You Can Wash Hands Better: Accurate Daily Handwashing Assessment with Smartwatches

Hand hygiene is one of the most efficient daily actions to prevent infectious diseases, such as Influenza, Malaria, and skin infections. We have been suggested to wash our hands under professional guidelines to prevent virus infection. However, several surveys show that very few people follow this suggestion. Thus we propose UWash, a wearable solution with smartwatches, to assess handwashing procedures for the purpose of raising users' awareness and cultivating habits of high-quality handwashing. We address the task of handwashing assessment from readings of motion sensors similar to the action segmentation problem in computer vision, and propose a simple and lightweight two-stream UNet-like network to achieve it effectively. Experiments over 51 subjects show that UWash achieves an accuracy of 92.27% on handwashing gesture recognition, <0.5 seconds error on onset/offset detection, and <5 points error on gesture scoring in the user-dependent setting, and keeps promising in the user-independent evaluation and the user-independent-location-independent evaluation. UWash even performs well on 10 random passersby in a hospital 9 months later. UWash is the first work that scores the handwashing quality by gesture sequences and is instructive to guide users in promoting hand hygiene in daily life. Code and data are avaliable at https://github.com/aiotgroup/UWash