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Ebrahimzadeh et al., 2018 - Google Patents

A time local subset feature selection for prediction of sudden cardiac death from ECG signal

Ebrahimzadeh et al., 2018

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Document ID
8302494915834159197
Author
Ebrahimzadeh E
Manuchehri M
Amoozegar S
Araabi B
Soltanian-Zadeh H
Publication year
Publication venue
Medical & biological engineering & computing

External Links

Snippet

Prediction of sudden cardiac death continues to gain universal attention as a promising approach to saving millions of lives threatened by sudden cardiac death (SCD). This study attempts to promote the literature from mere feature extraction analysis to developing …
Continue reading at www.researchgate.net (PDF) (other versions)

Classifications

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    • A61B5/04—Detecting, measuring or recording bioelectric signals of the body of parts thereof
    • A61B5/0402—Electrocardiography, i.e. ECG
    • A61B5/0452—Detecting specific parameters of the electrocardiograph cycle
    • A61B5/046—Detecting fibrillation
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
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    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
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    • A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
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