Towards Microwave Based Monitoring of Brain Thermo-Fluid Dynamics

About the thesis

The human brain is a central organ whose complex biological processes closely reflect the health and well-being of an individual. The temporal and spatial variations of thermal and hemodynamic states of the brain are of utmost clinical importance for both intensive care patients as well as healthy subjects. Microwave-based techniques are promising for such applications because they provide non-ionizing, non-invasive sensing with low system cost, compact and portable hardware, and tunable tissue penetration capabilities. The primary objective of this thesis is to develop a Machine Learning (ML) powered microwave system for non-invasive thermal and hemodynamic monitoring of the brain. The quantitative and automatic method proposed in this work is based on two-level features extracted from the magnitude and phase response of microwave sensors. The proposed method ensures an automatic, near-real-time operation using a unique Ordered Selection Scheme (OSS).