# Artifact filtering application to increase online parity in a communication BCI: progress toward use in daily-life

## TL;DR

This study shows that applying artifact filtering in a way that mimics real-time BCI use improves model performance and reliability for communication BCIs.

## Contribution

The paper introduces and validates an online parity filtering approach for BCIs that better reflects real-world usage.

## Key findings

- Filtering with online parity significantly improved model performance in a BCI communication task.
- Online simulations showed no performance drawbacks with the online parity approach.
- The method is suitable for real-time BCI applications in home or hospital settings.

## Abstract

A significant challenge in developing reliable Brain-Computer Interfaces (BCIs) is the presence of artifacts in the acquired brain signals. These artifacts may lead to erroneous interpretations, poor fitting of models, and subsequent reduced online performance. Furthermore, BCIs in a home or hospital setting are more susceptible to environmental noise. Artifact handling procedures aim to reduce signal interference by filtering, reconstructing, and/or eliminating unwanted signal contaminants. While straightforward conceptually and largely undisputed as essential, suitable artifact handling application in BCI systems remains unsettled and may reduce performance in some cases. A potential confound that remains unexplored in the majority of BCI studies using these procedures is the lack of parity with online usage (e.g., online parity). This manuscript compares classification performance between frequently used offline digital filtering, using the whole dataset, and an online digital filtering approach where the segmented data epochs that would be used during closed-loop control are filtered instead. In a sample of healthy adults (n = 30) enrolled in a BCI pilot study to integrate new communication interfaces, there were significant benefits to model performance when filtering with online parity. While online simulations indicated similar performance across conditions in this study, there appears to be no drawback to the approach with greater online parity.