SoDA
Donated on 6/19/2022
Dataset of "Social Distancing Alert with Smartwatches"
Dataset Characteristics
Time-Series
Subject Area
Health and Medicine
Associated Tasks
Classification
Feature Type
-
# Instances
1800
# Features
-
Dataset 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 in this 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.
Has Missing Values?
No
Introductory Paper
By Xin Wang, Xilei Wu, Huina Meng, Yu Fan, Jing Shi, Han Ding, Fei Wang. 2022
Published in ArXiv
Reviews
There are no reviews for this dataset yet.
pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset soda = fetch_ucirepo(id=742) # data (as pandas dataframes) X = soda.data.features y = soda.data.targets # metadata print(soda.metadata) # variable information print(soda.variables)
Wang,Xin, Meng,Huina, Wang,Fei, and Wu,Xilei. (2022). SoDA. UCI Machine Learning Repository. https://doi.org/10.24432/C5T31R.
@misc{misc_soda_742,
author = {Wang,Xin, Meng,Huina, Wang,Fei, and Wu,Xilei},
title = {{SoDA}},
year = {2022},
howpublished = {UCI Machine Learning Repository},
note = {{DOI}: https://doi.org/10.24432/C5T31R}
}Keywords
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
DOI
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.