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A fiber-optic biosensing platform based on ultra-narrowband cladding mode resonances was developed on a high-reflectivity fiber Bragg grating (FBG) for targeting biomolecular detection. The multiple cladding modes with a high sensitivity to the refractive index (RI) were excited in the FBG by coupling between the forward-propagating guided core mode of the multimode fiber and the backward-propagating guided cladding mode of the FBG without any damage to the fiber structure or any change to the standard FBG manufacturing process. The full width at half maximum and the Q-factor of the typical cladding mode resonance operation of the proposed sensor are 80 pm and 19,270, respectively, which are better than those of most fiber-optic biosensors reported to date. In addition, the FBG sensor demonstrated a high sensitivity in protein detection and a high selectivity in serum sample assays. The sensitivity of this sensor was further increased simply by coating it with graphene oxide (GO) sheets on the sensing surface without using a signal amplification strategy. Furthermore, an ultra-low limit of detection (LOD) of 32 pM was obtained by the GO-coated FBG sensor for IgG detection. The proposed FBG sensor provides a competitive fiber-optic platform for biomolecular detection. It has a great potential for applications in label-free biosensing.

In this paper, we demonstrate a fiber-optic surface plasmon resonance (FO-SPR) biosensor based on image processing and back propagation (BP) neural network. The transmitted light of the FO-SPR sensor was captured by using visible (VIS) and near-infrared (NIR) CMOS sensors. The optical information related to the SPR effect was extracted from images based on grayscale conversion and an edge detection algorithm. To achieve accurate monitoring of refractive index (RI) changes, the grayscale means of the VIS and NIR images and the RGB summation of the edge-detected images were used as training and test inputs for the BP neural network. We verified the effectiveness and superiority of this sensing system by experiments on sodium chloride solution identification and protein binding detection. This work is promising for practical applications in standardized biochemical sensing.