Quantitative Evaluation of Hand Washing Skills Based on Convolutional Neural Network for Nursing Education

Kazushi Yamamoto, M. Yoshii, Fumiya Kinoshita, Hideaki Touyama
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引用次数: 1

Abstract

The World Health Organization (WHO) reports that hand hygiene education is important for health workers. However, handwashing methods in hospitals require specialized handwashing knowledge. In this paper, we present a new quantitative handwashing skills assessment method based on the Convolutional Neural Network (CNN). An image capture box with blacklights was created and photos were taken before and after handwashing after the application of fluorescent paint. The photos after handwashing were labeled by specialists in each part. The total number of photos after handwashing labeled by specialists was 585. After that, 9-fold cross-validation was performed on the photos after handwashing to calculate the discrimination accuracy (F-value). As a result, the F-value was 81 . 26 ± 6 . 18% in the handwashing image evaluation system using CNN.
基于卷积神经网络的护理教育洗手技能定量评价
世界卫生组织(WHO)报告称,手部卫生教育对卫生工作者很重要。然而,医院的洗手方法需要专门的洗手知识。本文提出了一种基于卷积神经网络(CNN)的洗手技能定量评估新方法。我们制作了一个带有黑灯的图像捕捉盒,并在涂上荧光漆洗手前后拍摄了照片。洗手后的照片由专家在每个部分进行标记。经专家标记的洗手后照片总数为585张。然后对洗手后的照片进行9倍交叉验证,计算识别准确率(f值)。结果,f值为81。26±6。18%在洗手图像评价系统中使用CNN。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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