January 1, 2024Facta universitatis - series Electronics and EnergeticsOpen Access

Classifier accuracy levels of 91% (Support Vector Machine) and 98.94% (Decision Tree) were achieved using published datasets.

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Why the study?

Ensemble Empirical Mode Decomposition overcomes mode mixing in ECG analysis, but intrinsic mode functions vary depending on parameters used, creating a need for parameter-independent, consistent feature extraction.

Population

Published ECG datasets

Comparison

Different bioinspired optimization techniques for EEMD feature extraction evaluated with SVM and Decision Tree classifiers

Design

Algorithm development and validation study

Authors

ABA. S. Bakshi MPMamata Panigrahy JDJitendra Kumar Das

Discussion

Member takes

Overview

Caution against routine clinical use without validation; leaves open diagnostic utility pending prospective studies.

Structured PICO

Population

Published electrocardiogram (ECG) datasets

Intervention

Optimized Ensemble Empirical Mode Decomposition (EEMD) feature extraction using bio-inspired optimization algorithms

Outcome

Classifier accuracy

An optimized EEMD feature extraction method using bio-inspired algorithms achieved high classification accuracy for ECG signals, demonstrating its potential utility in automated ECG analysis.

Cite This Study

Bakshi et al. (2024) studied this question.

synapsesocial.com/papers/6a7614bb554f5a6e3e613e90 https://doi.org/10.2298/fuee2404619b

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January 1, 2024Facta universitatis - series Electronics and EnergeticsOpen Access

Classifier accuracy levels of 91% (Support Vector Machine) and 98.94% (Decision Tree) were achieved using published datasets.

View Full Paper

Ask AI

Bookmark

Why the study?

Population

Published ECG datasets

Comparison

Different bioinspired optimization techniques for EEMD feature extraction evaluated with SVM and Decision Tree classifiers

Design

Algorithm development and validation study

Authors

ABA. S. Bakshi MPMamata Panigrahy JDJitendra Kumar Das

Discussion

Member takes

Overview

Caution against routine clinical use without validation; leaves open diagnostic utility pending prospective studies.

Structured PICO

Population

Published electrocardiogram (ECG) datasets

Intervention

Optimized Ensemble Empirical Mode Decomposition (EEMD) feature extraction using bio-inspired optimization algorithms

Outcome

Classifier accuracy

An optimized EEMD feature extraction method using bio-inspired algorithms achieved high classification accuracy for ECG signals, demonstrating its potential utility in automated ECG analysis.

Cite This Study

Bakshi et al. (2024) studied this question.

synapsesocial.com/papers/6a7614bb554f5a6e3e613e90 https://doi.org/10.2298/fuee2404619b

View Full Paper

Ask AI

Bookmark