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MATLAB toolboxes: Teaching feature extraction from time‐varying biomedical signals
Author(s) -
Übeyli̇ Elif Derya,
Güler İnan
Publication year - 2006
Publication title -
computer applications in engineering education
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.478
H-Index - 29
eISSN - 1099-0542
pISSN - 1061-3773
DOI - 10.1002/cae.20086
Subject(s) - matlab , computer science , feature extraction , pattern recognition (psychology) , feature (linguistics) , signal processing , artificial intelligence , wavelet , signal (programming language) , speech recognition , data mining , digital signal processing , computer hardware , philosophy , linguistics , programming language , operating system
Abstract This article presents an initiative to teach the concept of feature extraction from time‐varying signals to biomedical engineering students. The approach was based on illustrative applications that highlight the performance of different feature extraction methods. Following a brief description of the feature extraction methods, applications of the methods to the time‐varying biomedical signals (electrocardiogram—ECG, electroencephalogram—EEG, arterial Doppler signals) were done by means of a series of MATLAB functions. The functions involved in Signal Processing and Wavelet Toolboxes of MATLAB, which can be used to extract features from the signals under study were presented. The authors suggest that the use of MATLAB exercises will assist the students in gaining a better understanding of the various features representing the time‐varying biomedical signals. © 2006 Wiley Periodicals, Inc. Comput Appl Eng Educ 14: 321–332, 2006; Published online in Wiley InterScience (www.interscience.wiley.com); DOI 10.1002/cae.20086