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Daniel Whittingslow
Biomedical Engineering PhD Thesis Defense
Date: Tuesday, October 22nd, 2019
Time: 11:00am - 1:00pm
Location: Room 114, CODA Building, Tech Square, Georgia Tech
Address: 756 W Peachtree St NW, Atlanta, GA 30308
Advisor:
Omer T. Inan, PhD
Committee Members:
Rob Butera, PhD
Young-Hui Chang, PhD
Shelly Abramowicz, DMD, MPH, FACS
Sampath Prahalad, MD
Title: Anatomy of a Joint Sound – Using Joint Acoustic Emissions to Diagnose and Grade Musculoskeletal Disease and Injury
Abstract:
Knee injuries and chronic disorders, such as arthritis, affect millions of Americans. Currently, diagnosis of these conditions relies primarily on imaging studies and physical examination by a health care professional. After diagnosis, there are few quantitative technologies available to provide feedback to patients regarding rehabilitation or efficacy of treatments. To address this need, I have developed a device capable of recording and analyzing a joint’s acoustic emissions (AEs). In this work, I developed a human cadaver model of acute knee injury and found a consistent and repeatable variation of the observed AE patterns. This study helped us better understand the underlying anatomical contributors to these AE patterns. I then translated this technology into a clinical study and performed cross-sectional and longitudinal recordings of two groups of patients: a pediatric cohort with juvenile idiopathic arthritis (JIA), and an adult cohort with acute, traumatic injuries. With those patients recorded, I computed features based on their low-level acoustic emission signals. Machine learning algorithms fused those feature sets into an easily interpretable joint health metric for use in clinical diagnosis and decision making.
