Date of Award
5-2017
Document Type
Thesis
Degree Name
Master of Science (MS)
Legacy Department
Bioengineering
Committee Member
Dr. David Kwartowitz, Committee Chair
Committee Member
Dr. Charles Thigpen
Committee Member
Dr. Delphine Dean
Abstract
Rotator cuff disease impacts approximately over 50% of the population above the age of 60, causing pain and ultimately possible loss of shoulder function. The rotator cuff is composed of muscles and tendons that work in tandem to support the shoulder and aid in the movement of the arm. History of trauma and increased age can lead to a rotator cuff tear, which can range in severity from a partial-thickness tear to a full-thickness, total rupture. Currently, diagnostic techniques for rotator cuff disease are based on physical assessment, detailed patient history, and medical imaging, primarily X-ray, MRI and ultrasonography. However, limitations still exist regarding rotator cuff diagnosis and monitoring. Ultrasound has been shown to have good accuracy in the identification and measurement of full-thickness and partial-thickness rotator cuff tears. Quantitative data regarding rotator cuff tears is not as readily available as the qualitative data provided by the aforementioned techniques. The device designed through this study improves the method of transduction and the analysis of in situ measurement of rotator cuff biomechanics. Improvements include the ability of the clinician to apply a uniform force to the underlying musculotendentious tissues while simultaneously obtaining an ultrasound image and the addition of Bluetooth for ease of data transfer. Preliminary studies were performed with the device on both post-operative and healthy patients, in which the stress and strain experienced by the rotator cuff tissue was analyzed. This device will ultimately aid in developing a more thorough predictive diagnostic model for the treatment of rotator cuff disease and aid clinicians in choosing the best treatment option for patients.
Recommended Citation
Hall, Brittany Nicole, "Novel device for improved diagnosis and monitoring of rotator cuff injury" (2017). All Theses. 2632.
https://tigerprints.clemson.edu/all_theses/2632