Committee: 

Dr. Inan, Advisor 

Dr. Sarioglu, Chair

Dr. Lam

Abstract:

This work proposes the use of wearable acoustic and vibration measurements to derive digital biomarkers, which can be used together with existing medical information to assist in clinical decisions. Acoustic and vibration signals carry information that is in many cases complementary to electrophysiology or movement, but the signals are not fundamentally well understood. This leads to a limited one-to-one correspondence between signal characteristics and important health parameters. To that end, this work aims to investigate this correspondence through signal processing, feature exploration and statistical techniques for deriving more accurate and clinically relevant digital biomarkers. In addition, acoustic and vibration signals exhibit substantial inter-subject and intra-subject variability, thus their use in classical diagnostic approaches have not been successful in the past. Rather than focusing on adapting these signals as diagnostic tools, this work aims to derive and employ new algorithms to detect and track the relative changes in health, e.g. exacerbation in clinical state and/or response to a specific treatment, for a given subject over time.