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Dissertation/Thesis Abstract

The use of edge detection techniques to analyze thoracoabdominal movement and infer breathing volume
by Szurley, Joseph Christopher, M.S., California State University, Long Beach, 2010, 125; 1486712
Abstract (Summary)

A method was proposed using edge detection techniques to extract spatial information of a subject during breathing. Subject airflow was recorded by a differential pressure pneumotach and positional movements were recorded by two digital cameras. An edge detection algorithm was then applied to the recorded videos to analyze thoracoabdominal movement.

The extracted spatial information was then used to formulate models relating to volumetric displacement of the lungs. Models were developed using the symmetries present in the ventral and lateral orientation of the thoracoabdominal cavity to infer breathing volume. The computed volumes were compared to the derived volumes from the airflow measurements of the subject.

The movements in the lateral and ventral direction were found to be an average of 3.8 mm and 9 3 mm respectively along the thoracoabdominal cavity during normal breathing. The calculated lung volumes were found to have a range of 1.3 to 83% difference from the measured lung volumes and were model dependent.

The edge detection techniques proved a viable alternative to fiduciary markers to observe thoracoabdominal movement while being a completely non-invasive system. The volume models used, while not able to accurately compute lung volume, placed an upper and lower limit on the volume change within the lungs during tidal breathing.

Indexing (document details)
Advisor: Druzgalski, Christopher
School: California State University, Long Beach
School Location: United States -- California
Source: MAI 49/02M, Masters Abstracts International
Subjects: Electrical engineering
Publication Number: 1486712
ISBN: 978-1-124-27639-7
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