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Volume 20, Issue 1
  • ISSN: 1573-4056
  • E-ISSN: 1875-6603
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Abstract

Biomedical signal and image processing is the study of the dynamic behavior of various bio-signals, which benefits academics and research. Signal processing is used to assess the behavior of analogue and digital signals for the assessment, reconfiguration, improved efficiency, extraction of features, and reorganization of patterns. This paper unveils hidden characteristic information about input signals using feature extraction methods. The main feature extraction methods used in signal processing are based on studying time, frequency, and frequency domain. Feature exaction methods are used for data reduction, comparison, and reducing dimensions, producing the original signal with sufficient accuracy with a structure of an efficient and robust pattern for the classifier system. Therefore, an attempt has been made to study the various feature extraction methods, feature transformation methods, classifiers, and datasets for biomedical signals.

© 2024 The Author(s). Published by Bentham Science Publisher.
This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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2024-10-15

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Current Trends in Feature Extraction and Classification Methodologies of Biomedical Signals
Curr. Med. Imaging 20, E090323214502 (2024); https://doi.org/10.2174/1573405619666230309103435
/content/journals/cmir/10.2174/1573405619666230309103435
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  • Article Type: Review Article
Keyword(s): Biomedical Signals; Classifier; Datasets; Feature extraction method; Feature transformation; Image processing

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