This review summarizes recent advances in sensors based on photonic crystal technologies for biomedical sensing applications. Photonic crystal sensing offers enormous promise due to their clear benefits in sensitivity, stability, compactness, portability. This work discusses several photonic crystal structures, such as photonic crystal waveguides, cavities, and photonic crystal fiber for biomedical sensing applications. The uniqueness, measurement technique, and biosensing properties of each type of these structures are discussed. Furthermore, manufacturing and functionally relevant properties that include design simplicity, compactness, and multi-wavelength operation are also reviewed. They are explored, organized, and compared using the most recent related literature in this field. Finally, a brief of novel trends has been introduced.

Tuberculosis is one of the most contagious and lethal illnesses in the world, according to the World Health Organization. Tuberculosis had the leading mortality rate as a result of a single infection, ranking above HIV/AIDS. Early detection is an essential factor in patient treatment and can improve the survival rate. Detection methods should have high mobility, high accuracy, fast detection, and low losses. This work presents a novel biomedical photonic crystal fiber sensor, which can accurately detect and distinguish between the different types of tuberculosis bacteria. The designed sensor detects these types with high relative sensitivity and negligible losses compared to other photonic crystal fiber-based biomedical sensors. The proposed sensor exhibits a relative sensitivity of 90.6%, an effective area of 4.342×10 ⁻⁸ m ² , with a negligible confinement loss of 3.13×10 ⁻⁹ cm ⁻¹ , a remarkably low effective material loss of 0.0132cm ⁻¹ , and a numerical aperture of 0.3462. The proposed sensor is capable of operating in the terahertz regimes over a wide range (1 THz–2.4THz). An abbreviated review of non-optical detection techniques is also presented. An in-depth comparison between this work and recent related photonic crystal fiber-based literature is drawn to validate the efficacy and authenticity of the proposed design.

Chikungunya virus (CHIKV) poses a significant public health threat due to its capacity to cause widespread and debilitating outbreaks. The virus is responsible for CHIKV fever, a disease characterized by severe joint pain, sudden onset of fever, headache, muscle pain, and rash. The virus has been reported in various regions globally, with outbreaks occurring in parts of Africa, Asia, the Americas, and the Indian subcontinent. Consequently, the scientific community expends substantial efforts in developing dependable, rapid, highly sensitive, and cost-effective techniques in order to identify the CHIKV virus. In this study, an innovative biomedical sensor using photonic crystal fiber technology enables precise detection of the CHIKV virus through uric acid, normal and infected plasma, red blood cells, and platelets in the blood. The introduced sensor identifies those kinds with extremely increased relative sensitivity and minimal losses in contrast to alternative photonic crystal fiber-based biosensors. The introduced sensor showcases a minimal confinement loss of 2.25 × 10^− 13 cm^− 1, a relative sensitivity of 99.37%, an effective area of 1.36 × 10⁵ µm², with a minimal effective material loss of 0.001966 cm^–1, a numerical aperture of 0.1874, and low dispersion of 0.06. Also, the demonstrated sensor is able to function within the terahertz spectrum, covering a substantial span from 0.8 to 2.6 THz. Furthermore, an extensive comparison analysis is performed between the showcased sensor and related literature on photonic crystal fibers to verify the reliability and effectiveness of the introduced structure.

Cancer remains one of the most critical global health challenges, where early detection significantly improves treatment outcomes and survival rates. This study presents a two-dimensional photonic crystal-based nanocavity sensor designed for the high-precision differentiation of six distinct cancer types from normal cases. The sensor leverages advanced optical signal processing through a carefully optimized nanocavity structure, enabling enhanced light confinement and analyte interaction. The results demonstrate that the sensor achieves exceptional refractive index sensitivity and ultra-low detection limits, making it highly effective for detecting biomolecular variations associated with malignancies. The methodologies employed include rigorous simulations to optimize the sensor’s structural parameters, such as the rod radius, lattice constant, and sample rod dimensions, to enhance performance metrics like the quality factor, sensitivity, detection limit, and figure of merit. The results demonstrate that the proposed sensor achieves exceptional performance, with a sensitivity of 457.1 nm/RIU, a maximal figure of merit of 22,856.7 RIU⁻¹, and a quality factor of 54,669. Additionally, the sensor exhibits a minimal detection limit of 4.3 × 10⁻⁶ RIU, showcasing its ability to identify various cancer types with high accuracy. Its compact design and compatibility with on-chip integration facilitate practical implementation in biomarker detection and early cancer diagnostics. A comparative analysis with existing photonic-based detection technologies underscores the originality and superior performance of the proposed sensor, positioning it as a promising platform for non-invasive, real-time cancer screening.