Document Type : Full Research Paper

Authors

• Mohammad Ali Manouchehri ¹
• Vahid Abootalebi ²
• Amin Mahnam ³

¹ M.Sc. Graduate, Department of Electrical Engineering, Yazd University, Yazd, Iran

² Associate Professor, Department of Electrical Engineering, Yazd University, Yazd, Iran

³ Assistant Professor of Biomedical Engineering, Faculty of Engineering, University of Isfahan, Isfahan, Iran

Abstract

SSVEP-based BCI systems have attracted attention of many researchers due to their high signal to noise ratio, high information transfer rate and being easy for use. The processing goal of these systems is to detect the stimulus frequency of EEG signal. Among the processing methods for frequency identification in SSVEP-based BCI systems, LASSO algorithm has gained great acceptance. Although LASSO has acceptable performance in SSVEP-based BCI systems, it doesn't consider the phase of recorded EEG signal for creating the reference signal. In this paper, the idea of correcting the phase of the reference signal with respect to recorded EEG signal was investigated and a new method called phase corrected LASSO was proposed. For this purpose, first, the optimal EEG channel for frequency identification was determined and then, the performance of the phase corrected LASSO method was compared with standard LASSO method. The results show that the phase corrected LASSO method has better performance compared with the standard LASSO method.

Keywords

• Brain-Computer Interface (BCI)
• Steady-State Visual Evoked Potential (SSVEP)
• frequency identification
• LASSO
• Phase Corrected LASSO

Main Subjects

• Biomedical Signal Processing / Medical Signal Processing / Biosignal Processing