Title :
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
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;
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
DOI :
10.1109/SSD.2012.6198121
