Description:
- Uses steady-state visually evoked potentials (SSVEPs) as endogenous reference signals for cross-session EEG calibration.
- Creates a subject-specific linear mapping that aligns raw EEG recordings to a common neural baseline.
- Reduces the impact of session dependent recording differences to support consistent longitudinal EEG analysis.
Abstract
This technology uses steady-state visually evoked potentials (SSVEPs) as calibration references for cross-session EEG normalization. Fixed-frequency visual stimuli (e.g., 10Hz, 15Hz) evoke stable responses used to create a linear mapping—via ordinary least squares or ridge regression—that calibrates raw EEG data to a common reference. Aligning to this baseline reduces inter-session variability, improves event-related potential (ERP) fidelity, and achieves up to 80% similarity in neural profiles, supporting reliable cognitive state decoding for clinical diagnostics and brain-computer interface (BCI) systems.
Benefit
- Improves EEG consistency without invasive methods or strict electrode placement
- Enables mental state decoding with ~80% reproducibility across sessions
- Reduces noise using endogenous calibration signals
- Supports scalable BCI deployment with minimal recalibration
Other
- Experimentally validated
- Available for exclusive and non-exclusive license