April 1, 1996IEEE Transactions on Biomedical Engineering

Classification of cardiac arrhythmias using fuzzy ARTMAP

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Population

ECG data from the MIT/BIH database containing normal and abnormal premature ventricular contraction QRS…

Design

Other

Authors

FHF.M. HamFlorida Institute of Technology SHSoowhan HanFlorida Institute of Technology

Discussion

Member takes

Implication

Supports neural network ECG diagnostics development; leaves open clinical adoption pending prospective validation.

Structured PICO

Population

ECG data from the MIT/BIH database containing normal and abnormal premature ventricular contraction (PVC) QRS complexes

Intervention

Fuzzy ARTMAP neural network trained on linear predictive coding (LPC) coefficients and mean-square value of QRS segments

Outcome

Classification performance (specificity and sensitivity) for normal and abnormal PVC conditions

A fuzzy ARTMAP neural network using linear predictive coding coefficients can accurately classify normal and abnormal premature ventricular contractions from ECG data.

Cite This Study

Ham et al. (1996) studied this question.

synapsesocial.com/papers/6a76536570b84e52bb88027d https://doi.org/10.1109/10.486263

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Classification of cardiac arrhythmias using fuzzy ARTMAP

Discussion

Member takes

Implication

Structured PICO

Cite This Study

Classification of cardiac arrhythmias using fuzzy ARTMAP

Discussion

Member takes

Implication

Structured PICO

Cite This Study

Also Consider

Also Consider