Mechanical Engineering Commons^™

An Automated, Deep Learning Approach To Systematically & Sequentially Derive Three-Dimensional Knee Kinematics Directly From Two-Dimensional Fluoroscopic Video, Viet Dung Nguyen

Doctoral Dissertations

Total knee arthroplasty (TKA), also known as total knee replacement, is a surgical procedure to replace damaged parts of the knee joint with artificial components. It aims to relieve pain and improve knee function. TKA can improve knee kinematics and reduce pain, but it may also cause altered joint mechanics and complications. Proper patient selection, implant design, and surgical technique are important for successful outcomes. Kinematics analysis plays a vital role in TKA by evaluating knee joint movement and mechanics. It helps assess surgery success, guides implant and technique selection, informs implant design improvements, detects problems early, and improves patient …

Development Of A Soft Robotic Approach For An Intra-Abdominal Wireless Laparoscopic Camera, Hui Liu

Doctoral Dissertations

In Single-Incision Laparoscopic Surgery (SILS), the Magnetic Anchoring and Guidance System (MAGS) arises as a promising technique to provide larger workspaces and field of vision for the laparoscopes, relief space for other instruments, and require fewer incisions. Inspired by MAGS, many concept designs related to fully insertable magnetically driven laparoscopes are developed and tested on the transabdominal operation. However, ignoring the tissue interaction and insertion procedure, most of the designs adopt rigid structures, which not only damage the patients' tissue with excess stress concentration and sliding motion but also require complicated operation for the insertion. Meanwhile, lacking state tracking of …

Environmental Design And Optimization Of Modular Hydropower Plants, Colin Sasthav

Doctoral Dissertations

This research aimed to understand the pathways to cost-effective and sustainable low-head hydropower. Designing viable hydropower projects requires optimization across many economic, environmental, and social outcomes. However, existing run-of-river hydropower design models often focus on economic performance and customizing technologies for high-head diversion schemes. Standard modular hydropower is a new design approach that uses standardized rather than custom-designed technologies to achieve economies of scale. Oak Ridge National Laboratory established a conceptual outline for module classes based on functions, such as generation modules and fish passage modules, but further research was needed to identify how modules should be selected and operated …

Adaptive Kernel Estimation For Enhanced Filtering And Pattern Classification Of Magnetic Resonance Imaging: Novel Techniques For Evaluating The Biomechanics And Pathologic Conditions Of The Lumbar Spine, Nicholas Vincent Battaglia

Doctoral Dissertations

This dissertation investigates the contribution the lumbar spine musculature has on etiological and pathogenic characteristics of low back pain and lumbar spondylosis. This endeavor necessarily required a two-step process: 1) design of an accurate post-processing method for extracting relevant information via magnetic resonance images and 2) determine pathological trends by elucidating high-dimensional datasets through multivariate pattern classification. The lumbar musculature was initially evaluated by post-processing and segmentation of magnetic resonance (MR) images of the lumbar spine, which characteristically suffer from nonlinear corruption of the signal intensity. This so called intensity inhomogeneity degrades the efficacy of traditional intensity-based segmentation algorithms. Proposed …

Dynamic Simulation And Neuromuscular Control Of Movement: Applications For Predictive Simulations Of Balance Recovery, Misagh Mansouri Boroujeni

Doctoral Dissertations

Balance is among the most challenging tasks for patients with movement disorders. Study and treatment of these disorders could greatly benefit from combined software tools that offer better insights into neuromuscular biomechanics, and predictive capabilities for optimal surgical and rehabilitation treatment planning. A platform was created to combine musculoskeletal modeling, closed-loop forward dynamic simulation, optimization techniques, and neuromuscular control system design. Spinal (stretch-reflex) and supraspinal (operational space task-based) controllers were developed to test simulation-based hypotheses related to balance recovery and movement control. A corrective procedure (rectus femoris transfer surgery) was targeted for children experiencing stiff-knee gait and how this procedure …

Modeling, Analysis, And Control Of A Mobile Robot For In Vivo Fluoroscopy Of Human Joints During Natural Movements, Matthew A. Young

Doctoral Dissertations

In this dissertation, the modeling, analysis and control of a multi-degree of freedom (mdof) robotic fluoroscope was investigated. A prototype robotic fluoroscope exists, and consists of a 3 dof mobile platform with two 2 dof Cartesian manipulators mounted symmetrically on opposite sides of the platform. One Cartesian manipulator positions the x-ray generator and the other Cartesian manipulator positions the x-ray imaging device. The robotic fluoroscope is used to x-ray skeletal joints of interest of human subjects performing natural movement activities. In order to collect the data, the Cartesian manipulators must keep the x-ray generation and imaging devices accurately aligned while …

Robust Multichannel Functional-Data-Analysis Methods For Data Recovery In Complex Systems, Jian Sun

Doctoral Dissertations

In recent years, Condition Monitoring (CM), which can be performed via several sensor channels, has been recognized as an effective paradigm for failure prevention of operational equipment or processes. However, the complexity caused by asynchronous data collection with different and/or time-varying sampling/transmission rates has long been a hindrance in the effective use of multichannel data in constructing empirical models. The problem becomes more challenging when sensor readings are incomplete. Traditional sensor data recovery techniques are often prohibited in asynchronous CM environments, not to mention sparse datasets. The proposed Functional Principal Component Analysis (FPCA) methodologies, e.g., nonparametric FPC model and semi-parametric …

In Situ Preconcentration By Ac Electrokinetics For Rapid And Sensitive Nanoparticle Detection, Kai Yang

Doctoral Dissertations

Reducing cost and time is a major concern in clinical diagnostics. Current molecular diagnostics are multi-step processes that usually take at least several hours or even days to complete multiple reagents delivery, incubations and several washing processes. This highly labor-intensive work and lack of automation could result in reduced reliability and low efficiency. The Laboratory-on-a-chip (LOC), taking advantage of the merger and development of microfluidics and biosensor technology, has shown promise towards a solution for performing analytical tests in a self-contained and compact unit, enabling earlier and decentralized testing. However, challenges are to integrate the fluid regulatory elements on a …

An Adaptive Nonparametric Modeling Technique For Expanded Condition Monitoring Of Processes, Matthew John Humberstone

Doctoral Dissertations

New reactor designs and the license extensions of the current reactors has created new condition monitoring challenges. A major challenge is the creation of a data-based model for a reactor that has never been built or operated and has no historical data. This is the motivation behind the creation of a hybrid modeling technique based on first principle models that adapts to include operating reactor data as it becomes available.

An Adaptive Non-Parametric Model (ANPM) was developed for adaptive monitoring of small to medium size reactors (SMR) but would be applicable to all designs. Ideally, an adaptive model should have …