SoDA

Donated on 6/20/2022

Dataset of "Social Distancing Alert with Smartwatches"

Dataset Characteristics

Time-Series

Subject Area

Life Sciences

Associated Tasks

Classification

Attribute Type

-

# Instances

1800

# Attributes

-

Information

For what purpose was the dataset created?

People would violate the social distancing practice unconsciously when they conduct some social activities such as handshaking, hugging, kissing on the face or forehead, etc. For preventing COVID-19 virus transmission, we collected recordings of accelerometers and gyroscopes to recognize activities that may violate social distancing practices.

Who funded the creation of the dataset?

Fei Wang

What do the instances that comprise the dataset represent?

every instance is a time series of different social distancing 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/SoDA

Additional Information

The file name with the format of "I_J_K.mat". I(1 - 10): the I-th subject. J(1 - 18): the J-th action. K(0 - 9): the K-th repetition. Every mat file contains three keys: accData(1, 3, sequence length): A sequence of the accelerometer readings. gyrData (1, 3, sequence length): A sequence of the gyroscope readings. label(1, sequence length): Action labels for each sample point.

Citation Requests/Acknowledgements

@article{wang2022social, title={Social Distancing Alert with Smartwatches}, author={Wang, Xin and Wu, Xilei and Meng, Huina and Fan, Yuhan and Shi, Jingang and Ding, Han and Wang, Fei}, journal={arXiv preprint arXiv:2205.06110}, year={2022} }

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Keywords

covid-19accelerometergyroscope

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

This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.

This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.

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