Real-time Prediction of Fast and Slow Delivery of Mental Commands in a Motor Imagery BCI: An Entropy-based Approach

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We prove a quantitative version of the classical Tits' alternative for discrete groups acting on packed Gromov-hyperbolic spaces supporting a convex geodesic bicombing. Some geometric consequences, as uniform estimates on systole, diastole, algebraic entro ...

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 ...

Background Each year, five million people are left disabled after stroke. Upper -extremity (UE) dysfunction is a leading problem. Neuroplasticity can be enhanced by non-invasive brain stimulation (NIBS) but evidence from large, randomized multicenter trial ...

Objective. Selective neuromodulation of deep brain regions has for a long time only been possible through invasive approaches, because of the steep depth-focality trade-off of conventional non-invasive brain stimulation (NIBS) techniques. Approach. An appr ...

The term 'brain-computer interface' (BCI) is widely used. However, even among experts, its meaning can sometimes be unclear 1-3. Lack of clarity from the term has real-world implications: it can muddle regulatory guidelines, it may confuse investors, it ca ...

Compute–forward is a coding technique that enables receiver(s) in a network to directly decode one or more linear combinations of the transmitted codewords. Initial efforts focused on Gaussian channels and derived achievable rate regions via nested lattice ...

Barocaloric (BC) materials provide cheaper and more energy efficient alternatives to traditional refrigerants. Some liquid alkanes were recently shown to exhibit a colossal BC effect, matching the entropy changes in commercial vapour-liquid refrigerants. D ...

Hand gestures are one of the most natural and expressive way for humans to convey information, and thus hand gesture recognition has become a research hotspot in the human-machine interface (HMI) field. In particular, biological signals such as surface ele ...

We propose a structured prediction approach for robot imitation learning from demonstrations. Among various tools for robot imitation learning, supervised learning has been observed to have a prominent role. Structured prediction is a form of supervised le ...

Error-related potentials (ErrPs) are a prominent electroencephalogram (EEG) correlate of performance monitoring, and so crucial for learning and adapting our behavior. It is poorly understood whether ErrPs encode further information beyond error awareness. ...

"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 ...

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 ...

Quantum random number generators (QRNGs) are a burgeoning technology used for a variety of applications, including modern security and encryption systems. Typical methods exploit an entropy source combined with an extraction or bit generation circuit in or ...

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 ...

Photonic crystals, appealing for their ability to control light, are constructed from periodic regions of different dielectric constants. Yet, the structural holy grail in photonic materials, diamond, remains challenging to synthesize at the colloidal leng ...

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 ...

Since the birth of Information Theory, researchers have defined and exploited various information measures, as well as endowed them with operational meanings. Some were born as a "solution to a problem", like Shannon's Entropy and Mutual Information. Other ...

Real-time Prediction of Fast and Slow Delivery of Mental Commands in a Motor Imagery BCI: An Entropy-based Approach

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Discrete groups of packed, non-positively curved, Gromov hyperbolic metric spaces

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

Efficacy and safety of transcranial direct current stimulation to the ipsilesional motor cortex in subacute stroke (NETS): a multicenter, randomized, double-blind, placebo-controlled trial

Safety, tolerability and blinding efficiency of non-invasive deep transcranial temporal interference stimulation: first experience from more than 250 sessions

An application-based taxonomy for brain–computer interfaces

A Unified Discretization Approach to Compute–Forward: From Discrete to Continuous Inputs

Pressure-freezing of dodecane: exploring the crystal structures, formation kinetics and phase diagrams for colossal barocaloric effects in n-alkanes

Motor-Unit Ordering of Blindly-Separated Surface-EMG Signals for Gesture Recognition

A structured prediction approach for robot imitation learning

EEG error-related potentials encode magnitude of errors and individual perceptual thresholds

Combination of Neurotechnologies Towards Personalized Neurorehabilitation for Stroke Patients

Sensory-Motor Neurostimulation to Enhance Exosuit Performance

A 3.3-Gb/s SPAD-Based Quantum Random Number Generator

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

A route to hierarchical assembly of colloidal diamond

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

A Functional Perspective on Information Measures