AUTOMATIC DETECTION OF PREMATURE COMPLEXES IN ECG USING WAVELET FEATURES AND FUZZY HYBRID NEURAL NETWORK

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FARROKHI F.; MORADI M.H.; MIRI R.

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Journal Paper

Paper Information

Journal: IRANIAN JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING (IJECE) Year:2004 | Volume:3 | Issue:2 Page(s): 132-137

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Information Journal Paper

Title

AUTOMATIC DETECTION OF PREMATURE COMPLEXES IN ECG USING WAVELET FEATURES AND FUZZY HYBRID NEURAL NETWORK

Author(s)

FARROKHI F. | MORADI M.H. | MIRI R. | Issue Writer Certificate

Keywords

PREMATURE VENTRICULAR COMPLEX

PREMATURE ATRIAL COMPLEX

ECG BEAT DETECTION

ECG BEAT RECOGNITION

NEURO FUZZY CLASSIFIER

DISCRETE WAVELET TRANSFORM

Abstract

This paper will purpose a beat recognition algorithm using discrete wavelet coefficients and fuzzy hybrid neural network. Cardiac beats have been detected from differential of compressed wavelet coefficients by Linear Approximation Data Transfer (LADT) algorithm and adaptive thresholds. The variance and sum of the squared wavelet coefficients and the R-R ratio of successive beats have been applied to the self organizing subnetwork connected in cascade with a multi layer perceptron as final classifier.The c-means and Gustafson-Kessel algorithms have been applied for the self-organizing layer. Potential of the method was examined using MIT_BIH arrhythmia database. Results show high detection (99.43%) and high sensitivity (99.65%) on 59864 detected beats and 100% sensitivity and specificity on premature beat recognition.

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APA: Copy

FARROKHI, F., MORADI, M.H., & MIRI, R.. (2004). AUTOMATIC DETECTION OF PREMATURE COMPLEXES IN ECG USING WAVELET FEATURES AND FUZZY HYBRID NEURAL NETWORK. IRANIAN JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING (IJECE), 3(2), 132-137. SID. https://sid.ir/paper/283342/en

Vancouver: Copy

FARROKHI F., MORADI M.H., MIRI R.. AUTOMATIC DETECTION OF PREMATURE COMPLEXES IN ECG USING WAVELET FEATURES AND FUZZY HYBRID NEURAL NETWORK. IRANIAN JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING (IJECE)[Internet]. 2004;3(2):132-137. Available from: https://sid.ir/paper/283342/en

IEEE: Copy

F. FARROKHI, M.H. MORADI, and R. MIRI, “AUTOMATIC DETECTION OF PREMATURE COMPLEXES IN ECG USING WAVELET FEATURES AND FUZZY HYBRID NEURAL NETWORK,” IRANIAN JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING (IJECE), vol. 3, no. 2, pp. 132–137, 2004, [Online]. Available: https://sid.ir/paper/283342/en

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