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Dataset for Heart Rate as a Predictor of Challenging Behaviours among Children with Autism from Wearable Sensors

Citation Author(s):
Ahmad Qadeib Alban
Ahmad Yaser Alhaddad
Abdulaziz Al-Ali
Wing Chee So
Olcay Connor
Malek Ayesh
Uvais Ahmed Qidwai
John-John Cabibihan
Submitted by:
John-John Cabibihan
Last updated:
DOI:
10.21227/5b7r-8j60
Data Format:
Average: 5 (1 vote)

Abstract

The dataset contains physiological data collected using a wearable device from 5 children with autism (all males) during interaction sessions with different stimuli. The dataset (QU_Autism_dataset.csv) is related to our investigations of using wearable devices to detect the occurrence of challenging behaviors among children with autism. The study used a wearable device that acquired the acceleration (ACC) (i.e., in X, Y, Z), electrodermal activity (EDA), temperature (TEMP), heart rate (HR), and blood volume pulse (BVP). The recorded sessions were annotated using two labels, namely Non-Challenging and Challenging. The index column identifies the participating child’s number. More details can be found with the related article. Note: The DOI/ link of the related publication will be updated once available.

Instructions:

The dataset columns include the acceleration (ACC) (i.e., in X, Y, Z), electrodermal activity (EDA), temperature (TEMP), heart rate (HR), blood volume pulse (BVP), the labels (i.e., Non-Challenging and Challenging), and the index to identify the child’s number.