Discriminative Channel Selection Method for the Recognition of Anticipation related Potentials from CCD estimated Cortical Activity
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The measurement of brain activity in a noninvasive way is an essential element in modern neurosciences. Modalities such as electroencephalography (EEG) and magnetoencephalography (MEG) recently gained interest, but two classical techniques remain predomina ...
Institute of Electrical and Electronics Engineers2006
A direct connection between ElectroEncephaloGram (EEG) and the genetic information of individuals has been investigated by neurophysiologists and psychiatrists since 1960’s; and it opens a new research area in the science. This paper focuses on the person ...
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 ...
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 ...
In this paper, we investigate the use of brain activity for person authentication. It has been shown in previous studies that the brain-wave pattern of every individual is unique and that the electroencephalogram (EEG) can be used for biometric identificat ...
Changes in EEG power spectra related to the imagination of movements may be used to build up a direct communication channel between the brain and computer (Brain Computer Interface; BCI). However, for the practical implementation of a BCI device, the featu ...
We compare the use of two Markovian models, HMMs and IOHMMs, to discriminate between three mental tasks for brain computer interface systems using an asynchronous protocol. We show that IOHMMs outperform HMMs but that, probably due to the lack of any prior ...
By directly analyzing brain activity, Brain-Computer Interfaces (BCIs) allow for communication that does not rely on any muscular control and therefore constitute a possible communication channel for the completely paralyzed. Typically, the user performs d ...