Hyperspectral learning and cyberphysical security for mHealth applications
Our lab’s current research area focuses on physics/biology-informed learning to address large-scale societal health challenges. First, we will share our recent work on hyperspectral learning, which can recover detailed spectral information from photos easily captured using smartphone cameras. A photograph is more than just an image; it contains detailed spectral information. We will discuss representative applications with a focus on hemodynamic parameters and ongoing studies in sub-Saharan Africa, including Kenya and Rwanda. This approach fosters reciprocal innovation, allowing mHealth technologies developed in resource-limited settings to be brought back to the US. Second, we will share our work on biomedical security in response to the FDA’s Drug Supply Chain Security Act. The issue of counterfeit medicines is not new; however, it continues to grow as practices of medication counterfeiting become increasingly advanced, especially during the pandemic. Cyberphysical biomedical security technologies, involving encoding dosage information and authentication into edible biomaterials, can provide serialization, track and trace, and authentication at the dosage level. This empowers patients to play a crucial role in combating counterfeit medicines. In conclusion, data-driven connected mHealth technologies can potentially offer mobility, simplicity, and affordability for rapid and scalable adaptation in resource-limited or at-home settings.
Hosted by Professor KiBum Lee
~Coffee/tea will be served prior to the lecture~