SmartSPR sensor: Machine learning approaches to create intelligent surface plasmon based sensors.

Surface plasmon resonance (SPR) based sensors allow the evaluation of aqueous and gaseous solutions from real-time measurements of molecular interactions. The reliability of the response generated by a SPR sensor must be guaranteed, especially in substance detection, diagnoses, and other routine applications since poorly handled samples, instrumentation noise features, or even molecular tampering manipulations can lead to wrong interpretations. This work investigates the use of different machine learning (ML) techniques to deal with these issues, and aim to improve and attest to the quality of the real-time SPR responses so-called sensorgrams. A new strategy to describe a SPR-sensorgram is shown. The results of the proposed ML-approach allow the creation of intelligent SPR sensors to give a safe, reliable, and auditable analysis of sensorgram responses. Our arrangement can be embedded in an Intelligence Module that can classify sensorgrams and identify the substances presents in it. Also made it possible to order and analyze interest areas of sensorgrams, standardizing data, and supporting eventual audit procedures. With those intelligence features, the new generation of SPR-intelligent biosensors is qualifying to perform automated testing. A properly protocol for Leishmaniasis diagnosis with SPR was used to verify this new feature.

Polymer-based surface plasmon resonance biochip: construction and experimental aspects

Abstract Introduction: Surface plasmon resonance biosensors are high sensitive analytical instruments that normally employ glass materials at the optical substrate layer. However, the use of polymer-based substrates is increasing in the last years due to favorable features, like: disposability, ease to construction and low-cost design. Review Recently, a polymer-based SPR biochip was proposed by using monochromatic and polychromatic input sources. Its construction and experimental considerations are detailed here. Experimental considerations and results, aspects from performance characteristics (resonance parameters, sensitivity and full width at half maximum – FWHM – calculations) are presented for hydrophilic and hydrophobic solutions. It is included also a brief description of the state of the art of polymer-based SPR biosensors.