Synopsis of recent research by authors named "Xing-Dan Chen"
Xing-dan Chen's research primarily focuses on the application of near-infrared spectroscopy (NIRS) and fluorescence spectral imaging technology for noninvasive biomedical diagnostics and analysis, including the detection of algae, hemoglobin, and glucose levels in the blood.
Chen has developed innovative methods to enhance the sensitivity and accuracy of spectral measurements, such as using empirical mode decomposition to improve signal-to-noise ratios in hemoglobin detection, and optimizing surface plasmon resonance sensors by modifying optical fiber structures.
His studies also explore the quality assessment of food products, exemplified by the use of NIRS for determining quality indicators in beer and analyzing caffeine content in tea polyphenols, indicating a multi-disciplinary approach that bridges health technologies and food science.
