Multiwavelet Feature Sets for ECG Beat Classification

被引：0

作者：

Sarvan, Cagla ^{[1
]}

Ozkurt, Nalan ^{[1
]}

机构：

[1] Yasar Univ, Elekt & Elekt Muhendisligi Bolumu, Izmir, Turkey

来源：

2017 25TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU) | 2017年

关键词：

ECG heart beat classification; arrhythmia; discrete wavelet transform; multiwavelet features; artificial neural networks;

D O I：

暂无

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

In this study, heart beats are classified as normal, right branch block, left branch block, and paced rhythm using electrocardiographic (ECG) signals obtained from the MIT-BIH cardiac arrhythmia database. Average, standard deviation, energy and entropy of discrete wavelet transform (DWT) coefficients are proposed as the features for the classification. The classification was performed by selecting the appropriate train function of artificial neural network. It has been observed that the combined use of two different feature sets from two wavelet families with the appropriate train function of neural network is better than use of individual wavelets features.

引用

页数：4

共 50 条

[21] Filter Bank-based ECG beat classification
Afonso, VX
Wieben, O
Tompkins, WJ
Nguyen, TQ
Luo, S
PROCEEDINGS OF THE 19TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOL 19, PTS 1-6: MAGNIFICENT MILESTONES AND EMERGING OPPORTUNITIES IN MEDICAL ENGINEERING, 1997, 19 : 97 - 100
[22] A Method for the Automatic Classification of ECG Beat on Mobile Phones
Varella, Fernando Arena
de Lima, Guilherme Lazzarotto
Iochpe, Cirano
Roesler, Valter
2011 24TH INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS (CBMS), 2011,
[23] A multiple-classifier architecture for ECG beat classification
Palreddy, S
Hu, YH
Mani, V
Tompkins, WJ
NEURAL NETWORKS FOR SIGNAL PROCESSING VII, 1997, : 172 - 181
[24] ECG beat classification using Mirrored Gauss Model
Zhou, Qunyi
Liu, Xing
Duan, Huilong
2005 27TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-7, 2005, : 5587 - 5590
[25] ECG beat classification using machine learning techniques
Jambukia, Shweta H.
Dabhi, Vipul K.
Prajapati, Harshadkumar B.
INTERNATIONAL JOURNAL OF BIOMEDICAL ENGINEERING AND TECHNOLOGY, 2018, 26 (01) : 32 - 53
[26] A Modified Convolutional Neural Network for ECG Beat Classification
Yang, Lulu
Zhu, Junjiang
Yan, Tianhong
Wang, Zhaoyang
Wu, Shangshi
JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS, 2020, 10 (03) : 654 - 660
[27] Patient-specific ECG beat classification technique
Das, Manab K.
Ari, Samit
HEALTHCARE TECHNOLOGY LETTERS, 2014, 1 (03): : 98 - 103
[28] ECG beat classification using a cost sensitive classifier
Zidelmal, Z.
Amirou, A.
Ould-Abdeslam, D.
Merckle, J.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2013, 111 (03) : 570 - 577
[29] A trainable neural network ensemble for ECG beat classification
Sajedin, Atena
Zakernejad, Shokoufeh
Faridi, Soheil
Javadi, Mehrdad
Ebrahimpour, Reza
World Academy of Science, Engineering and Technology, 2010, 69 : 788 - 794
[30] ECG beat classification by a novel hybrid neural network
Dokur, Z
Ölmez, T
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2001, 66 (2-3) : 167 - 181

← 1 2 3 4 5 →