FPGA-based approach for automatic peak detection in cyclic voltammetry

An adequate drug dosage is often difficult to be achieved in personalized medicine. Especially for critical application, such as anesthesia. To reach the right dose adjustment, electrochemical biosensors can be used to measure the actual concentration of the drug in the patient's blood. Normall...

Full description

Saved in:
Bibliographic Details
Published in2016 IEEE International Conference on Electronics, Circuits and Systems (ICECS) pp. 65 - 68
Main Authors Schirmer, Marius, Stradolini, Francesca, Carrara, Sandro, Chicca, Elisabetta
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2016
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:An adequate drug dosage is often difficult to be achieved in personalized medicine. Especially for critical application, such as anesthesia. To reach the right dose adjustment, electrochemical biosensors can be used to measure the actual concentration of the drug in the patient's blood. Normally, since many drugs have to be measured simultaneously, Cyclic Voltammetry (CV) is the most convenient electrochemical technique to be adopted. The data measured during CVs are current values coming from RedOX reactions of the target molecules. To detect the concentration of medical drugs from CV data it is necessary to identify characteristic peaks among current values. Indeed, the dependence of peak current and concentration is directly proportional as described by the Randles-Sevcik equation. This paper introduces a new approach for CV peak detection based on Field Programmable Gate Array (FPGA) implementation. A circuit synthesis for FPGA able to estimate the peaks' height of the measured data has been implemented. FPGAs offer the advantage of being a tool for fast prototyping of integrated circuit designs as well as providing real-time signal processing. Specifically, it enables the construction of a real-time system suitable for the immediate analysis of the monitored data and therefore on-line correction of drug dosage.
DOI:10.1109/ICECS.2016.7841133