Patient Identification and comparative study on Bioimpedance based diagnosis

Abstract

Bioimpedance analysis has become a major breakthrough in newlinethe medical field which plays a vital role in determining various newlinefunctional body parameters. The impedance which is measured in newlineopposition to a current flow through a tissue can be widely applied to newlinediagnose critical disease conditions of different systems of the human newlinebody. Many researches have been carried out for the diagnosis of newlinevarious physiological systems, including cardiac monitoring using newlinebioimpedance technique. It is also necessary to ensure quality health newlineinformation about the patients and their identity to provide value based newlinecare for ensuring patient safety. Biometric based patient identification newlinehas been developed by researchers to ensure patient safety for critically newlineill patients. The efficiency of a bioimpedance measurement system can newlinebe improved by simultaneously measuring the physiological parameters newlineof a patient along with patient identification. newlineThe proposed research work implements an electrical newlinebioimpedance based acquisition system with patient identification and newlinebioimpedance based disease diagnosis system for different age group. newlineThe main objective of the work is to study the influence of the excitation newlinesignal on the bioimpedance signal and to understand the different types newlineof electrodes and its configuration used in bioimpedance measurement newlinesystem. The first part of the work focus on designing a patient newlineidentification system for identification of patient during critical newlineconditions where the patient interaction is not possible using LabVIEW. newlineThe bioimpedance value obtained is unique for each individual. This newlinesystem has two modes of operation- enrollment and recognition. During newlineix newlineenrollment mode, when a patient is hospitalized for any surgery, the newlineimpedance value of the patient is acquired and stored with the patient newlinedetail using LabVIEW algorithm. During enrollment, before the surgery newlinebioimpedance value is measured again and matched with the enrolled newlinevalues to confirm the patient.