THz Photonic Crystal Fiber Sensor With High Sensitivity for Distinguishing Malaria Developmental Stages via Refractive Index Contrast and Machine Learning

ABSTRACT Diagnosing malaria necessitates quick and precise recognition of the infection's stage, since the refractive index (RI) of red blood cells varies during the parasite's life cycle. This research introduces a terahertz (Thz) photonic crystal fiber (PCF) sensor intended to identify these refractive index changes that depend on the stage. The sensor, designed with the finite element method in COMSOL Multiphysics, functions in the 1.0–2.5 THz range and exhibits high modal confinement while minimizing confinement and material losses. At 2.5 THz, the structure attains a high relative sensitivity of 99.937% for the Normal stage in y‐polarization, surpassing earlier reported THz PCF sensors. The design additionally demonstrates outstanding power confinement and an appropriate effective mode area. Moreover, the sensor works well with practical manufacturing methods like 3D printing and extrusion. Machine learning analysis further validated the sensor's capability by accurately classifying malaria stages based on the derived PCF optical features. These results suggest that the proposed PCF provides an exceptionally sensitive and practical platform for label‐free identification of malaria stages.