EEG

The hospital problem is not that EEG is too small. It is that EEG refuses to stay the same shape. A hospital does not run machine learning inside a clean benchmark. It runs it across devices, departments, vendors, technicians, recording protocols, and patients who rarely behave like textbook signals. Electroencephalography, or EEG, makes this especially inconvenient. The signal is long, noisy, clinically useful, and structurally inconsistent. Different datasets may use different electrode counts. Different institutions may follow different montage conventions. A model that looks competent on one electrode layout can become less confident when the scalp is wired slightly differently. Apparently, brains did not agree to standardize themselves for our convenience. ...