Title:  Multi-sensor Signal Processing Methods for Home Monitoring of Cardiovascular and Respiratory Diseases

Committee: 

Dr. Weitnauer, Dr. Inan, Advisors   

Dr. Bhatti, Chair

Dr. Anderson

Abstract: The objectives of the proposed research are to explore signals from existing measurement modalities and look for new sensors for estimation of mechanical parameters of physiological function for home monitoring of cardiovascular and respiratory health. Cardiovascular and respiratory diseases are leading contributors of health problems in the world. Both these systems are functionally intertwined with each other. In this context, over-night data from an under-the-mattress impulse radio ultra-wide band (IR-UWB) radar combined with the signals from microphone sensors will be analyzed using machine learning algorithms to detect sleep apnea, a sleep related respiratory disorder caused by involuntary cessation of breathing during sleep. The objective is to design a non-contact system of sleep apnea monitoring that can be used without the supervision of trained personnel in the home settings. Similarly, for monitoring cardiovascular health, ballistocardiogram (BCG), the measure of reactionary forces of the body as the blood is ejected into the aorta and vessels, is analyzed using a variety of wearable and unobtrusive sensors. The aim is to investigate the physiological origins of the BCG signals and to devise methods for accurate and robust estimation of cardiac health parameters as a person goes through different phases of daily living.