1. Principle and Classification

At the core of an optical biosensor lies a transduction principle that converts biochemical events at the sensor surface into changes in optical properties. Common readouts include variations in light intensity, wavelength, phase, polarization, lifetime or scattering profile.^[1][2][3] When a target analyte binds to a functionalized surface, it often alters the local refractive index, absorption coefficient or emission characteristics, leading to detectable shifts in resonance wavelength, changes in reflectivity or variations in fluorescence or Raman signal.^[1][3][4]

Several major classes of optical biosensors have been defined based on their transduction mechanisms and device architectures:

Surface plasmon resonance (SPR) biosensors. These exploit collective oscillations of free electrons at a metal–dielectric interface to sense refractive index changes within the evanescent field. Classical prism-coupled SPR and grating-coupled SPR are widely used for quantifying biomolecular interactions, kinetic parameters (association/dissociation rates) and equilibrium affinities, as well as for label-free cell-based assays.^[4][5] Long‑range SPR configurations and nanomaterial-enhanced SPR have been introduced to increase penetration depth and sensitivity.^[4]

Waveguide and interferometric biosensors. Integrated optical waveguides (e.g., Mach–Zehnder interferometers, ring resonators) detect phase or resonance shifts caused by surface binding, enabling compact lab‑on‑chip platforms with high sensitivity and multiplexing capability.^[3][6]

Photonic crystal and microcavity biosensors. Periodic dielectric structures supporting photonic bandgaps confine light in defect cavities; analyte-induced refractive index changes lead to measurable resonance wavelength shifts. Two-dimensional photonic crystal nanocavity and L3‑cavity designs have achieved high quality factors and figures of merit for hemoglobin and brain tissue sensing, underscoring their potential for label-free medical diagnostics.^[7][8][9]

Fiber-optic biosensors. These devices use optical fibers—often tapered, side-polished, or coated—to guide light through or adjacent to sensing regions. Configurations include fiber Bragg gratings, long-period gratings and fiber-based SPR, allowing remote, distributed and in situ measurements in harsh or confined environments.^[10][11]

Fluorescent and luminescent biosensors. These rely on changes in fluorophore intensity, wavelength, lifetime or FRET (Förster resonance energy transfer) efficiency in response to analyte binding or enzymatic activity. They dominate in cellular imaging, multiplex immunoassays and environmental pollutant detection.^[3][12]

Raman and surface-enhanced Raman spectroscopy (SERS) biosensors. By amplifying vibrational signatures of analytes on nanostructured metallic surfaces, SERS biosensors deliver highly specific “molecular fingerprints” for complex sample analysis.^[12]

Hybrid architectures such as photonic crystal–plasmonic nanoantenna biosensors combine multiple mechanisms to exploit the strengths of different optical interactions, and increasingly interface with machine learning algorithms for pattern recognition and biomarker quantification.^[7]

2. Key Performance Parameters

The performance of optical biosensors is commonly assessed using a set of quantitative parameters that describe sensitivity, resolution, selectivity, speed and robustness. Definitions are largely harmonized across recent reviews and device papers.^{[3][4][11][9][10]}

Sensitivity typically denotes the change in output signal per unit change in analyte concentration or refractive index. For refractometric devices, sensitivity is often expressed as resonance wavelength shift (nm) per refractive index unit (RIU). Photonic crystal biosensors designed for blood component recognition report sensitivities in the range of 270–327.2 nm/RIU, coupled with quality factors between 27,122 and 54,377 and figures of merit up to 10,907 RIU⁻¹, illustrating the high performance achievable with carefully engineered bandgap structures.^[9] An L3‑cavity photonic crystal biosensor for brain tissue and other biological samples demonstrates a maximum sensitivity of 450 nm/RIU, a quality factor of 5180 and a figure of merit of 1500 RIU⁻¹.^[10]

The limit of detection (LOD) quantifies the smallest refractive index or concentration change that can be reliably distinguished from noise. For photonic crystal devices, LOD values as low as 9.3 × 10⁻⁶ RIU have been reported for blood component detection, and 6.6 × 10⁻⁵ RIU for brain‑tissue‑range analytes, indicating capability to resolve subtle biochemical variations.^[9][10] SPR biosensors enhanced with nanomaterials similarly achieve low LODs, often in the sub‑nanomolar range for specific proteins or nucleic acids, though exact values depend on assay design, surface chemistry and instrumentation.^[4]

