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Kiran Kumar Guruswamy Ravindran

Bio: Kiran Kumar Guruswamy Ravindran is an academic researcher. The author has co-authored 1 publications.

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Proceedings ArticleDOI
01 Oct 2018
TL;DR: A novel, high accuracy, calibration less spatial filter for reliable steady-state visual evoked potential (SSVEP) extraction from noisy electroencephalogram (EEG) data called exactly periodic subspace decomposition (EPSD).
Abstract: This study introduces a novel, high accuracy, calibration less spatial filter for reliable steady-state visual evoked potential (SSVEP) extraction from noisy electroencephalogram (EEG) data. The proposed method, exactly periodic subspace decomposition (EPSD), utilises the periodic properties of the SSVEP components to achieve a robust spatial filter for SSVEP extraction. It tries to extract the SSVEP components by projecting the EEG data onto a subspace where only the target signal components are retained. The performance of the method was tested on an SSVEP dataset obtained from ten subjects and compared with common SSVEP spatial filtering and detection techniques. The results obtained from the study shows that EPSD consistently provides a significant improvement in detection performance than other SSVEP spatial filters used in brain-computer interface (BCI) applications.