Press Release

Global Good and Element Inc. to Develop Biometric Identification Technology for Infants and Children

October 31, 2017 New York and Bellevue, Washington

Powered by deep learning algorithms, a modern form of artificial intelligence, that use existing cameras on mobile devices, the biometric application could—for the first time—enable health systems to recognize and follow patients from birth to old age.

Leading biometric software company Element Inc. announced its partnership with the Global Good Fund to develop a smartphone-based, non-touch biometric platform capable of using infants’ and children’s unique biological characteristics to identify them.

Globally, nearly one in four children under the age of five are not registered at birth and lack formal identification. Drawing on the global health expertise of Global Good, the partnership will extend Element’s existing adult identity platform to this age group, enabling health systems to recognize and track health information of patients from birth through adulthood.

“Expanding Element’s cutting-edge biometric methods to infants and children could transform the way clinicians and their patients manage health delivery records,” said Maurizio Vecchione, Executive Vice President of Global Good & Research. “Not only would it improve the level of care we provide to the world’s most vulnerable patients, it could also lay a basis for the promised digital revolution in clinical management.”

“Accurately identifying patients, and linking them to their electronic medical records—which store past medical conditions, drug allergy information, medications and vaccination history—is critical to health care,” said Dr. David Bell, Director of the Global Health Technologies supporting Global Good. “While adult biometrics are widely used in financial services, these have not been translated to the health sector where the need to identify a person from birth to old age presents additional challenges; namely, that infants have delicate, rapidly changing features that are difficult to capture.”

Element’s platform is powered by the advances in deep learning algorithm development it helped pioneer as one of the first mobile deep learning-focused software companies. Element’s adult solutions for palm and face recognition are capable of biometric recognition of very large user bases local to a device, without wireless connectivity, a critical capability for some of the world’s largest populations.

“At Element, we aim to deliver identity to the billions who need it. The opportunity to meet people where they are, across the nearly three billion smartphones in the world today, is particularly profound, and can change models of service delivery,” said Adam Perold, co-founder and CEO of Element. “In the dozens of countries our partners operate in, mobile software-based digital identity has the power to be transformative, providing greater access to key health and financial resources. With Global Good, we’re excited to apply this commercial solution to people at the earliest stages of life, addressing an unsolved identity problem with broad implications for healthcare delivery.”

“Deep learning is uniquely suited to address the challenges of capturing infant biometrics,” said Yann LeCun, Director of AI Research at Facebook, Professor at NYU and co-founder of Element. “These algorithms allow the platform to learn directly from the natural features of infants, can understand changes over time, and can be applied to multiple biometrics at once. This creates a more robust method of identity recognition, and is something existing technologies simply can’t do.”

With the Matlab Health Research Centre of the icddr,b in Bangladesh and the Angkor Hospital for Children in Cambodia, the partnership will assess a range of biometric modalities—fingerprints, irises, palmprints, ears and feet—to determine which is most suitable for infants and young children.

A video of the initiative may be downloaded here.

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