P, Q, R, S and T peaks recognition of ECG using MRBF with selected features

Syed Sahal Nazli Alhady; Mohd Rizal Arshad; Mohd Yusoff Mashor

P, Q, R, S and T peaks recognition of ECG using MRBF with selected features

Syed Sahal Nazli Alhady^*, Mohd Rizal Arshad, Mohd Yusoff Mashor

^*Corresponding author for this work

Universiti Sains Malaysia

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

Abstract

P, Q, R, S and T peaks of ECG signal are fundamental and normally will be used as reference for classification and other parameters application for ECG signal. Multiple Radial Basis Function (MRBF) network is proposed in the current study for identification of these peaks for ECG signal. Amplitude, duration, pre-gradient, post-gradient and peak degree were used as inputs to the individual RBF networks with selected features.. The best accuracy achieved for individual network are combined and overall accuracy of 86.53% achieved for identification of P, Q, R, S and T peaks.

Original language	English
Pages (from-to)	136-139
Number of pages	4
Journal	WSEAS Transactions on Systems
Volume	4
Issue number	1
Publication status	Published - Jan 2005
Externally published	Yes

Keywords

Peak Degree and Multiple Radial Basis Function (MRBF)
Post-gradient
Pre-gradient

Cite this

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abstract = "P, Q, R, S and T peaks of ECG signal are fundamental and normally will be used as reference for classification and other parameters application for ECG signal. Multiple Radial Basis Function (MRBF) network is proposed in the current study for identification of these peaks for ECG signal. Amplitude, duration, pre-gradient, post-gradient and peak degree were used as inputs to the individual RBF networks with selected features.. The best accuracy achieved for individual network are combined and overall accuracy of 86.53% achieved for identification of P, Q, R, S and T peaks.",

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AU - Alhady, Syed Sahal Nazli

AU - Arshad, Mohd Rizal

AU - Mashor, Mohd Yusoff

PY - 2005/1

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N2 - P, Q, R, S and T peaks of ECG signal are fundamental and normally will be used as reference for classification and other parameters application for ECG signal. Multiple Radial Basis Function (MRBF) network is proposed in the current study for identification of these peaks for ECG signal. Amplitude, duration, pre-gradient, post-gradient and peak degree were used as inputs to the individual RBF networks with selected features.. The best accuracy achieved for individual network are combined and overall accuracy of 86.53% achieved for identification of P, Q, R, S and T peaks.

AB - P, Q, R, S and T peaks of ECG signal are fundamental and normally will be used as reference for classification and other parameters application for ECG signal. Multiple Radial Basis Function (MRBF) network is proposed in the current study for identification of these peaks for ECG signal. Amplitude, duration, pre-gradient, post-gradient and peak degree were used as inputs to the individual RBF networks with selected features.. The best accuracy achieved for individual network are combined and overall accuracy of 86.53% achieved for identification of P, Q, R, S and T peaks.

KW - Peak Degree and Multiple Radial Basis Function (MRBF)

KW - Post-gradient

KW - Pre-gradient

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SN - 1109-2777

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JO - WSEAS Transactions on Systems

JF - WSEAS Transactions on Systems

IS - 1

ER -

P, Q, R, S and T peaks recognition of ECG using MRBF with selected features

Abstract

Keywords

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