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Automatic detection of hand hygiene using computer vision technology.
Journal of the American Medical Informatics Association ( IF 6.4 ) Pub Date : 2020-07-26 , DOI: 10.1093/jamia/ocaa115 Amit Singh 1 , Albert Haque 2 , Alexandre Alahi 3 , Serena Yeung 4 , Michelle Guo 2 , Jill R Glassman 5 , William Beninati 6 , Terry Platchek 1, 5 , Li Fei-Fei 2 , Arnold Milstein 5
Journal of the American Medical Informatics Association ( IF 6.4 ) Pub Date : 2020-07-26 , DOI: 10.1093/jamia/ocaa115 Amit Singh 1 , Albert Haque 2 , Alexandre Alahi 3 , Serena Yeung 4 , Michelle Guo 2 , Jill R Glassman 5 , William Beninati 6 , Terry Platchek 1, 5 , Li Fei-Fei 2 , Arnold Milstein 5
Affiliation
Hand hygiene is essential for preventing hospital-acquired infections but is difficult to accurately track. The gold-standard (human auditors) is insufficient for assessing true overall compliance. Computer vision technology has the ability to perform more accurate appraisals. Our primary objective was to evaluate if a computer vision algorithm could accurately observe hand hygiene dispenser use in images captured by depth sensors.
中文翻译:
使用计算机视觉技术自动检测手部卫生。
手卫生对于预防医院获得性感染至关重要,但难以准确追踪。黄金标准(人工审核员)不足以评估真正的整体合规性。计算机视觉技术具有执行更准确的评估的能力。我们的主要目标是评估计算机视觉算法是否可以在深度传感器捕获的图像中准确观察手部卫生分配器的使用情况。
更新日期:2020-09-10
中文翻译:
使用计算机视觉技术自动检测手部卫生。
手卫生对于预防医院获得性感染至关重要,但难以准确追踪。黄金标准(人工审核员)不足以评估真正的整体合规性。计算机视觉技术具有执行更准确的评估的能力。我们的主要目标是评估计算机视觉算法是否可以在深度传感器捕获的图像中准确观察手部卫生分配器的使用情况。