WHO-Hand Hygiene Gesture Classification System

نویسندگان

چکیده

The recent ongoing coronavirus pandemic highlights the importance of hand hygiene practices in our daily lives, with governments and worldwide health authorities promoting good practices. More than one million cases hospital-acquired infections occur Europe annually. Hand compliance may reduce risk transmission by reducing number as well healthcare expenditures. In this paper, World Health Organization, gestures are recorded analyzed construction an aluminum frame, placed at laboratory sink. for thirty participants after conducting a training session about demonstration. video recordings converted into image files organized six different classes. Resnet50 framework selection classification multiclass stages. model is trained first set classes; Fingers Interlaced, P2PFingers Rotational Rub 25 epochs. An accuracy 44 percent experiments loss score greater 1.5 validation achieved. steps second hands palm to palm, Interlocked, Thumb 50 72 achieved less 0.8 set. work, preliminary analysis robust dataset transfer learning takes place. future aim deploying prediction system workers real-time.

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ژورنال

عنوان ژورنال: International Journal of Machine Learning and Computing

سال: 2022

ISSN: ['2010-3700']

DOI: https://doi.org/10.18178/ijmlc.2022.12.6.312