Doctor of Philosophy / Department of Kinesiology / Carl Ade / During exercise, muscle blood flow (Q ̇m) increases to match metabolic demand of the active skeletal muscle. In order for this matching to take place, ‘competition’ between local vasodilating metabolites and sympathetically mediated vasoconstriction, termed “functional sympatholysis,” must take place. A key feature of functional sympatholysis is that it is driven largely by metabolic rate (i.e., a higher work rates lead to greater sympatholysis), but may also be largely dependent on nitric oxide bioavailability and oxidative stress in certain disease states (e.g., hypertension). Thus, evaluation of these factors may provide valuable insight into the vascular control mechanisms during exercise in both health and disease. Therefore, the purpose of this dissertation was to 1) determine the role metabolic rate and blood flow on mediating functional sympatholysis, 2) determine the role of nitric oxide bioavailability on functional sympatholysis with high salt intake, a risk factor for primary hypertension, and 3) determine the effect of increases in nitric oxide bioavailability on functional sympatholysis in primary hypertension patients. In the first investigation (Chapter 1), we increased the relaxation phase of the contraction-relaxation cycle to increase active skeletal muscle blood flow (Q ̇m) and see if this would impact vasoconstriction of the active skeletal muscle. We showed that a decreased relaxation time led to greater functional sympatholysis. Interestingly, despite a lower metabolic rate (15% and 20% MVC), we showed that there was no difference in vasoconstriction between the increased relaxation times. These results may show that increases in Q ̇m play a role in functional sympatholysis when mechanical compression is minimized. In the second investigation (Chapter 2), we sought to determine if high dietary sodium (HS) intake would impact functional sympatholysis. We showed that HS intake (15g/day for 7 days) did not impact functional sympatholysis during exercise. Importantly, we show a significant increase in mean arterial pressure (i.e., pressor response) during handgrip exercise. These findings show the deleterious changes in blood pressure, but further work is needed to pinpoint specific mechanisms causing the responses. In the final investigation (Chapter 3), we used an acute nitrate rich (NR) supplement to improve NO bioavailability in hypertensive post-menopausal women (PMW), and observe the impact on functional sympatholysis. We provide novel evidence that functional sympatholysis is improved (~50%) with a NR supplement. The finding that a NR supplement can attenuate vasoconstriction in hypertensive PMW sheds light on the complexities of hypertension, functional sympatholysis and NO bioavailability. The current results indicate that the ‘competition’ between vasodilating metabolites and sympathetically mediated vasoconstriction can be independently modified in health and disease. In individuals with impairment to local vasodilation (e.g., hypertension), the ability to increase functional sympatholysis and muscle blood flow may lead to improvements in cardiovascular health. Taken together, the present results suggest that modifying duty cycle, sodium intake, and NO bioavailability are important factors to be considered with regard to overall cardiovascular health.

Magnetic Resonance Imaging (MRI) was used to determine changes in the size of the Inferior Vena Cava (IVC) as a result of blood pooling induced by lower body negative pressure (LBNP). Images of the IVC of supine human subjects (10 males, 10 females) were obtained under four conditions: 1) steady-state 0 mmHg LBNP, 2) steady-state –35 mmHg LBNP, 3) ramping from 0 to –35 mmHg LBNP, 4) ramping from –35 to 0 mmHg LBNP. Volumes for a given IVC segment were obtained under the first two conditions during both end inspiration and end expiration breath-holds. Inferior Vena Cava widths were measured under all four conditions at the levels of portal entry and portal exit. The IVC volume for men and women combined decreased 41% due to LBNP (p andlt; 1.02 x 10-9). The IVC was 64.4% wider at portal exit than at portal entry in men (p andlt; 0.0003). Lower Body Negative Pressure induced a decrease in men's vena cava width up to 46% at portal exit and up to 62% at portal entry. Supported by NASA EPSCoR WKU 522611 and NIH GCRC MO1 RR262.

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Over the last century, physiological signals have been broadly analyzed and processed not only to assess the function of the human physiology, but also to better diagnose illnesses or injuries and provide treatment options for patients. In particular, Electrocardiogram (ECG), blood pressure (BP) and impedance are among the most important biomedical signals processed and analyzed. The majority of studies that utilize these signals attempt to diagnose important irregularities such as arrhythmia or blood loss by processing one of these signals. However, the relationship between them is not yet fully studied using computational methods. Therefore, a system that extract and combine features from all physiological signals representative of states such as arrhythmia and loss of blood volume to predict the presence and the severity of such complications is of paramount importance for care givers. This will not only enhance diagnostic methods, but also enable physicians to make more accurate decisions; thereby the overall quality of care provided to patients will improve significantly. In the first part of the dissertation, analysis and processing of ECG signal to detect the most important waves i.e. P, QRS, and T, are described. A wavelet-based method is implemented to facilitate and enhance the detection process. The method not only provides high detection accuracy, but also efficient in regards to memory and execution time. In addition, the method is robust against noise and baseline drift, as supported by the results. The second part outlines a method that extract features from ECG signal in order to classify and predict the severity of arrhythmia. Arrhythmia can be life-threatening or benign. Several methods exist to detect abnormal heartbeats. However, a clear criterion to identify whether the detected arrhythmia is malignant or benign still an open problem. The method discussed in this dissertation will address a novel solution to this important issue. In the third part, a classification model that predicts the severity of loss of blood volume by incorporating multiple physiological signals is elaborated. The features are extracted in time and frequency domains after transforming the signals with Wavelet Transformation (WT). The results support the desirable reliability and accuracy of the system.