Title :
Extraction of stationary components in biosignal discrimination
Author :
Martinez-Vargas, J.D. ; Cardenas-Pena, D. ; Castellanos-Dominguez, German
Author_Institution :
Signal Process. & Recognition Group, Univ. Nac. de Colombia, Manizales, Colombia
fDate :
Aug. 28 2012-Sept. 1 2012
Abstract :
Biosignal recordings are widely used in the medical environment to support the evaluation and the diagnosis of pathologies. Nevertheless, the main difficulty lies in the non-stationary behavior of the biosignals, difficulting the obtention of patterns characterizing the changes in physiological or pathological states. Thus, the obtention of the stationary and non-stationary components of a biosignal is still an open issue. This work proposes a methodology to detect time-homogeneities based on time-frequency analysis with aim to extract the non-stationary behavior of the biosignal. Results show an increase in the stationarity and in the distance between classes of the reconstructions from the enhanced time-frequency representations. The stationary components extracted with the proposed approach can be used to solve biosignal classification problems.
Keywords :
diseases; feature extraction; medical signal processing; patient diagnosis; signal classification; signal reconstruction; signal representation; time-frequency analysis; biosignal classification problems; biosignal discrimination; biosignal recordings; enhanced time-frequency representations; medical environment; non-stationary components; nonstationary behavior; pathological states; pathology diagnosis; pattern obtention; physiological states; reconstructions; stationary component extraction; stationary obtention; time-frequency analysis; Databases; Electroencephalography; Heart rate variability; Stochastic processes; Time frequency analysis; Time series analysis; Multivariate locally stationary time series; Time-evolving Latent Variable Decomposition; Databases, Factual; Electroencephalography; Epilepsy; Female; Humans; Male; Models, Biological; Signal Processing, Computer-Assisted; Signal-To-Noise Ratio;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4244-4119-8
Electronic_ISBN :
1557-170X
DOI :
10.1109/EMBC.2012.6345856