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The world of healthcare can be seen as dynamic, often an area where technology and science meet to consummate a greater good for humanity. This relationship has been working well for the last century as evident by the average life expectancy change. For the greater of the last five decades

The world of healthcare can be seen as dynamic, often an area where technology and science meet to consummate a greater good for humanity. This relationship has been working well for the last century as evident by the average life expectancy change. For the greater of the last five decades the average life expectancy at birth increased globally by almost 20 years. In the United States specifically, life expectancy has grown from 50 years in 1900 to 78 years in 2009. That is a 76% increase in just over a century. As great as this increase sounds for humanity it means there are soon to be real issues in the healthcare world. A larger older population will need more healthcare services but have fewer young professionals to provide those services. Technology and science will need to continue to push the boundaries in order to develop and provide the solutions needed to continue providing the aging world population sufficient healthcare. One solution sure to help provide a brighter future for healthcare is mobile health (m-health). M-health can help provide a means for healthcare professionals to treat more patients with less work expenditure and do so with more personalized healthcare advice which will lead to better treatments. This paper discusses one area of m-health devices specifically; human breath analysis devices. The current laboratory methods of breath analysis and why these methods are not adequate for common healthcare practices will be discussed in more detail. Then more specifically, mobile breath analysis devices are discussed. The topic will encompass the challenges that need to be met in developing such devices, possible solutions to these challenges, two real examples of mobile breath analysis devices and finally possible future directions for m-health technologies.
ContributorsLester, Bryan (Author) / Forzani, Erica (Thesis advisor) / Xian, Xiaojun (Committee member) / Trimble, Steve (Committee member) / Arizona State University (Publisher)
Created2012
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The application of novel visualization and modeling methods to the study of cardiovascular disease is vital to the development of innovative diagnostic techniques, including those that may aid in the early detection and prevention of cardiovascular disorders. This dissertation focuses on the application of particle image velocimetry (PIV) to the

The application of novel visualization and modeling methods to the study of cardiovascular disease is vital to the development of innovative diagnostic techniques, including those that may aid in the early detection and prevention of cardiovascular disorders. This dissertation focuses on the application of particle image velocimetry (PIV) to the study of intracardiac hemodynamics. This is accomplished primarily though the use of ultrasound based PIV, which allows for in vivo visualization of intracardiac flow without the requirement for optical access, as is required with traditional camera-based PIV methods.

The fundamentals of ultrasound PIV are introduced, including experimental methods for its implementation as well as a discussion on estimating and mitigating measurement error. Ultrasound PIV is then compared to optical PIV; this is a highly developed technique with proven accuracy; through rigorous examination it has become the “gold standard” of two-dimensional flow visualization. Results show good agreement between the two methods.

Using a mechanical left heart model, a multi-plane ultrasound PIV technique is introduced and applied to quantify a complex, three-dimensional flow that is analogous to the left intraventricular flow. Changes in ventricular flow dynamics due to the rotational orientation of mechanical heart valves are studied; the results demonstrate the importance of multi-plane imaging techniques when trying to assess the strongly three-dimensional intraventricular flow.

The potential use of ultrasound PIV as an early diagnosis technique is demonstrated through the development of a novel elasticity estimation technique. A finite element analysis routine is couple with an ensemble Kalman filter to allow for the estimation of material elasticity using forcing and displacement data derived from PIV. Results demonstrate that it is possible to estimate elasticity using forcing data derived from a PIV vector field, provided vector density is sufficient.
ContributorsWesterdale, John Curtis (Author) / Adrian, Ronald (Thesis advisor) / Belohlavek, Marek (Committee member) / Squires, Kyle (Committee member) / Trimble, Steve (Committee member) / Frakes, David (Committee member) / Arizona State University (Publisher)
Created2015