way to operate a variety of devices, allowing their users to extend the limits of their motor abilities by exploiting the redundancy of muscles and motions that remain available after spinal cord injury ...

IOP PUBLISHING LTD2020

The Role of the Control Framework for Continuous Teleoperation of a Brain-Machine Interface-Driven Mobile Robot

José del Rocio Millán Ruiz, Luca Tonin, Felix Christian Bauer

Despite the growing interest in brain-machine interface (BMI)-driven neuroprostheses, the translation of the BMI output into a suitable control signal for the robotic device is often neglected. In this article, we propose a novel control approach based on ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Integration of hybrid material systems in conformable neural interfaces

Florian Dylan Fallegger

Neural interfaces are devices that are implanted into the body and interface electrically with the central (CNS) or peripheral nervous system. They are inserted surgically for short periods of time or chronically to diagnose or treat several neural disease ...

EPFL2020

Turning negative into positives! Exploiting 'negative' results in Brain-Machine Interface (BMI) research

Ricardo Andres Chavarriaga Lozano, Camille Marie Jeunet

Results that do not confirm expectations are generally referred to as 'negative' results. While essential for scientific progress, they are too rarely reported in the literature - Brain-Machine Interface (BMI) research is no exception. This led us to organ ...

TAYLOR & FRANCIS LTD2019

Closed-Loop Neural Interfaces with Embedded Machine Learning

Mahsa Shoaran, Uisub Shin, Bingzhao Zhu

Neural interfaces capable of multi-site electrical recording, on-site signal classification, and closed-loop therapy are critical for the diagnosis and treatment of neurological disorders. However, deploying machine learning algorithms on low-power neural ...

IEEE2020

Brain reactions to the use of sensorized hand prosthesis in amputees

Fabrizio Vecchio, Edoardo D'Anna, Silvestro Micera, Stanisa Raspopovic, Francesco Maria Petrini, Ivo Strauss, Giacomo Valle, Francesco Iberite

Objective We investigated for the first time the presence of chronic changes in the functional organization of sensorimotor brain areas induced by prolonged training with a bidirectional hand prosthesis. Methods A multimodal neurophysiological and neuroima ...

2020

The Human-Computer Connection An Overview Of Brain-Computer Interfaces

José del Rocio Millán Ruiz

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 ...

2019

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