Cardiovascular disease is responsible for the majority of morbidity and mortality in the United States. Physiologically healthy flow rarely displays turbulent behavior, thereby maintaining normal shear levels. The presence of vortical flow structures, however, alters the hemodynamical characteristics within the system, which has significant effect upon shear stress (SS) and wall shear stress (WSS) levels, as well as particle residence times. The relationship between these hemodynamic parameters and vascular injury response is of great relevance to understanding the cardiovascular disease process.

In this work, new methods and algorithms are developed and presented for resolving, both globally and locally, the spatial and temporal variations of shear stress (SS) and WSS for in vitro models of the human cardiovascular system. Advancements in global measurements are based on improving the accuracy of SS and WSS estimation from time-resolved Digital Particle Image Velocimetry (DPIV) velocity measurements. A new velocity derivative method, the fourth-order noise-optimized compact-Richardson implicit scheme, has been developed, overcoming the obstacle of minimizing both the bias and random error in temporal/spatial derivative estimations. The resulting error is on the same order as the velocity measurement error for global measurements which results in an order of magnitude accuracy improvement. The method has been extended to WSS measurements, and combined with a new method of mirroring/reflecting a flow field over its boundary in order to achieve higher-order estimation. For moving boundaries an edge detection cross-correlation algorithm has been developed and characterized, yielding sub-pixel accuracy in measuring dynamic wall position prior to estimating WSS. An original microelectromechanical system (MEMS) WSS sensor capable of delivering high sensitivity, frequency response and accurate WSS measurements has been developed and characterized in this work.