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arXiv · 2205.06113

Mask Wearing Status Estimation with Smartwatches

Huina Meng·Xilei Wu·Xin Wang·Yuhan Fan·Jingang Shi·Han Ding·Fei Wang
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Abstract

We present MaskReminder, an automatic mask-wearing status estimation system based on smartwatches, to remind users who may be exposed to the COVID-19 virus transmission scenarios, to wear a mask. MaskReminder with the powerful MLP-Mixer deep learning model can effectively learn long-short range information from the inertial measurement unit readings, and can recognize the mask-related hand movements such as wearing a mask, lowering the metal strap of the mask, removing the strap from behind one side of the ears, etc. Extensive experiments on 20 volunteers and 8000+ data samples show that the average recognition accuracy is 89%. Moreover, MaskReminder is capable to remind a user to wear with a success rate of 90% even in the user-independent setting.

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Huina Meng, Xilei Wu, Xin Wang, Yuhan Fan, Jingang Shi, Han Ding, Fei Wang. 2022-05-12. Mask Wearing Status Estimation with Smartwatches. https://arxiv.org/abs/2205.06113

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