Numerical Analysis of Photonic Crystal Fiber-Based Biosensor for Glucose Level Detection in Urine and Blood

This paper provides a numerical evaluation of a Photonic Crystal Fiber (PCF)-based Surface Plasmon Resonance (SPR) biosensor for detecting different glucose levels in urine and blood. The biosensor is based on Photonic Crystal Fiber (PCF) and uses Surface Plasmon Resonance (SPR). The evaluation is carried out using a simulation tool that employs the finite element method (FEM). The suggested sensor has exceptional performance characteristics and can detect analyte samples externally. The sensor is made from a fundamental square arrangement of Photonic Crystal Fiber (PCF), which is then coated with a thin layer of gold. Six distinct glucose levels in urine and three distinct glucose levels in blood can be detected by the proposed sensor. It exhibits the maximum level of sensitivity to wavelength, with a value of 10909 nm/RIU specifically for detecting glucose concentration 20 gm/dl in urine, and 20000 nm/ RIU for detecting glucose level of 342 mg/dl in blood. Other significant features of the suggested PCF biosensor include the Signal to Noise Ratio, Detection Limit, Sensor Length, Quality Factor, and Detection Accuracy, which are also calculated and presented.