The research presented in this thesis set out to contribute to knowledge seeking to advance the state-of-the-art in laser based, multi-functional, non-invasive diagnostic systems. The results of the work have contributed to the development of methodological generic approaches to the development of devices using light to detect and analyse biomarkers relevant to human health and disease conditions. Following the development of methodologies the research then progresses to examine in-vivo the potential of the integrated spectroscopic technologies to detect changes and rhythms in the micro-vasculature of the skin relevant to the response of the subjects to emotional and physical stress. The results uncover myogenic rhythm synchronisation as a potential marker of adaptive response. The complexity of monitoring and interpreting key biomarkers of metabolism, NADH and FAD and the derived redox ratio is addressed in detail. Analysis of results of around 3,000 functional scans, including tissue oxygen saturation and laser Doppler flowmetry, provides new insights into bio-technological issues. The challenges identified with biological characteristics include sampling zones and physiological features of the skin. Technological, photonics, electronics and computing challenges emerge from the results. These should be considered in advancing the integration of bio-photonic technologies toward realising meaningful diagnostic poly-bio-markers relevant to developing algorithms capable of delivering consistent, reliable and meaningful diagnostic information with utility in clinical practice for early diagnosis of disease conditions such as cancers and cardio-vascular diseases in individuals from the global population. The results have been published in peer-reviewed international journals and presented at major international conferences in the field.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:613572 |
Date | January 2013 |
Creators | Stewart, Neil Andrew |
Contributors | Nabi, Ghulam |
Publisher | University of Dundee |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | https://discovery.dundee.ac.uk/en/studentTheses/ddee58ac-0fda-41ca-9485-c74920cf3852 |
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