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EgoActive: Integrated Wireless Wearable Sensors for Capturing Infant Egocentric Auditory–Visual Statistics and Autonomic Nervous System Function ‘in the Wild’

Authors :
Elena Geangu
William A. P. Smith
Harry T. Mason
Astrid Priscilla Martinez-Cedillo
David Hunter
Marina I. Knight
Haipeng Liang
Maria del Carmen Garcia de Soria Bazan
Zion Tsz Ho Tse
Thomas Rowland
Dom Corpuz
Josh Hunter
Nishant Singh
Quoc C. Vuong
Mona Ragab Sayed Abdelgayed
David R. Mullineaux
Stephen Smith
Bruce R. Muller
Source :
Sensors, Vol 23, Iss 18, p 7930 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

There have been sustained efforts toward using naturalistic methods in developmental science to measure infant behaviors in the real world from an egocentric perspective because statistical regularities in the environment can shape and be shaped by the developing infant. However, there is no user-friendly and unobtrusive technology to densely and reliably sample life in the wild. To address this gap, we present the design, implementation and validation of the EgoActive platform, which addresses limitations of existing wearable technologies for developmental research. EgoActive records the active infants’ egocentric perspective of the world via a miniature wireless head-mounted camera concurrently with their physiological responses to this input via a lightweight, wireless ECG/acceleration sensor. We also provide software tools to facilitate data analyses. Our validation studies showed that the cameras and body sensors performed well. Families also reported that the platform was comfortable, easy to use and operate, and did not interfere with daily activities. The synchronized multimodal data from the EgoActive platform can help tease apart complex processes that are important for child development to further our understanding of areas ranging from executive function to emotion processing and social learning.

Details

Language :
English
ISSN :
14248220
Volume :
23
Issue :
18
Database :
Directory of Open Access Journals
Journal :
Sensors
Publication Type :
Academic Journal
Accession number :
edsdoj.75812e4686864e2fa50cda1bb18f62f8
Document Type :
article
Full Text :
https://doi.org/10.3390/s23187930