@article{ref1,
title="Datasets for recognition of aggressive interactions of children toward robotic toys",
journal="Data in brief",
year="2021",
author="Bonarini, Andrea and Cabibihan, John-John and Alhaddad, Ahmad Yaser",
volume="34",
number="",
pages="e106697-e106697",
abstract="The data is related to unwanted interactions between a person and a small robotic toy based on acceleration sensor embedded within the robotic toy. Three toys were  considered namely, a stuffed panda, a stuffed robot, and an excavator. Each toy was  embedded with an accelerometer to record the interactions. Five different unwanted  interactions were performed by adult participants and children. The considered  interactions were hit, shake, throw, pickup, drop, and idle for the no interaction  case. The collected data contains the magnitude of the resultant acceleration from  the interactions. The data was processed by extracting the instances of  interactions. A secondary dataset was created from the original one by creating  artificial sequences. This data article contains the processed data that can be used  to explore different machine learning models and techniques in classifying such  interactions. Online repository contains the files:  https://doi.org/10.7910/DVN/FHOO0Q.<p /> <p>Language: en</p>",
language="en",
issn="2352-3409",
doi="10.1016/j.dib.2020.106697",
url="http://dx.doi.org/10.1016/j.dib.2020.106697"
}