Decoding of Self-paced Lower-Limb Movement Intention: A Case Study on the Influence Factors
Graph Chatbot
Chattez avec Graph Search
Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.
AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.
Human brain is organized by a large number of functionally correlated but spatially distributed cortical neurons. Cognitive processes are usually associated with dynamic interactions among multiple brain regions. Therefore, the understanding of brain funct ...
Objective. Intracortical brain–machine interfaces (BMIs) have predominantly utilized spike activity as the control signal. However, an increasing number of studies have shown the utility of local field potentials (LFPs) for decoding motor related signals. ...
As a result of improved understanding of brain mechanisms as well as unprecedented technical advancement in neural recording methods and computer technology, it is now possible to translate large-scale brain signals into movement intentions in real time. S ...
A brain-machine interface (BMI) is about transforming neural activity into action and sensation into perception (Figure 1). In a BMI system, neural signals recorded from the brain are fed into a decoding algorithm that translates these signals into motor o ...
Brain-machine interfaces (BMI) usually decode movement parameters from cortical activity to control neuroprostheses. This requires subjects to learn to modulate their brain activity to convey all necessary information, thus imposing natural limits on the c ...
Neurotechnology is the application of scientific knowledge to the practical purpose of understanding, interacting and/or repairing the brain or, in a broader sense, the nervous system. The development of novel approaches to decode functional information fr ...
Future emerging technologies in upper limb neuroprosthetic devices will require decoding and executing the user's intended movement. Previous studies, using invasive and non-invasive brain signals, have shown promising results in decoding movement directio ...
Reach and grasp kinematics are known to be encoded in the spiking activity of neuronal ensembles and in local field potentials (LFPs) recorded from primate motor cortex during movement planning and execution. However, little is known, especially in LFPs, a ...
Inverse solution allows to estimate sources that generate a given scalp EEG topography. Recently, it has been used in Brain Computer Interfaces (BCIs) to extract robust features based on the hypothesis that projection onto the source space (high dimensiona ...
Recording neural activities plays an important role in numerous applications ranging from brain mapping to implementation of brain-machine interfaces (BMI) to recover lost functions or to understand the mechanisms behind the neurological disorders such as ...