Title:
Quantifying the Effects of Knee Joint Biomechanics on Acoustical Emissions

dc.contributor.advisor Inan, Omer T.
dc.contributor.author Jeong, Hyeon Ki
dc.contributor.committeeMember Young, Aaron
dc.contributor.committeeMember Ayazi, Farrokh
dc.contributor.committeeMember Plötz, Thomas
dc.contributor.committeeMember Millard-Stafford, Melinda
dc.contributor.department Electrical and Computer Engineering
dc.date.accessioned 2021-09-15T15:43:27Z
dc.date.available 2021-09-15T15:43:27Z
dc.date.created 2021-08
dc.date.issued 2021-07-27
dc.date.submitted August 2021
dc.date.updated 2021-09-15T15:43:27Z
dc.description.abstract The knee is one of the most injured body parts, causing 18 million patients to be seen in clinics every year. Because the knee is a weight-bearing joint, it is prone to pathologies such as osteoarthritis and ligamentous injuries. Existing technologies for monitoring knee health can provide accurate assessment and diagnosis for acute injuries. However, they are mainly confined to clinical or laboratory settings only, time-consuming, expensive, and not well-suited for longitudinal monitoring. Developing a novel technology for joint health assessment beyond the clinic can further provide insights on the rehabilitation process and quantitative usage of the knee joint. To better understand the underlying properties and fundamentals of joint sounds, this research will investigate the relationship between the changes in the knee joint structure (i.e. structural damage and joint contact force) and the JAEs while developing novel techniques for analyzing these sounds. We envision that the possibility of quantifying joint structure and joint load usage from these acoustic sensors would advance the potential of JAE as the next biomarker of joint health that can be captured with wearable technology. First, we developed a novel processing technique for JAEs that quantify on the structural change of the knee from injured athletes and human lower-limb cadaver models. Second, we quantified whether JAEs can detect the increase in the mechanical stress on the knee joint using an unsupervised graph mining algorithm. Lastly, we quantified the directional bias of the load distribution between medial and lateral compartment using JAEs. Understanding and monitoring the quantitative usage of knee loads in daily activities can broaden the implications for longitudinal joint health monitoring.
dc.description.degree Ph.D.
dc.format.mimetype application/pdf
dc.identifier.uri http://hdl.handle.net/1853/65076
dc.publisher Georgia Institute of Technology
dc.subject Joint Acoustic Emissions, Signal Processing, Biomechanics
dc.title Quantifying the Effects of Knee Joint Biomechanics on Acoustical Emissions
dc.type Text
dc.type.genre Dissertation
dspace.entity.type Publication
local.contributor.advisor Inan, Omer T.
local.contributor.corporatename School of Electrical and Computer Engineering
local.contributor.corporatename College of Engineering
relation.isAdvisorOfPublication fb82ce90-ad3a-45a6-b0e2-f1ee6fe6f744
relation.isOrgUnitOfPublication 5b7adef2-447c-4270-b9fc-846bd76f80f2
relation.isOrgUnitOfPublication 7c022d60-21d5-497c-b552-95e489a06569
thesis.degree.level Doctoral
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