کنفرانس مهندسی برق ایران

صفحه اصلی / سی امین کنفرانس بین المللی مهندسی برق

Event Related Potentials Extraction using Low-rank Tensor Decomposition

نویسندگان :

Zahra SohrabiBonab¹ Mohammad Bagher Shamsollahi²

1- دانشگاه صنعتی شریف 2- دانشگاه صنعتی شریف

کلمات کلیدی :

Event Related Potentials (ERPs), Tucker Decomposition, Low-Rank Restoration

چکیده :

Event-related potential (ERP) extraction from ongoing electroencephalograph (EEG) and its enhancement is one of the long-established problems in EEG signal processing. Most of the previous studies have focused mainly on the ERP enhancement without considering the multi-dimensional structure of the signal. In order to take advantage of this property, we propose a tensor-based solution with trial-by-trial concatenated ERP data. Then we develop an algorithm based on low-rank Tucker decomposition to detect single trial ERP component with maximized signal to noise ratio (SNR). In other words, by using tensor algebra we consider both self-similarity in intra-trials and global correlation in spatial mode. Applicability of the algorithm is demonstrated in the context of P300 detection with synthetic data and the real EEG data collected from 8 subjects during a visual oddball experiment. Performance of the proposed method is evaluated with approximation errors and classification accuracy.

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