Add to ORKGInternational audienceThis talk aim to present pattern recognition techniques of graphic elements (e.g. event-related potential, auditory evoked potential, k-complex, sleep spindles, vertex waves) included in electro-encephalographic signals. More specifically, template-based classifiers will be introduced to robustly detect evoked potentials in a single trial from noisy and multi-sources electro-encephalographic signals
International audienceA brain-computer interface (BCI) is a communication system that allows to cont...
A brain-computer interface (BCI) basically gives a second chance to people with motor disabilities t...
Epilepsy is a chronic disease influencing many people’s health worldwide. According to the study of ...
International audienceMore and more effort is done in BCI research to improve its usability for patie...
Objective: Visual analysis of EEG is time consuming and suffers from inter-observer variability. Ass...
International audienceIn this paper, we describe and evaluate the performance of a linear classifier...
A novel instance-based method for the classification of electroencephalography (EEG) signals is pres...
Abstract Detecting event related potentials (ERPs) from single trials is crit-ical to the operation ...
The University of Michigan Direct Brain Interface (UM-DBI) project seeks to detect voluntarily produ...
A direct brain interface (DBI) based on the detection of event-related potentials (ERPs) in human el...
The techniques involved in the development of the brain computer interfaces require the validation o...
National audienceTemplate-based analysis techniques are good candidates to robustly detect transient...
Brain?computer interface (BCI) systems based on electroencephalography have been increasingly usedin...
Detecting event related potentials (ERPs) from single trials is critical to the operation of many st...
© 2001-2011 IEEE. Brain-computer interfaces (BCIs) are desirable for people to express their thought...
International audienceA brain-computer interface (BCI) is a communication system that allows to cont...
A brain-computer interface (BCI) basically gives a second chance to people with motor disabilities t...
Epilepsy is a chronic disease influencing many people’s health worldwide. According to the study of ...
International audienceMore and more effort is done in BCI research to improve its usability for patie...
Objective: Visual analysis of EEG is time consuming and suffers from inter-observer variability. Ass...
International audienceIn this paper, we describe and evaluate the performance of a linear classifier...
A novel instance-based method for the classification of electroencephalography (EEG) signals is pres...
Abstract Detecting event related potentials (ERPs) from single trials is crit-ical to the operation ...
The University of Michigan Direct Brain Interface (UM-DBI) project seeks to detect voluntarily produ...
A direct brain interface (DBI) based on the detection of event-related potentials (ERPs) in human el...
The techniques involved in the development of the brain computer interfaces require the validation o...
National audienceTemplate-based analysis techniques are good candidates to robustly detect transient...
Brain?computer interface (BCI) systems based on electroencephalography have been increasingly usedin...
Detecting event related potentials (ERPs) from single trials is critical to the operation of many st...
© 2001-2011 IEEE. Brain-computer interfaces (BCIs) are desirable for people to express their thought...
International audienceA brain-computer interface (BCI) is a communication system that allows to cont...
A brain-computer interface (BCI) basically gives a second chance to people with motor disabilities t...
Epilepsy is a chronic disease influencing many people’s health worldwide. According to the study of ...