This book offers a tissue-parameterized framework for reading biomedical optical biosensor outputs, one that refuses to treat signal as direct biological truth whenever the sensing volume includes cells, extracellular matrix, blood-rich media, tissue interfaces, or other heterogeneous structures. Instead, it ties device response to refractive-index contrast, absorption, scattering, anisotropy, sampling geometry, calibration, uncertainty, validation level, and intended use, the variables that actually sit between a photon and a diagnosis. The coverage spans SPR/LSPR and plasmonic biosensors, fiber-optic biosensors, Raman/SERS, fluorescence, FRET and luminescence, OCT/OCE, photoacoustic and photothermal sensing, and multimodal data fusion. What unifies these otherwise disparate modalities is a shared vocabulary for separating detected signals from processed features, calibrated estimates from biological associations, predictive signatures from candidate biomarkers, and externally validated models from clinically actionable tools. These distinctions sound bureaucratic until you realize how often they collapse in practice.

The book's real contribution isn't another survey of optical devices, plenty of those exist already. It's a claim-boundary framework: a way of asking, rigorously, what a given optical measurement can support and where that support runs out. For biomedical engineers, biophysicists, optical sensing researchers, graduate students, and reviewers working across biomedical photonics, tissue optics, and AI-enabled multimodal sensing, that question is the one that matters most.

Dr. Nasrettin Yunus works at the intersection of biophysics, electrical-electronics engineering, biomedical signal processing, psychophysiology, and optical biosensing. He completed his doctoral training in biophysics at Ege University. From there his research moved into biomedical optics, physiological signal analysis, optical scattering, tissue polarimetry, and computational sensor modeling. His recent work focuses on tissue-parameterized interpretation of optical biosensor outputs, including refractive-index contrast, scatterer morphology, orientation dispersion, and validation-aware reporting of biomedical sensor claims. He has also worked on HRV/EDA-based psychophysiological measurement, real-time biosignal analysis, and applied computational modeling.