EEG classification using generative independent component analysis
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People with severe motor disabilities (spinal cord injury (SCI), amyotrophic lateral sclerosis (ALS), etc.) but with intact brain functions are somehow prisoners of their own body. They need alternative ways of communication and control to interact with th ...
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In this paper we investigate the use of a temporal extension of Independent Component Analysis (ICA) for the discrimination of three mental tasks for asynchronous EEG-based Brain Computer Interface systems. ICA is most commonly used with EEG for artifact i ...
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 ...
This thesis explores latent-variable probabilistic models for the analysis and classification of electroenchephalographic (EEG) signals used in Brain Computer Interface (BCI) systems. The first part of the thesis focuses on the use of probabilistic methods ...
