Phase synchronization for classification of spontaneous EEG signals in brain-computer interfaces
Related publications (118)
Graph Chatbot
Chat with Graph Search
Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.
DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.
In this work we present a multichannel EEG decomposition model based on an adaptive topographic time-frequency approximation technique. It is an extension of the Matching Pur- suit algorithm and called Dependency Multichannel Matching Pursuit (DMMP). It ta ...
Recent experiments have shown the possibility to use the brain electrical activity to directly control the movement of robots or prosthetic devices in real time. Such neuroprostheses can be invasive or non-invasive, depending on how the brain signals are r ...
We present an application of Independent Component Analysis (ICA) to the discrimination of mental tasks for EEG-based Brain Computer Interface systems. ICA is most commonly used with EEG for artifact identification with little work on the use of ICA for di ...
Brain-computer interfaces, as any other interaction modality based on physiological signals and body channels (e.g., muscular activity, speech and gestures), are prone to errors in the recognition of subject's intent. In this paper we exploit a unique feat ...
We present a training and testing method for Input-Output Hidden Markov Model that is particularly suited for classification of sequences in which class information accumulates over time. We discuss two such cases: the discrimination of mental tasks from s ...
A BCI allows a person to communicate with the external world using artificial electronic or mechanical devices controlled by means of brain signals. Present-day BCIs can be divided into invasive and noninvasive. Prospective application of invasive BCIs to ...
Scalp recorded electroencephalogram signals (EEG) reflect the combined synaptic and axonal activity of groups of neurons. In addition to their clinical applications, EEG signals can be used as support for direct brain-computer communication devices (Brain- ...
A brain-computer interface (BCI) is a communication system, that implements the principle of "think and make it happen without any physical effort". This means a BCI allows a user to act on his environment only by using his thoughts, without using peripher ...
Electroencephalogram recordings during imagination of mental tasks allow for developing a new communication device for, e.g., motor disabled people. 32-channel EEG was recorded from 5 healthy subjects while performing, after instruction and in random order ...
We present an application of Independent Component Analysis (ICA) to the discrimination of mental tasks for EEG-based Brain Computer Interface systems. ICA is most commonly used with EEG for artifact identification with little work on the use of ICA for di ...