The development of new methods and concepts to visualize massive amounts of data holds the promise to revolutionize the way scientific results are analyzed, especially when tasks such as classification and clustering are involved, as in the case of sensing and biosensing. In this paper we employ a suite of software tools, referred to as PEx-Sensors, through which projection techniques are used to analyze electrical impedance spectroscopy data in electronic tongues and related sensors. The possibility of treating high dimension datasets with PEx-Sensors is advantageous because the whole impedance vs. frequency curves obtained with various sensing units and for a variety of samples can be analyzed at once. It will be shown that non-linear projection techniques such as Sammon's Mapping or IDMAP provide higher distinction ability than linear methods for sensor arrays containing units capable of molecular recognition, apparently because these techniques are able to capture the cooperative response owing to specific interactions between the sensing unit material and the analyte. In addition to allowing for a higher sensitivity and selectivity, the use of PEx-Sensors permits the identification of the major contributors for the distinguishing ability of sensing units and of the optimized frequency range. The latter will be illustrated with sensing units made with layer-by-layer (LbL) films to detect phytic acid, whose capacitance data were visualized with Parallel Coordinates. Significantly, the implementation of PEx-Sensors was conceived so as to handle any type of sensor based on any type of principle of detection, representing therefore a generic platform for treating large amounts of data for sensors and biosensors.

We report on immunosensors to detect D-dimer, a biomarker of venous thromboembolism, which are made with layer-by-layer (LbL) films containing immobilized anti-D-dimer monoclonal antibody alternated with a layer of chitosan/gold nanoparticles (AuNpChi). Detection was due to irreversible adsorption of the antigen D-dimer on its corresponding antibody according to a Langmuir-Freundlich model, thus giving rise to ellipsoidal structures in scanning electron microscopy images whose size and number increased with D-dimer concentration. The chemical groups involved in the adsorption process were inferred from polarization-modulated infrared reflection absorption (PM-IRRAS) through changes in the amide and carbonyl bands. Detection of D-dimer was made with electrical impedance spectroscopy, electrochemical impedance spectroscopy and cyclic voltammetry. The latter was the most sensitive with a detection limit of 9x10^-4μg/mL, sensitivity of 0.27x10-6A/μgmL^-1 with linear increase from 0 to 1μg/mL. The selectivity of the immunosensor made with AuNpChi/anti-D-dimer film was verified by noting negligible changes in the cyclic voltammograms when exposed to typical interferents in biological fluids.