Pulse and respiration rates provide vital information for evaluating the physiological state of an individual during triage.
Traditionally, pulse and respiration have been tracked by means of contact sensors. Recent work has shown that visible
cameras can passively and remotely obtain pulse signals under controlled environmental conditions    .
This paper introduces methods for extracting and characterizing pulse and respiration signals from skin reflectivity data
captured in peak sensitivity range for silicon detector (400nm-1100nm). Based on the physiological understanding 
  of human skin and reflectivity at various skin depths, we optimize a group of spectral bands to determine pulse
and respiration with high Peak Signal-to-Noise Ratio (PSNR) and correlation values  . Our preliminary results
indicate top six optimal waveband groups in about 100nm - 200nm resolution in each, with rank-ordered peaks at
409nm, 512nm, 584nm, 667nm, 885nm and 772nm. This work, collected under an approved IRB protocol enhances
non-contact, remote, passive, and real-time measurement of pulse and respiration for security and medical applications.