Developing Machine Vision Algorithms to Score MBSImP


This investigation aims to leverage advances in machine vision to develop algorithms that can take in standard videofluoroscopy recordings of swallows and output reliable MBSImP scores. To accomplish this a multi-stage machine vision algorithm has been developed to build machine learning guided by expert knowledge from speech language pathologists. PhD Candidate Principal Investigator: Alex [...]

Diagnostic Validity of Clinical Markers in Detecting Physiologic Swallowing Impairment


The goal of this study is to investigate the diagnostic validity of clinical markers used during clinical swallow evaluations (CSE). Knowing how sensitive and specific our clinical markers are in detecting physiologic swallowing impairment and airway invasion events is an essential step to improve the validity of CSEs, inform targeted treatment planning, reduce unwarranted testing and [...]

RST Temporal Measures


The aim of this study is to determine temporal measures underlying improved swallowing function when initiated during expiration at low to mid-lung volume during quiet breathing. Principal Investigator: Dr. Brittany Krekeler Co-Investigators: Dr. Bonnie Martin-Harris Dr. Cagla Kantarcigil Kate Davidson Kent Armeson