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Ear biometrics for patient identification in global health: a field study to test the effectiveness of an image stabilization device in improving identification accuracy
BACKGROUND: In many low and middle-income countries (LMICs), difficulties in patient identification are a major obstacle to the delivery of longitudinal care. In absence of unique identifiers, biometrics have emerged as an attractive solution to the identification problem. We developed an mHealth Ap...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6580478/ https://www.ncbi.nlm.nih.gov/pubmed/31215427 http://dx.doi.org/10.1186/s12911-019-0833-9 |
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author | Etter, Lauren P. Ragan, Elizabeth J. Campion, Rachael Martinez, David Gill, Christopher J. |
author_facet | Etter, Lauren P. Ragan, Elizabeth J. Campion, Rachael Martinez, David Gill, Christopher J. |
author_sort | Etter, Lauren P. |
collection | PubMed |
description | BACKGROUND: In many low and middle-income countries (LMICs), difficulties in patient identification are a major obstacle to the delivery of longitudinal care. In absence of unique identifiers, biometrics have emerged as an attractive solution to the identification problem. We developed an mHealth App for subject identification using pattern recognition around ear morphology (Project SEARCH (Scanning EARS for Child Health). Early field work with the SEARCH App revealed that image stabilization would be required for optimum performance. METHODS: To improve image capture, we designed and tested a device (the ‘Donut’), which standardizes distance, angle, rotation and lighting. We then ran an experimental trial with 194 participants to measure the impact of the Donut on identification rates. Images of the participant’s left ear were taken both with and without use of the Donut, then processed by the SEARCH algorithm, measuring the top one and top ten most likely matches. RESULTS: With the Donut, the top one identification rate and top ten identification rates were 99.5 and 99.5%, respectively, vs. 38.4 and 24.1%, respectively, without the Donut (P < 0.0001 for each comparison). In sensitivity analyses, crop technique during pre-processing of images had a powerful impact on identification rates, but this too was facilitated through the Donut. CONCLUSIONS: By standardizing lighting, angle and spatial location of the ear, the Donut achieved near perfect identification rates on a cohort of 194 participants, proving the feasibility and effectiveness of using the ear as a biometric identifier. TRIAL REGISTRATION: This study did not include a medical intervention or assess a medical outcome, and therefore did not meet the definition of a human subjects research study as defined by FDAAA. We did not register our study under clinicaltrials.gov. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12911-019-0833-9) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6580478 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-65804782019-06-24 Ear biometrics for patient identification in global health: a field study to test the effectiveness of an image stabilization device in improving identification accuracy Etter, Lauren P. Ragan, Elizabeth J. Campion, Rachael Martinez, David Gill, Christopher J. BMC Med Inform Decis Mak Technical Advance BACKGROUND: In many low and middle-income countries (LMICs), difficulties in patient identification are a major obstacle to the delivery of longitudinal care. In absence of unique identifiers, biometrics have emerged as an attractive solution to the identification problem. We developed an mHealth App for subject identification using pattern recognition around ear morphology (Project SEARCH (Scanning EARS for Child Health). Early field work with the SEARCH App revealed that image stabilization would be required for optimum performance. METHODS: To improve image capture, we designed and tested a device (the ‘Donut’), which standardizes distance, angle, rotation and lighting. We then ran an experimental trial with 194 participants to measure the impact of the Donut on identification rates. Images of the participant’s left ear were taken both with and without use of the Donut, then processed by the SEARCH algorithm, measuring the top one and top ten most likely matches. RESULTS: With the Donut, the top one identification rate and top ten identification rates were 99.5 and 99.5%, respectively, vs. 38.4 and 24.1%, respectively, without the Donut (P < 0.0001 for each comparison). In sensitivity analyses, crop technique during pre-processing of images had a powerful impact on identification rates, but this too was facilitated through the Donut. CONCLUSIONS: By standardizing lighting, angle and spatial location of the ear, the Donut achieved near perfect identification rates on a cohort of 194 participants, proving the feasibility and effectiveness of using the ear as a biometric identifier. TRIAL REGISTRATION: This study did not include a medical intervention or assess a medical outcome, and therefore did not meet the definition of a human subjects research study as defined by FDAAA. We did not register our study under clinicaltrials.gov. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12911-019-0833-9) contains supplementary material, which is available to authorized users. BioMed Central 2019-06-18 /pmc/articles/PMC6580478/ /pubmed/31215427 http://dx.doi.org/10.1186/s12911-019-0833-9 Text en © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Technical Advance Etter, Lauren P. Ragan, Elizabeth J. Campion, Rachael Martinez, David Gill, Christopher J. Ear biometrics for patient identification in global health: a field study to test the effectiveness of an image stabilization device in improving identification accuracy |
title | Ear biometrics for patient identification in global health: a field study to test the effectiveness of an image stabilization device in improving identification accuracy |
title_full | Ear biometrics for patient identification in global health: a field study to test the effectiveness of an image stabilization device in improving identification accuracy |
title_fullStr | Ear biometrics for patient identification in global health: a field study to test the effectiveness of an image stabilization device in improving identification accuracy |
title_full_unstemmed | Ear biometrics for patient identification in global health: a field study to test the effectiveness of an image stabilization device in improving identification accuracy |
title_short | Ear biometrics for patient identification in global health: a field study to test the effectiveness of an image stabilization device in improving identification accuracy |
title_sort | ear biometrics for patient identification in global health: a field study to test the effectiveness of an image stabilization device in improving identification accuracy |
topic | Technical Advance |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6580478/ https://www.ncbi.nlm.nih.gov/pubmed/31215427 http://dx.doi.org/10.1186/s12911-019-0833-9 |
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