Heart Blocks Detection in ECG Signals Using Time Frequency Distribution Techniques

被引：0
|
作者：
Azarnia, Ghanbar [1 ]
Tinati, Mohammad Ali [1 ]
Afkhami, Rashid Ghorbani [1 ]
机构：
[1] Univ Tabriz, Fac Elect & Comp Engn, Tabriz, Iran
来源：
2016 24TH IRANIAN CONFERENCE ON ELECTRICAL ENGINEERING (ICEE) | 2016年
关键词：
electrocardiogram signal; heart blocks; time-frequency distribution; time-frequency resolution; Choi-Williams distribution;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
The electrical conduction system of the heart has an elaborate structure. A small failure in this system can put the person's life in danger. In people with heart block disease the electrical signal that controls the heartbeat is partially or completely blocked from reaching the ventricles. Electrocardiograms are used in detection of heart blocks and thus in this paper we have used it for the assessment of heart block cases. In this paper we propose a noninvasive diagnostic method based on the Choi Williams distribution to differentiate between normal and heart block subjects. The proposed procedure in addition to detection of heart blocks provides additional information for better characterization of ECG parameters for heart block subjects. Simulation results show superior performance of our proposed algorithm with respect to the others.
引用
收藏
页码：1568 / 1573
页数：6
相关论文
共 50 条
  • [21] Personal Identification Using a Robust Eigen ECG Network Based on Time-Frequency Representations of ECG Signals
    Lee, Jae-Neung
    Kwak, Keun-Chang
    IEEE ACCESS, 2019, 7 : 48392 - 48404
  • [22] Application of Deep Neural Network for Congestive Heart Failure Detection Using ECG Signals
    Zhang, Yue
    Xia, Ming
    4TH INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE APPLICATIONS AND TECHNOLOGIES (AIAAT 2020), 2020, 1642
  • [23] Mental Stress Detection using Heart Rate Variability and Morphologic Variability of ECG Signals
    Costin, Hariton
    Rotariu, Cristian
    Pasarica, Alexandru
    PROCEEDINGS OF THE 2012 INTERNATIONAL CONFERENCE AND EXPOSITION ON ELECTRICAL AND POWER ENGINEERING (EPE 2012), 2012, : 591 - 596
  • [24] DETECTION OF UNKNOWN SIGNALS USING TIME FREQUENCY-ANALYSIS
    BOASHASH, B
    OSHEA, P
    CA-DSP 89, VOLS 1 AND 2: 1989 INTERNATIONAL SYMPOSIUM ON COMPUTER ARCHITECTURE AND DIGITAL SIGNAL PROCESSING, 1989, : 231 - 235
  • [25] DISTRIBUTION OF STANDARD FREQUENCY AND TIME SIGNALS
    MORGAN, AH
    PROCEEDINGS OF THE INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS, 1967, 55 (06): : 827 - +
  • [26] Recording of ECG signals on a portable MiniDisc recorder for time and frequency domain heart rate variability analysis
    Norman, SE
    Eager, RA
    Waran, NK
    Jeffery, L
    Schroter, RC
    Marlin, DJ
    PHYSIOLOGY & BEHAVIOR, 2005, 83 (05) : 729 - 738
  • [27] Detection of abnormal heart conditions based on characteristics of ECG signals
    Hammad, Mohamed
    Maher, Asmaa
    Wang, Kuanquan
    Jiang, Feng
    Amrani, Moussa
    MEASUREMENT, 2018, 125 : 634 - 644
  • [28] Deconvolution approach for time-frequency analysis of ECG signals
    Al-Manie, MA
    2004 RF AND MICROWAVE CONFERENCE, RFM 2004, PROCEEDINGS, 2004, : 243 - 245
  • [29] A new method for QRS detection in ECG signals using QRS-preserving filtering techniques
    Sharma, Tanushree
    Sharma, Kamalesh K.
    BIOMEDICAL ENGINEERING-BIOMEDIZINISCHE TECHNIK, 2018, 63 (02): : 207 - 217
  • [30] Application of deep learning techniques for heartbeats detection using ECG signals-analysis and review
    Murat, Fatma
    Yildirim, Ozal
    Talo, Muhammed
    Baloglu, Ulas Baran
    Demir, Yakup
    Acharya, U. Rajendra
    COMPUTERS IN BIOLOGY AND MEDICINE, 2020, 120
12345