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Objective. A key challenge of virtual reality (VR) applications is to maintain a reliable human-avatar mapping. Users may lose the sense of controlling (sense of agency), owning (sense of body ownership), or being located (sense of self-location) inside th ...

The rise of robotic body augmentation brings forth new developments that will transform robotics, human-machine interaction, and wearable electronics. Extra robotic limbs, although building upon restorative technologies, bring their own set of challenges i ...

Novel usages of brain stimulation combined with artificially intelligent (AI) systems promise to address a large range of diseases. These new conjoined technologies, such as brain-computer interfaces (BCI), are increasingly used in experimental and clinica ...

"Ensure healthy lives and promote well-being for all at all ages" is the third sustainable development goal for the United Nations Agenda of 2030. This doctoral thesis fully embodied this objective by targeting stroke, a leading cause of death and disabili ...

Over the past two decades, epidural electrical stimulation (EES) has transitioned from a treatment for chronic pain to a promising paradigm for ameliorating deficits associated with neurological disorders like spinal cord injury (SCI) and Parkinson's Disea ...

Intracortical brain-machine interfaces decode motor commands from neural signals and translate them into actions, enabling movement for paralysed individuals. The subjective sense of agency associated with actions generated via intracortical brain-machine ...

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 ...

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 ...

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 ...

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 ...

Brain-computer interfaces (BCIs) are neural prosthetics that enable closed-loop electrophysiology procedures. These devices are currently used in fundamental neurophysiology research, and they are moving toward clinical viability for neural rehabilitation. ...

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 ...

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 ...

Development of neural interface and brain-machine interface (BMI) systems enables the treatment of neurological disorders including cognitive, sensory, and motor dysfunctions. While neural interfaces have steadily decreased in form factor, recent developme ...

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 ...

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 ...

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 ...

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 ...

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 ...

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Customizing the human-avatar mapping based on EEG error related potentials during avatar-based interaction

Investigating neural resource allocation in the sensorimotor control of extra limbs

How I became myself after merging with a computer: Does human-machine symbiosis raise human rights issues?

Combination of Neurotechnologies Towards Personalized Neurorehabilitation for Stroke Patients

Closed-Loop Control of Epidural Electrical Stimulation in Patients with Spinal Cord Injury and Parkinson's Disease

Sense of agency for intracortical brain-machine interfaces

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

The present and future of neural interfaces

Shared Intelligence for Robot Teleoperation via BMI

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

Adaptive Wireless Power Transfer and Backscatter Communication for Perpetual Operation of Wireless Brain-Computer Interfaces

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

Motor state transitions and Breathing in Brain Machine Interfaces

Neural interface systems with on-device computing: machine learning and neuromorphic architectures

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

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

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

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

Integration of hybrid material systems in conformable neural interfaces