DocumentCode
981066
Title
Biosignal pattern recognition and interpretation systems. 2. Methods for feature extraction and selection
Author
Ciaccio, E.J. ; Dunn, S.M. ; Akay, M.
Author_Institution
Dept. of Biomed. Eng., Rutgers Univ., Piscataway, NJ, USA
Volume
12
Issue
4
fYear
1993
Firstpage
106
Lastpage
113
Abstract
Some feature extraction methods used in biomedical signal pattern recognition are presented. Particular attention is given to nontransformed signal characteristics, transformed signal characteristics, structural descriptors, graph descriptors, and feature selection methods. It is noted that the wide variety of techniques used for feature extraction presents two problems: which techniques should be used and how to select from among the features that each extraction technique generates. Selected features are best only by some standard; therefore, techniques for generation of features tend not to be very portable from one pattern processing problem to another. Production of salient features is the connecting link between prototypical and symbolic representations of a class. Often, thresholds govern the selection of features. Many techniques do not generate independent features; therefore, there is redundancy in the data, which potentially affects both efficiency and accuracy in pattern recognition.<>
Keywords
feature extraction; medical signal processing; biosignal pattern interpretation system; biosignal pattern recognition; data redundancy; feature selection methods; graph descriptors; nontransformed signal characteristics; prototypical representations; salient features production; structural descriptors; symbolic representations; thresholds; transformed signal characteristics; Autoregressive processes; Biomedical engineering; Biomedical measurements; Feature extraction; Hardware; Harmonic analysis; Parametric statistics; Pattern analysis; Pattern recognition; Power system modeling;
fLanguage
English
Journal_Title
Engineering in Medicine and Biology Magazine, IEEE
Publisher
ieee
ISSN
0739-5175
Type
jour
DOI
10.1109/51.248173
Filename
248173
Link To Document