Spatial filters yield stable features for error-related potentials across conditions

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Transient electronics enabling devices to safely disappear in the environment can be applied not only in green electronics, but also in bioelectronic medicine. Neural implants able to degrade harmlessly inside the body eliminate the need for removal surger ...

Decoding visual cognition from non-invasive measurements of brain activity has shown valuable applications. Vision-based Brain-Computer Interfaces (BCI) systems extend from spellers to database search and spatial navigation. Despite the high performance of ...

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 ...

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 ...

The 2020's decade will likely witness an unprecedented development and deployment of neurotechnologies for human rehabilitation, personalized use, and cognitive or other enhancement. New materials and algorithms are already enabling active brain monitoring ...

Objective. Accurate decoding of individual finger movements is crucial for advanced prosthetic control. In this work, we introduce the use of Riemannian-space features and temporal dynamics of electrocorticography (ECoG) signal combined with modern machine ...

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 ...

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 ...

This article proposes a novel shared intelligence system for brain-machine interface (BMI) teleoperated mobile robots where user's intention and robot's intelligence are concurrent elements equally participating in the decision process. We designed the sys ...

Recently, flexible and soft bioelectronic interfaces have been proposed as a solution to improve existing neural interfaces that currently present mechanical mismatch with the soft tissue. These are devices fabricated with thin polymeric or elastomeric bac ...

Voluntary action is a fundamental element of self-consciousness. The readiness potential (RP), a slow drift of neural activity preceding self-initiated movement, has been suggested to reflect neural processes underlying the preparation of voluntary action; ...

Transcranial (electro)magnetic stimulation (TMS) is currently the method of choice to non-invasively induce neural activity in the human brain. A single transcranial stimulus induces a time-varying electric field in the brain that may evoke action potentia ...

Objective.Mobile Brain/Body Imaging (MoBI) frameworks allowed the research community to find evidence of cortical involvement at walking initiation and during locomotion. However, the decoding of gait patterns from brain signals remains an open challenge. ...

Visual backward masking (VBM) deficits are candidate endophenotypes of schizophrenia indexing genetic liability of the disorder. In VBM, a target is followed by a mask that deteriorates target perception. Schizophrenia patients and, to a lesser extent, the ...

Peripheral neural interfaces have been successfully used in the recent past to restore sensory-motor functions in disabled subjects and for the neuromodulation of the autonomic nervous system. The optimization of these neural interfaces is crucial for ethi ...

The ability to notice erroneous behavior is crucial for effective training. Within the framework of neuroprosthetics, numerous studies in electroencephalography (EEG) confirm the existence of neural correlates when humans perceive the erroneous actions of ...

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 ...

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 ...

Spatial filters yield stable features for error-related potentials across conditions

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Development of a Transient Neural Interface for Minimally Invasive Recording and Stimulation

Towards everyday brain-computer interfacing through decoding visual cognition

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

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

The present and future of neural interfaces

Fast and accurate decoding of finger movements from ECoG through Riemannian features and modern machine learning techniques

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

Longitudinal neural and vascular structural dynamics produced by chronic microelectrode implantation

Shared Intelligence for Robot Teleoperation via BMI

Conformable neural interfaces : from engineering stretchability at the micro-scale to translational applications

Breathing is coupled with voluntary action and the cortical readiness potential

Transcranial magnetic stimulation of the brain: What is stimulated? - A consensus and critical position paper

Deep learning-based BCI for gait decoding from EEG with LSTM recurrent neural network

Neural Compensation Mechanisms of Siblings of Schizophrenia Patients as Revealed by High-Density EEG

Tutorial: a computational framework for the design and optimization of peripheral neural interfaces

Decoding of error-related potentials in continuous feedback protocols for personalized human computer interaction

Closed-Loop Neural Interfaces with Embedded Machine Learning

Motor state transitions and Breathing in Brain Machine Interfaces