Selectivity reflects the ability to distinguish the target analyte from structurally related species or matrix interferences. This is primarily governed by the biological recognition element (e.g., antibody, aptamer, enzyme) and by surface blocking strategies, but optical design can also contribute by enabling multi-parameter readouts or spectral multiplexing.^[1][2][3][6] Response time covers the interval required for signal to reach steady state after exposure to the analyte; microfluidic integration and optimized mass transport can reduce assay times to minutes while preserving equilibrium binding accuracy.^[5]

Other important metrics include dynamic range (concentration span over which the signal is quantitative), regeneration capability (ability to reuse the same sensor surface after analyte removal), stability (thermal, mechanical and photostability of optical and biofunctional components) and compatibility with complex samples such as blood, serum or food matrices.^{[1][2][3][11][12][9]}

3. Materials and Devices

Optical biosensors integrate functional materials from biochemistry, physical chemistry and nanophotonics into structured devices. At the biochemical interface, recognition elements include enzymes for substrate-specific catalytic sensing, antibodies and antigen-binding fragments for high-affinity immunoassays, nucleic acid probes for hybridization-based detection, and whole cells or tissue slices for cell‑based assays that preserve physiological environments.^[1][2][3][5] Surface chemistries often rely on self-assembled monolayers, polymer brushes or hydrogel matrices to control probe orientation, density and antifouling properties.^[4][5]

Transducer materials are selected to optimize optical confinement, plasmonic response or mechanical flexibility. Classical SPR chips employ noble metals such as gold or silver deposited on glass prisms or planar substrates, while next‑generation plasmonic biosensors incorporate nanostructured films, gratings or nanoantenna arrays to enhance local field intensity and spectral tunability.^[4][7] Silicon and silicon nitride are standard platforms for integrated photonic waveguide and photonic crystal devices due to their mature fabrication, high refractive index contrast and compatibility with CMOS processing.^[8][9][10]

Photonic crystal biosensors for hemoglobin and blood component detection use patterned silicon rods or air holes forming two-dimensional lattices, exploiting TE or TM bandgaps to confine light in defect cavities.^[8][9] Compact footprints on the order of 29–95 μm² have been reported, pointing to integration possibilities within photonic circuits.^[8][10] Fiber-optic biosensors leverage silica or polymer fibers, often modified with metallic coatings or gratings; an optimized photonic crystal fiber SPR biosensor, for example, combines microstructured fiber geometry with a plasmonic layer to achieve enhanced sensitivity for biosensing applications.^[8]

Nanoscale materials play a pivotal role in optical nanosensors, where metal and semiconductor nanoparticles, quantum dots, carbon-based nanostructures and hybrid composites are used to tune fluorescence, plasmonic and Raman responses.^[6][7] These materials enable colorimetric, fluorescence and SERS‑based detection in compact, often portable platforms designed for healthcare, including cancer, neurodegenerative disorders, infections and metabolic diseases.[8] Device architectures span benchtop instruments with microfluidic chips, handheld readers with disposable sensor cartridges, and emerging wearable or implantable formats incorporating optical fibers or flexible waveguides.^[11][12][6]

4. Applications

Optical biosensors have diversified into a broad spectrum of applications across biochemistry, physical chemistry and translational medicine. In clinical diagnostics, SPR, photonic crystal and fluorescence-based biosensors are widely used for detecting disease biomarkers, monitoring therapeutic drug levels and characterizing antibody–antigen interactions.^{[3][4][5][13][9][10]} SPR platforms have become standard tools for quantifying kinetic parameters and affinities in drug discovery, while also supporting cell-based assays that probe signaling events in their native environment.^[5]

Cancer diagnosis represents a prominent application area. Optical biosensors targeting tumor-associated proteins, nucleic acids and circulating tumor cells have been developed for early detection, prognosis and treatment monitoring. A recent overview highlights optical biosensors for cancer diagnosis in contexts such as liquid biopsy, image-guided surgery and intraoperative margin assessment, underscoring the role of label-free refractometric and fluorescence modalities in complementing conventional histopathology and imaging.^[13] Photonic crystal–plasmonic nanoantenna biosensors have been used in conjunction with artificial intelligence for protein biomarker detection, demonstrating how advanced optics and computational analysis can be combined to improve diagnostic accuracy.^[7]

