Date of Award
Doctor of Philosophy (PhD)
Big data, Hematocrit, Noninvasive, Physiology, Plasma volume, Raman Spectroscopy
Physical Sciences and Mathematics
This work describes the ongoing analysis of blood noninvasively in vivo along with the in vitro validation of the algorithm. The blood is taken as two components, red blood cells and plasma, both of which cause elastic emission (from Mie and Rayleigh scattering) and inelastic emission (from fluorescence and Raman emission). The algorithm describes the linear dependence of the volume fractions of both red blood cells and plasma with both the elastic and inelastic emissions where the two equations are independent. These equations are used to calculate the Hematocrit which is defined as the volume fraction of red blood cells in the total volume of blood. We believe that monitoring changes in the Hematocrit with sufficient sensitivity could give information about many physiological parameters including an early indication for internal hemorrhaging. The stability of the baseline was analyzed in 10 test subjects across 29 experiments including over 8 million frames of data to give the smallest physiological increment of ±0.033 Hematocrit units. Compared to the medical standard blood draw method, with a standard deviation of ±2.0 Hematocrit units, our device is 60 times more sensitive to changes in the Hematocrit. Repeating patterns in the Hematocrit can be analyzed by a Fourier transform to give respiration rate and pulse rate earning the title of “big data.” Changes in the Hematocrit were also observed in dialysis patients (where the blood is manually cleaned due to kidney failure) and in a rat model where large portions of the blood can be removed and reintroduced. Blood loss and addition of fluid reveal changes in the Hematocrit that are distinguishable from the baseline. The algorithm was validated by a well-defined in vitro system modeling the blood components. The model demonstrates that an optically thin sample in the linear range produces a good fit by the algorithm. Finally, the blood was analyzed in vitro to demonstrate that the red blood cells and plasma show linearity within the physiological ranges observed in vivo. At 830 nm excitation, the same wavelength used in vivo, volume fractions of red blood cells and plasma at the physiological range demonstrate linearity. All of the experiments and analysis appear to give evidence supporting the measuring of changes in the Hematocrit noninvasively in vivo on a medically useful timescale.
Dent, Paul Washington, "Plasma Volume Hematocrit (PVH): “Big Data” Applied to Physiology Enabled by a New Algorithm" (2016). Dissertations - ALL. 664.