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Dataset for Heart Rate as a Predictor of Challenging Behaviours among Children with Autism from Wearable Sensors
- Citation Author(s):
- Submitted by:
- John-John Cabibihan
- Last updated:
- Mon, 07/08/2024 - 15:59
- DOI:
- 10.21227/5b7r-8j60
- Data Format:
- License:
- Categories:
- Keywords:
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.
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.
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