论文标题
面具戴着智能手表的状态估算
Mask Wearing Status Estimation with Smartwatches
论文作者
论文摘要
我们提出了MaskReminder，这是一种基于智能手表的自动戴面膜状态估计系统，以提醒用户可能接触到Covid-19病毒传输方案，以戴口罩。具有功能强大的MLP混合学习模型的MASKREMINDER可以从惯性测量单元读取中有效地学习长期范围的信息，并可以识别与面具相关的手势，例如戴口罩，降低面膜的金属表带，从而将表带删除，从而从一侧删除表面。此外，MaskReminder能够提醒用户即使在用户无关的设置中，成功率也达到90％。
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.
