Processing discrete data for deconvolution voltammetry based on the Fourier least-square method Original Research Article

Deconvolution voltammetry is a useful trace elctroanalytical technique. However, it suffers from a number of inherent problems that, inevitably, limit the applicability and scope of the technique. The linear sweep voltammetric curve, while it is not smoothing, cannot be used to operate the deconvolution calculation. By monitoring the voltammetric signal in the digital domain, it is possible to apply the digital signal-processing method to overcome the problems. In this work, a procedure based on the Fourier least-square method (FLSM) is proposed to treat a noise-contaminated signal. It was found that, after careful optimization of the parameters, the smoothed data can be further used to perform deconvolution analysis, and the shape of the processed voltammetric wave is not distorted with an accurate peak position.