Linear filtering and nonlinear fuzzy logic filtering for sample identification with Raman spectroscopy

Raman spectroscopy provides detail information on molecular structure and chemical composition of the samples. It can be used to characterize the normal issue and the malignant tissue for decision-making and medical diagnosis. The goal in this research is to eliminate the noise to an acceptable level. This article is also about some preliminary work of Raman signal processing for sample identification. The whole procedure includes spectrum capturing by Raman spectrometer, spectrum calibration, slowly varying noise filtering using linear least squares estimation, fast varying noise filtering using nonlinear fuzzy control. The long-term objective is to create a real-time approach for sample analysis using a Raman spectrometer directly mounted at the end-effector of the medical robot, which enhances the remote controlled robot strategy.