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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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Title: Novel Methods using Acoustics and Bioimpedance to Assess Musculoskeletal Health and Performance
Committee:
Dr. Omer Inan, ECE, Chair, Advisor
Dr. Farrokh Ayazi, ECE
Dr. Alper Erturk, ME
Dr. Gregory Sawicki, ME
Dr. Sampath Prahalad, Emory
Abstract: One in every five people in the world has a musculoskeletal condition. Unfortunately, assessment of musculoskeletal conditions requires either unaffordable and inconvenient benchtop systems or a health professional present for qualitative examinations. Recent advancements in wearable and mobile sensing technologies have ushered in the era of digital health data collection. The availability of advanced computational tools has enabled the burgeoning of digital biomarkers from wearable devices as quantitative markers of physiology. Wearable technologies could be utilized as non-invasive, objective, and affordable musculoskeletal health assessment tools. With these technologies, the number of clinical visits can be greatly reduced, which would lessen the economic and social burden on society. Importantly, wearable technologies could enable at-home musculoskeletal health monitoring to facilitate preventative medicine and successful recovery following injuries. In this dissertation, we demonstrate the utility of wearable acoustics and bioimpedance sensing for non-invasive, affordable, and convenient assessment of musckloskeletal health and performance. Importantly, the findings of this research have important implications for meaningful interpretation of “digital biomarkers” of musculoskeletal health. We anticipate this research will help inform the development of next generation wearable technologies for musculoskeletal health assessment. The tools and insights presented here may enable the use of the state-of-the-art wearable technologies in fully unsupervised at-home settings.
