MaskReminder

Donated on 6/19/2022

Dataset of "Mask Wearing Status Estimation with Smartwatches"

Dataset Characteristics

Time-Series

Subject Area

Health and Medicine

Associated Tasks

Classification

Feature Type

-

# Instances

7600

# Features

-

Dataset Information

For what purpose was the dataset created?

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.

Who funded the creation of the dataset?

Fei Wang

What do the instances in this dataset represent?

every instance is a time series of different mask-related hand movements actions

Are there recommended data splits?

based on different needs, can split data into training-set/validation-set/testing-set

Was there any data preprocessing performed?

please reference https://github.com/aiotgroup/MaskReminder

Additional Information

18 actions are divided into three categories: Wearing a mask: Wear The Mask; Mask-wearing related actions: Adjust The Mask, Pull On The Mask, Pull Down The Mask, Pull On One Rope, Pull Down One Rope; Actions that may mislead mask-wearing status estimation: Remove The Mask, Rubbing Eyes, Rubbing The Nose, Rubbing The Hair, Put On A Hat, Take Off The Hat, Put On The Earphones, Take Off The Earphones, Wear Glasses, Push The Glasses, Take Off The Glasses, Wiping Mouth;

Has Missing Values?

No

Introductory Paper

Mask Wearing Status Estimation with Smartwatches

By Huina Meng, Xilei Wu, Xin Wang, Yu Fan, Jingang Shi, Han Ding, Fei Wang. 2022

Published in ArXiv

Dataset Files

FileSize
MaskReminder.zip19.4 MB
diversity.png30.3 KB

Reviews

There are no reviews for this dataset yet.

Login to Write a Review
Download (19.4 MB)
1 citations
2891 views

Creators

Xin Wang

xwang6@stu.xjtu.edu.cn

XJTU

Huina Meng

menghuina@stu.xjtu.edu.cn

XJTU

Fei Wang

feynmanw@xjtu.edu.cn

XJTU

Xilei Wu

xlwuuu@stu.xjtu.edu.cn

License

By using the UCI Machine Learning Repository, you acknowledge and accept the cookies and privacy practices used by the UCI Machine Learning Repository.

Read Policy