Open Access Open Access  Restricted Access Subscription or Fee Access

Detection of Heart Diseases by Analysing QRS Complex

M. Divya, Dr.V. Kalaivani, V. Anusuya Devi

Abstract


In this paper, we propose a novel method for the detection of heart diseases. It is proposed to develop an automated system for the classification of heart diseases. The proposed system includes pre-processing, peak detection, feature extraction, feature selection and classification. In pre-processing, the noise removal is done and then peak detection of input ECG signal is performed. The peak detection process is used to detect the peaks in the ECG signal. It is for the detection of QRS complex, QRS interval, from the ECG signal. Then, many time domain and frequency domain features are extracted and some among them are selected for the classification of heart diseases. This proposed system may be helpful for the clinical diagnosis of heart diseases like Ventricular Arrhythmias, Atrial Fibrillation and Atrial flutter.

Keywords


Electrocardiogram, ECG Signals, Heart Diseases, QRS Complex, Peak Detection.

Full Text:

PDF

References


Alberto Herreros, Enrique Baeyens (2009), ‘Analysis of changes in the beat-to-beat P-wave morphology using clustering techniques’, Elsevier Transactions on Biomedical Signal Processing and Control, Vol.4, pp. 309-316

Aliaksei Sandryhaila, Samir Saba, Markus Pijscel (2012), ‘Efficient compression of QRS complex using Hermite Expansion’, IEEE Transactions on Signal Processing,February, Vol.60, No.2, pp.947-955

Aline Cabasson,Olivier Meste (2012), ‘Estimation and Modeling of QT-Interval Adaptation to Heart Rate Changes’, IEEE Transactions on Biomedical Engineering, April,Vol.59, No.4, pp.956-964

Aline Cabasson,Olivier Meste (2009), ‘Quantifying the PR interval pattern during dynamic exercise and recovery’, IEEE Transactions on Biomedical Engineering,November,Vol.56, No.11, pp.2675-2683

Andrius Petrenas,Vaidotas Marozas (2012 ), ‘A Echo state neural network for QRST cancellation during atrial fibrillation’, IEEE Transactions on Biomedical Engineering,October, Vol.59, No.10, pp.2950-2957

Chatterjee H K, Gupta R, Mitra M (2012), ‘Real time P and T wave detection from ECG using FPGA’, Elsevier Transactions on Procedia Technology, Vol.4, pp.840-844

Chao Lin, Corine Mailhes (2010), ‘P-and T-Wave delineation in ECG signals using a Bayesian approach and a partially collapsed Gibbs sampler’, IEEE Transactions on Biomedical Engineering,December, Vol.57, no.12, pp.2840-2849

Chris F.Zhang and Tae-Wuk Bae (2012), ‘VLSI friendly ECG QRS complex detector for body sensor networks’, IEEE Journal on Emerging and Seleted Topics in Circuits and Systems,March, Vol.2, No.1, pp.52-59

Chia-Ping Shen, Wen-Chung Kao (2012),’Detection of cardiac arrhythmia in electrocardiogram using adaptive feature extraction and modified support vector machines’, Elsevier Transactions on Expert Systems with Applications,Vol.39, pp. 7845–7852

Deboleena Sadhukhan, Madhuchhanda Mitra (2012), ‘R-Peak detection algorithm for ECG using double difference and RR interval processing’. Elsevier Transactions on Procedia Technology , Vol.4, pp.873-877

Dierya C, Rowlandsa D, Cutmorea T R H, Jamesa D (2011), ‘Automated ECG diagnostic P-Wave analysis using wavelets’, Elsevier Transactions on computer methods and programs in biomedicine,Vol.101,pp. 33-43

Hong-Bo Xie , Zhong-Mei Gao, Hui Liu (2011), ‘Classification of ventricular tachycardia and fibrillation using fuzzy similarity-based approximate entropy’, Elsevier Transactions on Expert Systems with Applications,Vol.38, pp.3973–3981

Jinseok Leea, David D McManusc (2013), ‘Atrial flutter and atrial tachycardia detection using Bayesian approach with high resolution time–frequency spectrum from ECG recordings’, Elsevier Transactions on Biomedical Signal Processing and Control.

Manual Blanco-Velasco, Fernando Cruz-Roldan (2010), ‘Non linear trend estimation of the ventricular reploarization segment for T-Wave alternans detection’, IEEE Transactions on Biomedical Engineering,October,Vol.57, No.10, pp.2402-2412

Mehta S S, Lingayat N S (2009), ‘Application of support vector machine for the detection of P and T waves in 12 lead electrocardiogram’, Elsevier Transactions on computer methods and programs in biomedicine, Vol.93, pp.46-60,

Peter Van Leeuwen, Anna Vob (2012), ‘Automatic identification of fetal breathing movements in fetal RR interval time series’, Elsevier Transactions on Computers in Biology and Medical, Vol.42, pp.342-346

Sabarimalai Manikandana M, Somanb K P (2012), ‘A novel method for detecting R-Peaks in electrocardiogram signal’, Elsevier Transactions on Biomedical Signal Processing and Control, Vol.7, pp.118-128

Saeed Shakibfar, Claus Graff (2012), ‘Assessing common classification methods for the identification of abnormal repolarization using indicators of T-Wave morphology and QT interval’, Elsevier Transactions on Computers in Biology and Medicine ,Vol.42, pp.485-491

Shamim Nemati, Omar Abdala (2011), ‘A nonparametric surrogate based test of significance for T-Wave alternans detection’, IEEE Transactions on Biomedical Engineering,May, Vol.58, No.5,pp.1356-1364

Vincent Jacquemet, Bruno Dube (2011), ‘Extraction and Analysis of T Waves in Electrocardiograms During Atrial Flutter’, IEEE Transactions on Biomedical Engineering, April, Vol.58, No.4, pp.1104-1112




DOI: http://dx.doi.org/10.36039/AA032014001

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.