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Biometric identification of newborns and infants by non-contact fingerprinting: lessons learned
Author(s) -
Steven Saggese,
Yunting Zhao,
Tom Kalisky,
Courtney Avery,
Deborah Förster,
Lilia Edith Duarte-Vera,
Lucila Alejandra Almada-Salazar,
Daniel Perales-Gonzalez,
Alexandra Hubenko,
Michael Kleeman,
Enrique ChacónCruz,
Eliah AronoffSpencer
Publication year - 2019
Publication title -
gates open research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.069
H-Index - 9
ISSN - 2572-4754
DOI - 10.12688/gatesopenres.12914.1
Subject(s) - biometrics , identification (biology) , matching (statistics) , computer science , field (mathematics) , artificial intelligence , medicine , biology , pathology , mathematics , botany , pure mathematics
Despite years of effort, reliable biometric identification of newborns and young children has remained elusive. In this paper, we review the importance of trusted identification methods, the biometric landscape for infants and adults, barriers and success stories, and we discuss specific failure modes particular to young children. We then describe our approach to infant identification using non-contact optical imaging of fingerprints. We detail our technology development history, including Human-Centered Design methods, various iterations of our platform, and how these iterations addressed failure modes in the identification process. We close with a brief description of our clinical trial of newborns and infants at an urban hospital in Mexico and report preliminary results that show high accuracy, with matching rates consistent with acceptable field-performance for reliable biometric identification in large populations.

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