# A labeled dataset of simulated phlebotomy procedures for medical AI: polygon annotations for object detection and human-object interaction

Source: [A labeled dataset of simulated phlebotomy procedures for medical AI: polygon annotations for object detection and human-object interaction](<https://www.sota2.com/research/paper/6984242ea8b01e76cc8ee831>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-02-06T05:00:14.101Z

Authors: Ra\\'ul Jim\\'enez Cruz, C\\'esar Torres-Huitzil, Marco Franceschetti, Ronny Seiger, Luciano Garc\\'ia-Ba\\~nuelos, Barbara Weber

Published: 2026-02-04T14:54:46.000Z

## Abstract

This data article presents a dataset of 11,884 labeled images documenting a simulated blood extraction (phlebotomy) procedure performed on a training arm. Images were extracted from high-definition videos recorded under controlled conditions and curated to reduce redundancy using Structural Similarity Index Measure (SSIM) filtering. An automated face-anonymization step was applied to all videos prior to frame selection. Each image contains polygon annotations for five medically relevant classes: syringe, rubber band, disinfectant wipe, gloves, and training arm. The annotations were exported in a segmentation format compatible with modern object detection frameworks (e.g., YOLOv8), ensuring broad usability. This dataset is partitioned into training (70%), validation (15%), and test (15%) subsets and is designed to advance research in medical training automation and human-object interaction. It enables multiple applications, including phlebotomy tool detection, procedural step recognition, workflow analysis, conformance checking, and the development of educational systems that provide structured feedback to medical trainees. The data and accompanying label files are publicly available on Zenodo.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2602.04624>)

[PDF](<https://arxiv.org/pdf/2602.04624.pdf>)