In biomedical monitoring, fiber-optic biosensors measure physiological parameters including temperature, pH, glucose and oxygen, offering remote sensing capabilities in harsh or confined environments. Reviews of optical fiber sensors emphasize their adoption in medicine and biomedicine, including applications in endoscopy, minimally invasive surgery, wearable monitoring and distributed sensing in tissue or organ models.^[11][12]

Environmental applications encompass detection of pollutants, toxins and pathogens in water, air and soil. Fluorescent and SPR biosensors have been applied to monitoring heavy metals, pesticides and emerging contaminants, with recent analyses stressing water pollution sensing as a key growth area for optical biosensors.^[3] In food safety, optical biosensors detect adulterants, spoilage indicators and pathogenic microorganisms, supported by rapid, on-site measurement capabilities.^[1][2][3]

Additional domains include biodefense (detection of biological warfare agents), pharmaceutical analysis and theranostics, where optical nanosensors simultaneously provide diagnostic information and trigger therapy—for example, light-activated drug release or photothermal ablation, integrated with real-time biosensing.^[6]

5. Current Research and Future Perspectives

Research between 2021 and 2026 shows a clear trajectory toward higher sensitivity, deeper integration, and broader deployment of optical biosensors in real-world settings. SPR biosensors remain a focal point, with recent work on nanomaterial-enhanced surfaces, long‑range SPR configurations and multiplexed platforms aimed at lowering LODs and improving robustness.^[4] Comprehensive reviews of SPR-based sensing trace the evolution from simple biomolecular interaction assays to sophisticated cell-based and grating-coupled systems, highlighting emerging opportunities in high-throughput screening and in situ physiological assays.^[4][5]

Fiber-optic sensors have attracted intense interest as essential tools for monitoring physical, chemical and biomedical parameters in harsh environments. A large-scale bibliometric analysis of more than 23,000 publications from 2019–2025 underscores the rapid expansion of optical fiber sensor technologies in medicine and biomedicine, environmental chemistry, civil engineering and aerospace, with particular emphasis on AI- and IoT-integrated sensors and distributed sensing architectures.^[11] A dedicated review of optical fiber sensors in biomedical applications further stresses trends toward miniaturized, wearable and minimally invasive devices tailored for point-of-care diagnostics and continuous health monitoring.^[12]

Nanotechnology continues to reshape the landscape of optical biosensing. Optical nanosensors leveraging organic, inorganic and carbon-based materials have been developed for a wide variety of healthcare applications, including cancer, neurodegenerative disorders, infections, diabetes and cardiovascular diseases. These nanosensors support multi-analyte detection (e.g., pH, oxidative stress markers, cytokines, neurotransmitters) and are increasingly explored as theranostic platforms combining diagnostic feedback with targeted therapy.^[6]

Photonic crystal biosensors represent another rapidly evolving frontier. Designs targeting hemoglobin concentration, blood component profiling, brain tissue characterization, diabetes markers in human tears and breast cancer cells in lymph nodes demonstrate substantial gains in sensitivity, LOD and miniaturization. Researchers have reported thermally stable, ultrasensitive two-dimensional photonic crystal biosensors compatible with photonic integrated circuits, emphasizing their suitability for label-free medical diagnostics and compact lab‑on‑chip systems.^[8][9][10] Hybrid photonic crystal–plasmonic nanoantenna architectures, coupled with AI-based data analysis, point toward intelligent biosensing platforms capable of complex biomarker pattern recognition.^[7]

Looking ahead, key directions identified in recent reviews include: (i) integration of optical biosensors with microfluidics, electronics and wireless communication for fully autonomous point-of-care devices; (ii) standardization and calibration strategies to ensure reproducibility and regulatory acceptance, particularly for clinical applications; (iii) deeper incorporation of machine learning and data-driven approaches for signal processing, multiplexed analyte discrimination and predictive diagnostics; and (iv) exploration of new materials—such as two-dimensional semiconductors and metasurfaces—to achieve unprecedented control over light–matter interactions.^{[3][4][11][6][7]} While challenges remain in terms of large-scale manufacturing, sensor surface stability and translation from laboratory prototypes to commercial products, the convergence of biochemistry, physical chemistry, photonics and data science suggests a robust future for optical biosensors as core components of next-generation analytical and healthcare systems.