  Today's diagnostics include devices such as pulse oximeters, blood pressure
monitors, and temperature measurements. These devices provide vital information
to medical personnel when making treatment decisions. Drawing inspiration from
the fundamental utility of pulse oximeters, we present a methodology for a
robust low-cost approach to imaging subsurface vasculature and monitoring heart
rate. The approach uses off-the-shelf equipment, set up in free space without
physical contact and exploits the nature of the interaction between light at
near-infrared wavelengths with tissue. Image processing algorithms extract
heart rate information from the snapshot and video sequence captured at a
stand-off distance. The method can be applied in a room with ambient light and
remains robust to scenarios comparable to medical situations. This research
sets the platform for future diagnostic devices based on imaging systems and
algorithms for non-contact point-of-care investigations.
