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Open video data sharing in developmental science and clinical practice

Authors :
Peter B. Marschik
Tomas Kulvicius
Sarah Flügge
Claudius Widmann
Karin Nielsen-Saines
Martin Schulte-Rüther
Britta Hüning
Sven Bölte
Luise Poustka
Jeff Sigafoos
Florentin Wörgötter
Christa Einspieler
Dajie Zhang
Source :
iScience, Vol 26, Iss 4, Pp 106348- (2023)
Publication Year :
2023
Publisher :
Elsevier, 2023.

Abstract

Summary: In behavioral research and clinical practice video data has rarely been shared or pooled across sites due to ethical concerns of confidentiality, although the need of shared large-scaled datasets remains increasing. This demand is even more imperative when data-heavy computer-based approaches are involved. To share data while abiding by privacy protection rules, a critical question arises whether efforts at data de-identification reduce data utility? We addressed this question by showcasing an established and video-based diagnostic tool for detecting neurological deficits. We demonstrated for the first time that, for analyzing infant neuromotor functions, pseudonymization by face-blurring video recordings is a viable approach. The redaction did not affect classification accuracy for either human assessors or artificial intelligence methods, suggesting an adequate and easy-to-apply solution for sharing behavioral video data. Our work shall encourage more innovative solutions to share and merge stand-alone video datasets into large data pools to advance science and public health.

Details

Language :
English
ISSN :
25890042
Volume :
26
Issue :
4
Database :
Directory of Open Access Journals
Journal :
iScience
Publication Type :
Academic Journal
Accession number :
edsdoj.1ac9f20db2774ece9d554ad0977ebf2b
Document Type :
article
Full Text :
https://doi.org/10.1016/j.isci.2023.106348