Re-Referencing

Dual-layer electrode structure for biosignal detection and noise cancellation.

System and methods for biosignal detection and active noise cancellation

We developed a novel EEG system with a dual-electrode net structure for noise reduction and precise biosignal capture. Incorporating advanced software for signal processing, this invention enhances EEG accuracy, reduces setup complexity, and broadens EEG applications, including brain-computer interfaces, through real-time noise separation and immersive noise layering techniques.

Re-referencing EEG data will delete common mode biological and non-biological signals.

EEG Re-refrencing Methods, Why and How?

In exploring EEG re-referencing techniques, it’s emphasized that re-referencing may unintentionally remove common mode biological signals, crucial for accurate data interpretation. This document from the BRaIN Lab at the University of Central Florida discusses the implications of such data loss and proposes methods to mitigate these effects, ensuring reliable EEG analysis.