PV[O]H: Noninvasive Enabling Technology, New Physiological Monitoring, and Big Data

Measures of normal and abnormal physiology are interrelated and vary continuously. Our ability to detect and predict changes in physiology in real time has been limited in part by the requirement for blood sampling and the lack of a continuous data stream of various "signals", i.e., measurements of vital signs. It is important to determine which signals are most revealing for detection and treatment of, e.g., internal bleeding, managing fluid balance for mission/combat readiness, and hydration. Although our current algorithm for PV[O]H reflects changes in hematocrit and blood and plasma volumes, additional algorithms utilizing the whole raw PV[O]H data stream, along with other variables, can be constructed. We present a working prototype demonstrating that acceptable size, power, and complexity footprints for military needs can be achieved. Results of previous studies involving humans have demonstrated that PV[O]H can provide simultaneous, noninvasive, in vivo continuous monitoring of hematocrit, vascular volume, hemoglobin oxygen saturation, pulse rate, and breathing rate using a single light source with a reporting frequency of every 3 seconds.

We have engineered an instrument implementing the PV[O]H algorithm in which (1) single channel photodetectors replace multichannel detection; (2) optical filters replace gratings; (3) battery power is used; and (4) sufficient computation with input/output capability moderated by application specific graphical user interfaces, and compatible with all cloud, wireless environment, and local protocols is implemented.

We have engineered a complete version of a two-probe PV[O]H system meeting military needs and have fabricated a first version. Testing of subsystems, calibration, and optical characterization of the optical probes are underway.

Simultaneous noninvasive continuous monitoring of peripheral vessels using a previous PV[O]H system demonstrates large, physiology revealing data sets. The technologies enable the methodical search for relevant physiological signals allowing the use of discriminant analysis, Bayesian approaches, and artificial intelligence to create predictive algorithms enabling timely interventions in medical care and troop training.