DocumentCode :
2552336
Title :
Signal Modality Characterisation of EEG with Response to Steady-State Auditory and Visual BCI Paradigms
Author :
Chen, Mo ; Mandic, Danilo P. ; Rutkowski, Tomasz M. ; Cichocki, Andrzej
Author_Institution :
Imperial Coll. London, London
fYear :
2007
fDate :
27-29 Aug. 2007
Firstpage :
223
Lastpage :
228
Abstract :
Novel nonlinear dynamical analysis of the electroencephalogram (EEG) data recorded in steady state brain stimulation paradigms is provided. This is achieved based on some recent developments in the local predictability in phase space, which allows for the assessment of the degree of nonlinearity and uncertainty within the EEG data. Both the responses from the visual and auditory experiments are addressed, based on the auditory steady-state responses (ASSR) and steady-state visual evoked potentials (SSVEP). Simulation results show clear difference in the degree of nonlinearity and uncertainty between the segments of EEG data recorded before, during and after the stimulus. This provides a novel insight into the dynamics of the brain information processing mechanism captured in EEG.
Keywords :
electroencephalography; medical signal processing; visual evoked potentials; auditory steady-state response; brain computer interface; brain information processing; electroencephalogram data; nonlinear dynamical analysis; steady state brain stimulation; steady-state visual evoked potential; Brain computer interfaces; Computer interfaces; Electroencephalography; Humans; Signal analysis; Signal generators; Signal processing; Steady-state; Stochastic processes; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning for Signal Processing, 2007 IEEE Workshop on
Conference_Location :
Thessaloniki
ISSN :
1551-2541
Print_ISBN :
978-1-4244-1566-3
Electronic_ISBN :
1551-2541
Type :
conf
DOI :
10.1109/MLSP.2007.4414310
Filename :
4414310
Link To Document :
بازگشت