A new open dataset called DOSE-I gives researchers annotated biosignal recordings from patients under procedural sedation during endoscopy.
Published on Zenodo, DOSE-I covers 281 endoscopic procedures across 171 records, totaling 78.5 hours of data. Individual records range from 6.7 to 70.8 minutes. The dataset includes 1,129 transitions of consciousness — a median of 6 per record — and 7,328 sedation depth labels, with a median of 39 labels per record. Beyond the raw biosignals, it ships with static subject data, recording metadata, artifact detection notes, preprocessed pEEG features, and C preprocessing code on GitHub.
Sedation monitoring is an area where AI-assisted tools have real clinical stakes: misjudging depth can mean a patient wakes mid-procedure or receives too much drug. Labeled, multimodal biosignal datasets are scarce, which limits how far researchers can push model development — DOSE-I is a direct attempt to close that gap. The pEEG component is worth watching specifically, since processed EEG is one of the more promising signals for real-time consciousness inference.
For now, this is a technical report describing a dataset, not a model with clinical results — so the cautious read is that the hard work of turning these labels into reliable monitoring software still lies ahead.