Enhancing Temporal Classification of AAR Parameters in EEG single-trial analysis for Brain-Computer Interfacing.
Adaptive autoregressive (AAR) coefficients provide dynamic spectral information in EEG single-trial analysis. In this paper we propose a temporal evidence accumulation framework to enhance classification of AAR features. The results for a single subject, using 280 trials, indicate distinct improvements over a conventional method of temporal classification. We illustrate how the framework is applicable to AAR features, as well as to wavelet features as reported in [13]. These findings put the two time-frequency features on equal footing for comparison in this context.
Dharwarkar
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Pattern Analysis and Machine Intelligence (PAMI) Lab Electrical and Computer Engineering, University of Waterloo.
Basir
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