Feature Extraction From Biological Signals: A Case Study

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F04%3A03099608" target="_blank" >RIV/68407700:21230/04:03099608 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Feature Extraction From Biological Signals: A Case Study
Original language description
This paper presents two case studies illustrating the problem of data preprocessing as the first step in computer-aided analysis of biological signals used in clinical decision support. Methods for data extraction from ECG and EEG signals are described.We show the differences between these two signal types and the reasons why different approaches are used for their preprocessing. Analysis of ECG records is performed by the wavelet transform, and analysis of EEG records is performed using adaptive segmentation and the Fourier transform. The wavelet transform allows good localisation of QRS complexes, P and T waves in time and amplitude. The average accuracy of detection of all events is above 87 per cent. Adaptive segmentation abstracts the EEG signaldata into stationary segments and the Fourier transform calculates their basic characteristics. In both cases extracted data are used as inputs for machine learning methods.
Czech name
Není k dispozici
Czech description
Není k dispozici

Publication year
2004
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
IEEE 4th International Conference on Intelligent Systems Design and Application
ISBN
963-7154-29-9
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
139-144
Publisher name
IEEE
Place of publication
Piscataway
Event location
Budapest
Event date
Aug 26, 2004
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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