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. 2024 Oct 22;7:287. doi: 10.1038/s41746-024-01295-2

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© The Author(s) 2024

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

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Fig. 1 — a Head-mounted camera (GoPro Hero8) attached to a head strap and powered by an external battery pack. b Recording drug preparation events using wearable camera system. c Vial swap error from midazolam vial into syringe with ondansetron label. d Real-world operating room use showing that syringe and vial labels are not visible in every frame and can be obscured by the provider’s hand or tilted away. e Real-world environments containing other syringes and vials in the background unrelated to the drug drawup event. f Workflow demonstrating how drug drawup events captured through our system are detected and classified. Medication errors can be communicated to the provider through real-time auditory or visual feedback and automatically recorded.