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Enhanced Performance of a Brain Switch by Simultaneous Use of EEG and NIRS Data for Asynchronous Brain-Computer
Summary
This study developed a hybrid electroencephalography (EEG)/near-infrared spectroscopy (NIRS) brain switch, outperforming single-modality systems. The hybrid approach significantly improved brain switch performance, particularly reducing false positives for BCI applications.
Area of Science:
- Neuroscience
- Biomedical Engineering
- Signal Processing
Background:
- Hybrid electroencephalography (EEG)/near-infrared spectroscopy (NIRS) brain-computer interfaces (BCIs) show superior performance.
- The effectiveness of hybrid EEG/NIRS for brain switches detecting the onset of user intention remains unclear.
Purpose of the Study:
- To develop and evaluate a hybrid EEG/NIRS brain switch.
- To compare its performance against single-modality EEG and NIRS brain switches.
- To assess performance in detecting the onset of BCI activation intention.
Main Methods:
- Developed a hybrid EEG/NIRS brain switch.
- Compared performance metrics including true positive rate (TPR), false positive rate (FPR), onset detection time (ODT), and information transfer rate (ITR).
- Conducted both offline and pseudo-online analyses to validate system feasibility.
Main Results:
- The hybrid EEG/NIRS brain switch demonstrated significantly improved overall performance compared to single-modality switches.
- A notably lower false positive rate (FPR) was achieved with the hybrid system.
- Pseudo-online analysis results generally aligned with offline findings, confirming practical feasibility.
Conclusions:
- A hybrid EEG/NIRS brain switch offers superior onset detection performance compared to using EEG or NIRS alone.
- The hybrid approach enhances BCI reliability by reducing false positives.
- The developed system is feasible for online BCI implementation.
