چكيده به لاتين
With the ever-growing global population and the emergence of various diseases, continuous health monitoring, non-invasive medical diagnostics, and accessible healthcare services have become essential for governments. The prevalence and incidence of dementia vary across different regions, largely influenced by the population's age structure. Numerous factors contribute to the onset, development, and progression of this disease. The most significant risk factors include high blood pressure in middle age, obesity in youth, hearing impairment, depression in older age, diabetes, physical inactivity, smoking, and the use of antidepressants. To prevent the progression of dementia and mitigate its substantial costs for both governments and households, effective health monitoring is crucial. In particular, the development of non-invasive sensors capable of on-site disease diagnosis is of growing importance. In this thesis, four portable, wearable solid-state fluorometric microfluidic wearable sensors were developed, each utilizing different mechanisms. These sensors are based on carbon quantum dots (synthesized from para-phenylenediamine) doped with deep eutectic solvent gels (derived from choline chloride, urea, quaternary ammonium salt-modified chitosan, acrylamide, and triethanolamine), stabilized on modified thin-layer chromatography paper. These sensors are designed to detect biomarkers—dopamine, epinephrine, glutamic acid, and glycine—in human sweat for the purpose of monitoring dementia. Key operational variables, such as volume and interaction time, were optimized to achieve optimal performance. The carbon quantum dots' optical, structural, and chemical properties were characterized using a range of methods including FTIR, EDS, TEM, DLS, SEM, HNMR, XRD, UV-Vis, CIE-1931, zeta potential, fluorescence spectroscopy, and electrochemical techniques. A smartphone-integrated, on-site signal recording method enabled the visualization of fluorescence changes before and after the addition of target biomarkers. The sensors exhibited emissions in blue, green, yellow, and red, and successfully detected the biomarkers across linear ranges of 6-300, 1-400, 1-300, and 1-400 µM, with detection limits of 1.76, 0.26, 0.27, and 0.26 µM, and relative standard deviation (RSD) values of 3.21%, 3.87%, 4.31%, and 4.51% for dopamine, epinephrine, glutamic acid, and glycine, respectively. These sensors demonstrated their efficacy in tracking biomarkers in real human sweat samples in laboratory settings. Additionally, the functional performance of these sensors was tested on human subjects using a wearable microfluidic system with PDMS molding, and the results were validated. These findings highlight the potential of wearable microfluidic sweat sensors as cost-effective, multi-diagnostic tools for monitoring human health.
