Ear biometrics for patient identification in global health: a cross-sectional study to test the feasibility of a simplified algorithm.
BACKGROUND
One of the greatest public health challenges in low- and middle-income countries (LMICs) is identifying people over time and space. Recent years have seen an explosion of interest in developing electronic approaches to addressing this problem, with mobile technology at the forefront of these efforts. We investigate the possibility of biometrics as a simple, cost-efficient, and portable solution. Common biometrics approaches include fingerprinting, iris scanning and facial recognition, but all are less than ideal due to complexity, infringement on privacy, cost, or portability. Ear biometrics, however, proved to be a unique and viable solution.


METHODS
We developed an identification algorithm then conducted a cross sectional study in which we photographed left and right ears from 25 consenting adults. We then conducted re-identification and statistical analyses to identify the accuracy and replicability of our approach.


RESULTS
Through principal component analysis, we found the curve of the ear helix to be the most reliable anatomical structure and the basis for re-identification. Although an individual ear allowed for high re-identification rate (88.3%), when both left and right ears were paired together, our rate of re-identification amidst the pool of potential matches was 100%.


CONCLUSIONS
The results of this study have implications on future efforts towards building a biometrics solution for patient identification in LMICs. We provide a conceptual platform for further investigation into the development of an ear biometrics identification mobile application.
Department of Global Health, Boston University School of Public Health, Boston, MA, USA.|Center for Global Health and Development, Boston University School of Public Health, Boston, MA, USA.
Elizabeth J
EJ
Ragan
Department of Global Health, Boston University School of Public Health, Boston, MA, USA.
Courtney
C
Johnson
Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
Jacqueline N
JN
Milton
Department of Global Health, Boston University School of Public Health, Boston, MA, USA. cgill@bu.edu.|Center for Global Health and Development, Boston University School of Public Health, Boston, MA, USA. cgill@bu.edu.
Christopher J
CJ
Gill
D000328:Adult; D000368:Aged; D000465:Algorithms; D056667:Biometric Identification / Q000379:methods*; D044383:Black People; D003430:Cross-Sectional Studies; D003906:Developing Countries; D004423:Ear / Q000033:anatomy & histology*; D014943:Global Health; D006801:Humans; D008875:Middle Aged; D010355:Patient Identification Systems / Q000379:methods*; D025341:Principal Component Analysis; D044465:White People