SSVEP-EEG Feature Enhancement Method Using an Image Sharpening Filter.

Wenqiang Yan,Yuhui Du,Guanghua Xu,Xiaobi Chen

doi:10.1109/tnsre.2022.3142736

Abstract

Steady-state visual evoked potential (SSVEP) is widely used in brain computer interface (BCI), medical detection, and neuroscience, so there is significant interest in enhancing SSVEP features via signal processing for better performance. In this study, an image processing method was combined with brain signal analysis and a sharpening filter was used to extract image details and features for the enhancement of SSVEP features. The results demonstrated that sharpening filter could eliminate the SSVEP signal trend term and suppress its low-frequency component. Meanwhile, sharpening filter effectively enhanced the signal-to-noise ratios (SNRs) of the single-channel and multi-channel fused signals. Image sharpening filter also significantly improved the recognition accuracy of canonical correlation analysis (CCA), filter bank canonical correlation analysis (FBCCA), and task-related component analysis (TRCA). The tools developed here effectively enhanced the SSVEP signal features, suggesting that image processing methods can be considered for improved brain signal analysis.

Highlights

W HEN human eyes are stimulated by an external stimulus applied at constant frequency, the brain will generate a response with the same frequency as the external stimulus or its harmonics
Time domain analysis revealed that sharpening filtering based on first-order differential can effectively eliminate the trend term of state visual evoked potential (SSVEP) signal, while sharpening filtering based on second-order differential was not effective at elimination of the trend term of SSVEP signal
Enhancement of SSVEP features is essential for the accurate analysis of SSVEP signals

Summary

Introduction

W HEN human eyes are stimulated by an external stimulus applied at constant frequency, the brain will generate a response with the same frequency as the external stimulus or its harmonics. This natural response to visual stimulation can be measured by voltage on the scalp, i.e., steady-state visual evoked potential (SSVEP). The amplitude of SSVEP varies with the stimulus frequency, and a significant steady-state response can be observed up to 90 Hz with optical stimulation of frequency ranging from 1-100 Hz [1].

Methods

Results

Discussion

Conclusion