Key result
Hybrid VMD-LGBM improves accuracy and information transfer rate for single-channel SSVEP detection.
Why the study?
Single-channel SSVEP configurations are simple and user-friendly compared to intricate multichannel setups, but attaining necessary accuracy is difficult, requiring a reliable and accurate single-channel technique.
A novel hybrid VMD-LGBM approach improves the accuracy and information transfer rate of single-channel SSVEP detection for brain-computer interfaces.
May advance accessible single-channel BCIs; leaves open prospective validation before clinical use.
Steady-state visual evoked potential (SSVEP) is a brain response to flickering visual stimuli in the occipital area. SSVEP detection methods usually utilize multichannel configurations, which can be intricate and uncomfortable. Conversely, single-channel configurations are simple and user-friendly, but attaining the necessary accuracy is difficult, requiring the development of a reliable and accurate single-channel technique. For this purpose, this study introduces a hybrid VMD-LGBM approach to single-channel SSVEP detection. The proposed technique utilizes VMD as a preprocessor that decomposes the SSVEP signal into harmonic, intrinsic mode functions (IMFs), and noisy IMFs. To separate harmonic IMFs from noisy IMFs, the crest factor of the cross-correlation function was introduced. Then the restored SSVEP signal is used to extract features using power spectral density analysis (Welch's approach), followed by classification using a Light Gradient Boosting Machine. Our proposed approach performs better than available techniques in terms of classification accuracy and information transfer rate. The proposed single-channel approach provides better efficiency and user-friendliness for practical applications.
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Wahab et al. (2024) studied Steady-state visual evoked potential (SSVEP) detection for BCI systems. Hybrid VMD-LGBM approach vs. Available techniques was evaluated on Classification accuracy and information transfer rate. A hybrid VMD-LGBM approach for single-channel SSVEP detection outperformed available techniques in classification accuracy and information transfer rate.
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