Physiological signals to individual assessment for application in wireless health systems

Author

Kumar, Mohit ; Stoll, Norbert ; Thurow, Kerstin ; Stoll, Regina

Author_Institution

Center for Life Sci. Autom., Rostock, Germany

fYear

2012

fDate

20-23 March 2012

Firstpage

1

Lastpage

6

Abstract

The mathematical analysis of physiological signals is meant for extracting the signal features relevant for functional state assessment. The stochastic fuzzy modeling and analysis techniques have much to offer in this area. The approach takes simultaneously the advantages of Bayesian analysis theory and fuzzy theory to formulate the patients´ state prediction problem mathematically in a sensible way. It is possible to design new signal feature extraction methods with high diagnostic efficiency and thus is possible to build an expert system for making accurate predictions regarding the physiological state of individuals.

Keywords

Bayes methods; feature extraction; fuzzy reasoning; medical expert systems; medical signal processing; personal area networks; physiological models; stochastic processes; Bayesian analysis theory; diagnostic efficiency; expert system; functional state assessment; mathematical analysis; patient state prediction problem; physiological signals; signal feature extraction; stochastic fuzzy modeling; wireless health system; Bayesian methods; Computational modeling; Data models; Feature extraction; Physiology; Stochastic processes; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Signals and Devices (SSD), 2012 9th International Multi-Conference on

Conference_Location

Chemnitz

Print_ISBN

978-1-4673-1590-6

Electronic_ISBN

978-1-4673-1589-0

Type

conf

DOI

10.1109/SSD.2012.6198121

Filename

6198121