By Topic

Biosignal pattern recognition and interpretation systems. 2. Methods for feature extraction and selection

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
E. J. Ciaccio ; Dept. of Biomed. Eng., Rutgers Univ., Piscataway, NJ, USA ; S. M. Dunn ; M. Akay

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.<>

Published in:

IEEE Engineering in Medicine and Biology Magazine  (Volume:12 ,  Issue: 4 )