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Full-Text Articles in Engineering
Development Of A Dual-Mode Cmos Microelectrode Array For The Simultaneous Study Of Electrochemical And Electrophysiological Activities Of The Brain, Geoffrey Mulberry
Development Of A Dual-Mode Cmos Microelectrode Array For The Simultaneous Study Of Electrochemical And Electrophysiological Activities Of The Brain, Geoffrey Mulberry
Electronic Theses and Dissertations, 2020-
Medical diagnostic devices are in high demand due to increasing cases of neurodegenerative diseases in the aging population and pandemic outbreaks in our increasingly connected global community. Devices capable of detecting the presence of a disease in its early stages can have dramatic impacts on how it can be treated or eliminated. High cost and limited accessibility to diagnostic tools are the main barriers preventing potential patients from receiving a timely disease diagnosis. This dissertation presents several devices that are aimed at providing higher quality medical diagnostics at a low cost. Brain function is commonly studied with systems detecting the …
Mos2 Based Memristive Synapses For Neuromorphic Computing, Adithi Pandrahal Krishnaprasad Sharada
Mos2 Based Memristive Synapses For Neuromorphic Computing, Adithi Pandrahal Krishnaprasad Sharada
Electronic Theses and Dissertations, 2020-
Brain inspired computing enabled by memristors have gained prominence over the years due to its nano-scale footprint, reduced complexity for implementing synapses and neurons. Several demonstrations show two-dimensional (2D) materials as a promising platform for realization of robust and energy-efficient memristive synapses. Ideally, a synapse should exhibit low cycle-to-cycle (C-C) and device-to-device (D-D) variability along with high maximum /minimum conductance (Gmax/Gmin) ratio, linearity and symmetry in weight update for obtaining high learning accuracy in neural networks (NNs). However, the demonstration of neuromorphic circuits using conventional materials systems has been limited by high C-C and D-D variability and non-linearity in the …
Novel Computational Approaches For Multidimensional Brain Image Analysis, Harish Raviprakash
Novel Computational Approaches For Multidimensional Brain Image Analysis, Harish Raviprakash
Electronic Theses and Dissertations, 2020-
The overall goal of this dissertation is focused on addressing challenging problems in 1D, 2D/3D and 4D neuroimaging by developing novel algorithms that combine signal processing and machine learning techniques. One of these challenging tasks is the accurate localization of the eloquent language cortex in brain resection pre-surgery patients. This is especially important since inaccurate localization can lead to diminshed functionalities and thus, a poor quality of life for the patient. The first part of this dissertation addresses this problem in the case of drug-resistant epileptic patients. We propose a novel machine learning based algorithm to establish an alternate electrical …
Characterization Of Left Ventricular Volumes And Ejection Fraction In Patients With A Left Ventricular Assist Device, Viswajith Siruvallur Vasudevan
Characterization Of Left Ventricular Volumes And Ejection Fraction In Patients With A Left Ventricular Assist Device, Viswajith Siruvallur Vasudevan
Electronic Theses and Dissertations, 2020-
In the treatment of heart patients, as a bridge to recovery, the challenge currently in using a continuous-flow left ventricular assist device (LVAD), is to provide a method to monitor the recovery of the heart. This dissertation addresses the hypothesis that continuous monitoring of the ejection fraction of a patient implanted with an LVAD should be to examine the progress of the patient without the need for excessive in vivo measurements. Also, the ejection fraction can be used to provide a control mechanism for the pump depending on the requirements of each patient. In this dissertation, the left ventricle, in …