Vision-Based Shared Control for a BCI Wheelchair

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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 ...

"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 ...

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 ...

Objective: Home-based non-invasive brain stimulation (NIBS) has been suggested as an adjunct treatment strategy for neuro-psychiatric disorders. There are currently no available solutions to direct and monitor correct placement of the stimulation electrode ...

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 ...

Operation of a tokamak device requires the coordinated operation of a multitude of systems. The sequence of operations during a discharge is both too complex and fast for human interaction. A common way of operation is a predefined sequence of operations w ...

Abstractive summarization has seen big improvements in recent years, mostly due to advances in neural language modeling, language model pretraining, and scaling models and datasets. While large language models generate summaries that are fluent, coherent, ...

Exosuits typically provide limited mechanical support and rely on a user's residual functional ability. However, people with neurological impairments often suffer from both motor and sensory deficits that limit the assistance an exosuit can provide. To ove ...

Background: Simulating the cardiac function requires the numerical solution of multi-physics and multi-scale mathematical models. This underscores the need for streamlined, accurate, and high-performance computational tools. Despite the dedicated endeavors ...

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 ...

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 ...

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 ...

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 ...

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 ...

Robotic systems are becoming more and more pervasive in modern industrial, scientific and personal activities through recent years and will play a fundamental role in the future society. Despite their increasing level of automation, teleoperation is still ...

The RAPTOR suite of codes combines real-time model-based predictions of the plasma state with the available diagnostic measurements. Following the work on TCV and ASDEX-Upgrade, this paper presents the implementation of the RAPTOR suite for JET. This suite ...

Vision-Based Shared Control for a BCI Wheelchair

Chattez avec Graph Search

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

Combination of Neurotechnologies Towards Personalized Neurorehabilitation for Stroke Patients

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

Computer vision-based algorithm to sUppoRt coRrect electrode placemeNT (CURRENT) for home-based electric non-invasive brain stimulation

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

Dynamic pulse scheduling in ASDEX Upgrade: Disruption avoidance and investigation of the H-Mode density limit

Interpretable Representation Learning and Evaluation for Abstractive Summarization

Sensory-Motor Neurostimulation to Enhance Exosuit Performance

lifex-ep: a robust and efficient software for cardiac electrophysiology simulations

Sense of agency for intracortical brain-machine interfaces

The present and future of neural interfaces

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

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

Shared Intelligence for Robot Teleoperation via BMI

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

Personalized Body-Machine Interfaces for Advanced Human-Robot Interaction

Development of the RAPTOR suite of codes towards real-time reconstruction of JET discharges