Geangu, Elena orcid.org/0000-0002-0398-8398, Smith, William Alfred Peter orcid.org/0000-0002-6047-0413, Mason, Harry Thomas orcid.org/0000-0002-3464-7254 et al. (15 more authors) (2023) EgoActive: Integrated wireless wearable sensors for capturing infant egocentric auditory-visual statistics and autonomic nervous system function ‘in the wild’. Sensors. 7930. ISSN 1424-8220
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 multi-modal 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.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2023 by the authors |
Keywords: | infant,multimodal measures,child,wearable sensors,egocentric view,head-mounted camera,ECG,body movement,naturalistic research methods,real-world big data |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Psychology (York) The University of York > Faculty of Sciences (York) > Computer Science (York) The University of York > Faculty of Sciences (York) > Electronic Engineering (York) The University of York > Faculty of Sciences (York) > Mathematics (York) |
Funding Information: | Funder Grant number EPSRC EP/R51181X/1 |
Depositing User: | Pure (York) |
Date Deposited: | 12 Sep 2023 08:40 |
Last Modified: | 15 Feb 2025 00:11 |
Published Version: | https://doi.org/10.3390/s23187930 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.3390/s23187930 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:203234 |