Morphological modeling of cardiac signals based on signal decomposition

被引：43

作者：

Roonizi, Ebadollah Kheirati ^{[1
]}

Sameni, Reza ^{[1
]}

机构：

[1] Shiraz Univ, Sch Elect & Comp Engn, Shiraz, Iran

来源：

COMPUTERS IN BIOLOGY AND MEDICINE | 2013年 / 43卷 / 10期

关键词：

Morphological modeling; Signal decomposition; Electrocardiogram modeling; Electrocardiogram compression; ECG; REPRESENTATION; FRAMEWORK;

D O I：

10.1016/j.compbiomed.2013.06.017

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

In this paper a general framework is presented for morphological modeling of cardiac signals from a signal decomposition perspective. General properties of a desired morphological model are presented and special cases of the model are studied in detail. The presented approach is studied for modeling the morphology of electrocardiogram (ECG) signals. Specifically, three types of ECG modeling techniques, including polynomial spline models, sinusoidal model and a model previously presented by McSharry et al., are studied within this framework. The proposed method is applied to datasets from the PhysioNet ECG database for compression and modeling of normal and abnormal ECG signals. Quantitative and qualitative results of these applications are also presented and discussed. (C) 2013 Elsevier Ltd. All rights reserved.

引用

页码：1453 / 1461

页数：9

共 50 条

[21] A method separating echo by adaptive chirplet signal decomposition based on FRFT [J].

Chen Wen-jing ;

Yuan Li ;

Sheng Jing ;

Ren Hong-mei .

PROCEEDINGS OF THE 2016 11TH INTERNATIONAL SYMPOSIUM ON ANTENNAS, PROPAGATION AND EM THEORY (ISAPE), 2016, :869-872

[22] Signal decomposition by using the S-method with application to the analysis of HF radar signals in sea-clutter [J].

Stankovic, LJubisa ;

Thayaparan, Thayananthan ;

Dakovic, Milos .

IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2006, 54 (11) :4332-4342

[23] Unified study on the decomposition for deterministic signals and stationary random signals [J].

Wang H.-Y. ;

Qiu T.-S. .

Tongxin Xuebao/Journal on Communications, 2016, 37 (10) :1-8

[24] Decomposition of Multicomponent Micro-Doppler Signals Based on HHT-AMD [J].

Li, Wenchao ;

Kuang, Gangyao ;

Xiong, Boli .

APPLIED SCIENCES-BASEL, 2018, 8 (10)

[25] A NOVEL SIGNAL DECOMPOSITION APPROACH - ADAPTIVE FOURIER DECOMPOSITION [J].

Zhang, Liming ;

Li, Hong .

ADVANCES IN DATA SCIENCE AND ADAPTIVE ANALYSIS, 2011, 3 (03) :325-338

[26] ON-SIGNAL DECOMPOSITION TECHNIQUES [J].

AKANSU, AN ;

LIU, YP .

OPTICAL ENGINEERING, 1991, 30 (07) :912-920

[27] Fetal ECG Extraction and QRS Detection Using Advanced Adaptive Filtering-Based Signal Decomposition and Peak Threshold Technique from Abdominal ECG Signals [J].

Jebastine, J. .

CIRCUITS SYSTEMS AND SIGNAL PROCESSING, 2023, 42 (10) :6058-6088

[28] Acoustic cardiac signals analysis: a Kalman filter-based approach [J].

Salleh, Sheik Hussain ;

Hussain, Hadrina Sheik ;

Swee, Tan Tian ;

Ting, Chee-Ming ;

Noor, Alias Mohd ;

Pipatsart, Surasak ;

Ali, Jalil ;

Yupapin, Preecha P. .

INTERNATIONAL JOURNAL OF NANOMEDICINE, 2012, 7 :2873-2881

[29] Modelling and decomposition of compound biomedical signals [J].

Zazula, D .

INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOL I AND II, 1999, :196-202

[30] REPRESENTATION OF SIGNALS BY LOCAL SYMMETRY DECOMPOSITION [J].

Gnutti, Alessandro ;

Guerrini, Fabrizio ;

Leonardi, Riccardo .

2015 23RD EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO), 2015, :983-987

← 1 2 3 4 5 →