Comparative Study of Frequency Recognition Techniques for Steady-State Visual Evoked Potentials According to the Frequency Harmonics and Stimulus Number
Author(s):
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Background
A key challenge in steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) systems is to effectively recognize frequencies within a short time window. To address this challenge, the specific characteristics of the data are needed to select the frequency recognition method. These characteristics include factors, such as the number of stimulation targets and the presence of harmonic frequencies, resulting in optimizing the performance and accuracy of SSVEP-based BCI systems.Objective
The current study aimed to examine the effect of data characteristics on frequency recognition accuracy.Material and Methods
In this analytical study, five commonly used frequency recognition methods were examined, used to various datasets containing different numbers of frequencies, including sub-data with and without frequency harmonics.Results
The increase in the number of frequencies in the Multivariate Linear Regression (MLR) method has led to a decrease in frequency recognition accuracy by 9%. Additionally, the presence of harmonic frequencies resulted in an 8% decrease in accuracy for the MLR method. Conclusion
Frequency recognition using the MLR method reduces the effect of the number of different frequencies and harmonics of the stimulation frequencies on the frequency recognition accuracy.Keywords:
Language:
English
Published:
Journal of Biomedical Physics & Engineering, Volume:14 Issue: 4, Jul-Aug 2024
Pages:
365 to 378
https://www.magiran.com/p2747634
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