Techniques for signal analysis in surface plasmon resonance sensors

Surface plasmon resonance (SPR) sensing has become an undis-putable and still burgeoning, leading technology in the plasmonics field. The main benefits of SPR are label-free detection and studies of biological binding to the sensor surface. Determination of the SPR location with high accuracy is of major importance for analyzing SPR signals and further improving sensor features such as resolution, sensitivity, and accuracy. The signal analysis and instrumentation requirements of the biosensing of medical diagnostic applications of SPR sensors are more stringent than the requirements of laboratory research. Therefore, the method of determining the relative change in resonance location must be reliable and repeatable. In many ap-plications, it is of great interest to accurately detect and measure the position of an extremum in an optical signal. For example, a correla-tion process produces an output having a peak at a position related to the phase difference of its inputs. In image processing, commu-nications, and digital signal processing, the detection of peaks and their positions is often necessary. This chapter summarizes five methods of processing an SPR signal: the minimum hunt method (MHM), center-of-mass calculation, linear data analysis, locally weighted parametric regression (LWPR), and the novel Radon transform (RT)-based technique.