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Full-Text Articles in Mechanical Engineering

Multi-Classifier Fusion Strategy For Activity And Intent Recognition Of Torso Movements, Abhijit Kadrolkar Nov 2016

Multi-Classifier Fusion Strategy For Activity And Intent Recognition Of Torso Movements, Abhijit Kadrolkar

Doctoral Dissertations

As assistive, wearable robotic devices are being developed to physically assist their users, it has become crucial to develop safe, reliable methods to coordinate the device with the intentions and motions of the wearer. This dissertation investigates the recognition of user intent during flexion and extension of the human torso in the sagittal plane to be used for control of an assistive exoskeleton for the human torso. A multi-sensor intent recognition approach is developed that combines information from surface electromyogram (sEMG) signals from the user’s muscles and inertial sensors mounted on the user’s body. Intent recognition is implemented by following …


Reduced Order Fluid-Structure Interaction Models For Thin Shells With Non-Zero Gaussian Curvatures To Understand The Response Of Aneurysms To Flow, Gary Han Chang Nov 2016

Reduced Order Fluid-Structure Interaction Models For Thin Shells With Non-Zero Gaussian Curvatures To Understand The Response Of Aneurysms To Flow, Gary Han Chang

Doctoral Dissertations

In this thesis, a reduced-order model is constructed to study the physiological flow and wall shear stress conditions for aneurysms. The method of local proper orthogonal decomposition (POD) is used to construct the reduced-order modes using a series of CFD results, which are subsequently improved using a QR-factorization technique to satisfy the various boundary conditions in physiological flow problems. This method can effectively construct a computationally efficient physiological model, which allows us to examine the fluid velocities and wall shear stress distributions over a range of different physiological flow parameters. Aneurysms are the dilation, bulging, or ballooning-out of part of …


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 May 2016

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 …