Titlebook: Brain-Computer Interface Research; A State-of-the-Art S Christoph Guger,Brendan Allison,Milena Korostenska Book 2024 The Editor(s) (if appl

Allowance

Brain-Computer Interface Research: A State-of-the-Art Summary 11,mmands without moving. In 2010, we launched the Annual BCI Research Awards. People submit their projects to a jury that scores each project on many criteria and then selects the best projects from that year. This book contains project summaries written by most of the teams that were nominated for a

Femish

Remediating Phonological Deficits in Dyslexia with Brain-Computer Interfaces,we design a non-invasive EEG-BCI relying on auditory inputs and visual feedback to optimise brain patterns related to phonology (speech-sound) and reading deficits in children with dyslexia. Drawing from a decade of dyslexia neuroscience research on perceptive ‘temporal sampling’ along with computat

monopoly

Highly Generalizable Spelling Using a Silent-Speech BCI in a Person with Severe Anarthria,) technology has the potential to restore communication to people who cannot speak or type due to paralysis. Recent advances have enabled users to communicate by attempting to speak, type, or handwrite intended messages. Another approach may be to spell out intended words and sentences with a BCI th

秘傳

Fast, Accurate, Unsupervised, and Time-Adaptive EEG-Based Auditory Attention Decoding for Neuro-ste of life. However, current hearing technology does not work well in cocktail party scenarios, where several people talk simultaneously. This is mainly because the hearing device does not know which speaker the user is attending to, and so which speaker should be amplified relative to the background

火花

Closed-Loop Control of Images Based on Electrocorticogram Decoding in Visual Semantic Space,sual images decoded from electrocorticograms (ECoGs) could be controlled to represent intentional meaning in a closed-loop condition. ECoGs were recorded while subjects watched videos containing natural scenes, while the annotations of the scenes in the videos were converted into vectors in the visu

intuition

Digital Bridge to Restore Voluntary Control of Leg Movements After Paralysis,ven suppresses voluntary control of muscles, leading to permanent paralysis. Yet, the motor cortex remains able to generate meaningful neuronal activity during attempts to move the paralyzed limbs. This activity can be detected as electrical potential recorded at the surface of the brain. Similarly,

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Brain-Body Interfaces to Assist and Restore Motor Functions in People with Paralysis,rged as a solution to achieve two complementary rehabilitation objectives in people with motor deficits: induce long-lasting neurological recovery and assist motor functions during daily activities. Here, we describe representative promising implementations for both applications and future steps tow

canonical

MANIA

Real-Time Decoding of Leg Motor Function and Dysfunction from the Subthalamic Nucleus in People wittials (LFP) recorded from the subthalamic nucleus of patients with Parkinson’s disease. Concretely, we designed decoders that can predict locomotor states, gait events, modulations in force during obstacle avoidance, and freezing of gait episodes while participants walked freely in unconstrained con

antiquated