Learn how to classify sleep stages using EEG data with Python, MNE, and Scikit-learn in this step-by-step guide. More for You Hillary Clinton breaks silence on Trump’s controversial $400m Qatari jet ...

For this study, the research team enlisted 16 experts, including EEG technologists and fellowship-trained neurologists, to rate 1,440 iEEG channels as "good" or "bad." ...

The researchers trained machine learning algorithms on multichannel EEG segments, with the aim of predicting seizure recurrence 1-year after evaluation. The median (SD) age of patients was 50 (IQR ...

That’s very cool. I’ve a big interest in what can be done with consumer grade EEG hardware. For anybody else that’s interested in an alternative to the emotiv epoc, there’s the kt88-1016.

EEG pattern-detecting algorithms have been around a while, but the researchers note that most are event-specific; they’re hardwired to recognize known electrical patterns.

Cutting-edge algorithm improves intracranial EEG accuracy to improve future patient care. ScienceDaily. Retrieved June 2, 2025 from www.sciencedaily.com / releases / 2024 / 08 / 240827140719.htm.

The study was a sub-analysis of data from the retrospective SAFER-EEG trial. The Clarity algorithm was run post-hoc in 344 cases with point-of-care EEGs at four academic centers.

More information: Tariq Hattab et al, Assessing expert reliability in determining intracranial EEG channel quality and introducing the automated bad channel detection algorithm, Journal of Neural ...