Difference between revisions of "BioSignal Analysis"
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Revision as of 15:34, 29 July 2009
Analysis of biological signals to understand high-level features of people producing them.
Click here for a brief description of the Research Area, taken from the AIRLab website.
Projects
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- Affective Computing - Analysis of biological signals to understand humans emotions
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- Brain-Computer Interface - Analysis of EEG data to control or interact with artificial devices
- Characterization of the NIA signal (Characterization of the NIA signal From AIRWiki Jump to: navigation, search)
- Stimulus tagging using aperiodic visual stimulation in a VEP-based BCI (Stimulus tagging using aperiodic visual stimulation in a VEP-based BCI)
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- Analysis of the Olfactory Signal - Analysis of the olfactory signal by an electronic nose
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- Classification of EMG signals - Increase the effectiveness of active hand prostheses with EMG signals
Project Proposals
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- Aperiodic visual stimulation in a VEP-based BCI (Aperiodic visual stimulation in a VEP-based BCI)
- Creation of new EEG training by introduction of noise (Creation of new EEG training by introduction of noise)
- Real-time removal of ocular artifact from EEG (Real-time removal of ocular artifact from EEG)
- Multimodal GUI for driving an autonomous wheelchair (Multimodal GUI for driving an autonomous wheelchair)
- Exploratory data analysis by genetic feature extraction (Exploratory data analysis by genetic feature extraction)
- Driving an autonomous wheelchair with a P300-based BCI (Driving an autonomous wheelchair with a P300-based BCI)
People
Useful Resources
- AirBAT is a repository containing software developed in projects related to this area. See instructions here.
