EAGER: SaTC: Sweaty Digits: Bridging Chemistry and AI-Empowered Imaging for Secure and Trustworthy Human Identity Verification

Compared to current biometric technologies, sweat can better represent human identity with more discerning characteristics, overcoming limitations of existing systems such as demographic differentials (e.g., lower accuracy in women) and vulnerability to spoof attacks. This research aims to define human identity through richer signals, not only spatial features but also associated chemical content, captured by a hyperspectral imager without the use of reagents. This proposal aims to create a new representation of human identity based on the analysis of sweat through hyperspectral imaging (HSI), which enables further research to explore sweat as a solution for efficient, accurate, and secure biometric human identity verification. Sweat can provide a meticulous perspective on identity by incorporating chemical properties of a biometric trait. By focusing on an HSI perspective of sweat as biometric modality, this project builds a deeper profile of the identity makes the link between the genuine person and the digital representation stronger and, subsequently, the system processing it less prone to errors and more resilient to spoofing. The project's broader significance and importance is to bridge advances in chemical sweat analysis to imaging that builds foundations for reasoning on HSI learning techniques applied to sweat. The project’s novelties include creating profiles of sweat metabolites using HSI, thereby creating a digital human identity based on sweat. To accomplish this objective, this project focuses on confirming that metabolites can be extracted from sweat excreted from human fingertips, confirming their reproducibility, and creating an HSI reference for each metabolite of interest. Due to diversity in the sensing approach, spectral references obtained through traditional spectroscopy for sweat metabolites cannot be used as HSI reference. The research investigates important aspects such as how to acquire appropriate sweat samples and whether the deposited sample and the capture process are repeatable - with the application of HSI. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.