DOSE-I: A Multimodal Biosignal Dataset of Procedural Sedation for Endoscopy -- Technical Report
arXiv:2607.02570v1 Announce Type: cross Abstract: In this document, we describe characteristics and technical details of the multimodal biosignal dataset DOSE-I of procedural sedation for endoscopy published on zenodo. The DOSE-I dataset includes 78.5 hours of recording in 171 records ranging from 6.7 to 70.8 minutes (mean: 27.5, SD: 11.6) of 281 endoscopic procedures. 1129 (median: 6 per record) transitions of consciousness and 7328 (median: 39 per record) individual sedation depth labels were recorded. In addition to clinically annotated biosignals, the DOSE-I dataset provides detailed stati
The proliferation of digital health records and advanced sensing technologies allows for the creation of rich, multimodal biosignal datasets, accelerating AI applications in healthcare.
This dataset provides critical annotated data for training AI models in procedural sedation, potentially leading to more precise, safer, and automated patient monitoring during medical procedures.
The availability of a large, multimodal, and clinically annotated dataset for procedural sedation elevates the potential for AI-driven analytics and interventions in this specific medical domain.
- · AI healthcare developers
- · Medical device manufacturers
- · Anesthesiologists
- · Patients undergoing endoscopy
- · Traditional sedation monitoring techniques
AI models will be developed and refined to predict and manage sedation depth more effectively.
Improved patient safety and outcomes during endoscopic and other procedural sedations due to AI-assisted monitoring.
Potential for fully autonomous sedation systems, reducing the need for direct human oversight in routine procedures.
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Read at arXiv cs.AI