Theses and Dissertations Collection

Vagus nerve stimulation is an emerging therapy that seeks to offset pathological conditions by electrically stimulating the vagus nerve through cuff electrodes, where the electrical pulse is defined by several parameters such as pulse amplitude, pulse width, and pulse frequency. This electroceutical therapy has been approved for treatment resistant depression, and is currently under investigation for heart failure, heart arrhythmia, hypertension, and gastric motility disorders. Recent studies have shown the ability to selectively activate different fibers in the vagus nerve, thus allowing for a highly specific control of physiological behavior through vagal nerve stimulation. One of the major challenges with the application of this therapy involves a closed loop controller to autonomously control the behavioral responses. This problem becomes additionally challenging when multiple locations and multiple stimulation parameters are considered for optimization. Using a physiological model of a rat heart, this thesis investigates a data-driven control scheme for closed-loop control of the rat cardiac system. In the first section of this thesis, a data-driven modeling approach is used to develop a model that maps vagus nerve stimulation parameter selection to the effect on the physiological variables of heart rate and blood pressure. The second part of this thesis develops a controller that uses the data-driven model by utilizing a model predictive control framework to control the heart rate and the blood pressure in closed-loop simulations of a rat model.