Article
Version 1
Preserved in Portico This version is not peer-reviewed
Electrochemical Sensors for Digital Medicine and Biology Electrochemical Digitization of Analytical Information Biological Fluids Samples
Version 1
: Received: 30 July 2022 / Approved: 1 August 2022 / Online: 1 August 2022 (10:19:30 CEST)
A peer-reviewed article of this Preprint also exists.
Sokolkov, S.V. Electrochemical Digitization of Biological Fluids Samples. Electrochem 2022, 3, 653-667. Sokolkov, S.V. Electrochemical Digitization of Biological Fluids Samples. Electrochem 2022, 3, 653-667.
Abstract
Digital medicine based on the integration of all medical data of a particular patient, has become a reality today, thanks to information technology. Traditional medical examinations can be supple-mented by assessment results of the oxidative-anti-oxidative (OAO) status of the body [1]. Elec-trochemical sensors are able to not only determine the integral indicators of the OAO system of the body, but also to depict details of the processes occurring in the system. The main obstacle to the widespread use of electrochemical sensors in medical diagnostics is the extremely small amount of the received information in comparison with tens of thousands of known human dis-eases. The problem can be eliminated only by rethinking the purpose of electrochemical measure-ment within the framework of thermodynamics of information processes and information theory. In the information paradigm of electrochemical analysis of biological fluids, a sample is considered as an electrochemical message created by a sensor. The purpose of electrochemical measurement is to obtain information in a volume sufficient to identify the sample composition within the range of possible concentrations of its components. The fundamentals of the thermodynamics of infor-mation processes are considered and conclusions that are of practical importance for the devel-opment of electrochemical sensors and analyzers are derived. It is shown that potentiostatic con-trol of the sensor is physically impacted by the electromechanical instability of the electrical double layer, which is the main source of sensor signal noise. Estimates are of a minimum amount of an-alytical signal information required for identification of a sample of a known composition, such as a biological fluid, are provided. Examples of highly informative analytical signals for flowing and stationary samples are presented. Problems related to the visualization of such signals are noted.
Keywords
electrochemistry; analytical signal; noise; trends; identification; classification; fluids samples
Subject
Chemistry and Materials Science, Electrochemistry
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Comments (0)
We encourage comments and feedback from a broad range of readers. See criteria for comments and our Diversity statement.
Leave a public commentSend a private comment to the author(s)
* All users must log in before leaving a comment
