Biomedical Engineering and Bioengineering Commons^™

Improvement Of Fluorescence-Based Microfluidic Dna Analyzers, Collin Tranter

Doctoral Dissertations

A tremendous effort continues in the development of micro-total-analysis-systems; in support of this, many chemical passivation methods have been developed to enhance the biocompatibility of such microfluidic systems. However, the suitability of these passivation techniques to many fluorescence-based assays still remains inconsistent. This part of this work is focused on the performance of a third generation intercalating DNA dye when used within microfluidic devices treated with a select variety of passivating coatings. The results of these tests indicate that passivation coatings which are intended to shed DNA based on electrostatic repulsion will in fact imbibe the fluorescent DNA intercalating dye …

A High -Order Finite Difference Method For Solving Bioheat Transfer Equations In Three-Dimensional Triple -Layered Skin Structure, Haofeng Yu

Doctoral Dissertations

Investigations on instantaneous skin burns are useful for an accurate assessment of burn-evaluation and for establishing thermal protections for various purposes. Meanwhile, hyperthermia with radiation is important in the treatment of cancer, and it is essential for developers and users of hyperthermia systems to predict, and interpret correctly the biomass thermal and vascular response to heating. In this dissertation, we employ the well-known Pennes' bioheat transfer equation to predict the degree of skin burn and the temperature distribution in hyperthermia cancer treatment.

A fourth-order compact finite difference scheme is developed to solve Pennes' bioheat transfer equation in a three-dimensional single …

Bottom-Up Design Of Artificial Neural Network For Single-Lead Electrocardiogram Beat And Rhythm Classification, Srikanth Thiagarajan

Doctoral Dissertations

Performance improvement in computerized Electrocardiogram (ECG) classification is vital to improve reliability in this life-saving technology. The non-linearly overlapping nature of the ECG classification task prevents the statistical and the syntactic procedures from reaching the maximum performance. A new approach, a neural network-based classification scheme, has been implemented in clinical ECG problems with much success. The focus, however, has been on narrow clinical problem domains and the implementations lacked engineering precision. An optimal utilization of frequency information was missing. This dissertation attempts to improve the accuracy of neural network-based single-lead (lead-II) ECG beat and rhythm classification. A bottom-up approach defined …