SVD and SVM based approach for congestive heart failure detection from ECG signal

40th International Conference on Computers and Industrial Engineering: Soft Computing Techniques for Advanced Manufacturing and Service Systems, CIE40 2010

Volumn , Issue , 2010, Pages

  Wang, Chien Chih ^a   Chang, Cheng Ding ^b  

^a MING CHI UNIVERSITY OF TECHNOLOGY   (Taiwan)

^b YUAN ZE UNIVERSITY   (Taiwan)

Author keywords

Physiological signal; Singular value decomposition; Support vector machine

Indexed keywords

CLASSIFICATION RESULTS; CONGESTIVE HEART FAILURES; DATA SETS; DETECTION APPROACH; ECG SIGNALS; EMPIRICAL MODE DECOMPOSITION; FEATURES EXTRACTION; HEALTHY PERSONS; INTRINSIC MODE FUNCTIONS; PHYSIOLOGICAL SIGNALS; PHYSIOLOGICAL STATE; PHYSIONET; RR INTERVALS; SINGULAR VALUES;

CLASSIFICATION (OF INFORMATION); FEATURE EXTRACTION; INDUSTRIAL ENGINEERING; PHYSIOLOGY; SIGNAL DETECTION; SOFT COMPUTING; SUPPORT VECTOR MACHINES; TABLE LOOKUP;

SINGULAR VALUE DECOMPOSITION;

EID: 78651467260     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCIE.2010.5668319     Document Type: Conference Paper

References (14)

1. M. S. Figueroa and J. I. Peters, "Congestive Heart Failure: Diagnosis, Pathophysiology, Therapy, and Implications for Respiratory Care," Respiratory Care, 51(4), pp. 403-412, 2006.
2. MedicineNet.com, http://www.medicinenet.com/congestive-heart-failure/ page2.htm#2whatcauses (Access time: 15.01.2010).
3. M. W. Rich, V. Beckham, C. Wittenberg, C. L. Leven, K. E. Freedland and R. M. Carney, "A Multidisciplinary Intervention to Prevent Readmission of Elderly Patients with Congestive Heart Failure," The New England Journal of Medicine, 333(18), pp. 1190-1195, 1995.
4. P. M. Rautaharju, C. Kooperberg, J. C. Larson and A. LaCroix, "Electrocardiographic Predictors of Incident Congestive Heart Failure and All-Causes Mortality in Postmenopausal Women," Circulation, 113, pp. 481-489, 2006.
5. E. D. Übeyli, "Adaptive Neuro-Fuzzy Inference System for Classification of ECG Signals Using Lyapunov Exponents," Computer Methods and Programs in Biomedicine, 93, pp. 313-321, 2009.
6. E. D. Übeyli, "ECG Beats Classification Using Multiclass Support Vector Machines With Error Correcting Codes,"Digital Signal Processing, 17, pp. 675-684, 2007.
7. T. Lahiri, U. Kumar, H. Mishra, S. Sarkar, and A. D. Roy, "Analysis of ECG Signal by Chaos Principle to Help Automatic Diagnosis of Myocardial Infarction," Journal of Scientific and Industrial Research, 68, pp. 866-870, 2009.
8. H. V. Huikuri, T. H. Mäkikallio, C. K. Peng, A. L. Goldberger, "Ulrik Hintze and Mogens Møller, Fractal Correlation Properties of R-R Interval Dynamics and Mortality in Patients With Depressed Left Ventricular Function After an Acute Myocardial Infarction," Circulation, 101, pp. 47-53, 2000.
9. M.G. Tsipouras, D. I. Fotiadis and D. Sideris, "An Arrhythmia Classification System Based On The RR-interval Signal," Artificial Intelligence in Medicine, 33(3), pp. 237-250, 2005.
10. P. P. Kanjilal, S. Palit and G. Saha, "Fetal ECG Extraction from Single-Channel Maternal ECG Using Singular Value Decomposition,". IEEE Trans. Biomed. Eng., 44(1), pp. 51-59, 1997.
11. M. Ayat, K. Assaleh and H. Nashash, "Fetal ECG Extraction from A Single Abdominal ECG Signal Using SVD and Polynomial Classifiers," IEEE Workshop on Machine Learning for Signal Processing, Cancun, Mexico, 2008.
12. Physiobank Archieve Index, Normal Sinus Rhythm RR Interval Database: http://www.physionet.org/physiobank/database/nsr2db (Access time: 28.10.2009).
13. Physiobank Archieve Index, Congestive Heart Failure RR Interval Database: http://www.physionet.org/physiobank/database/chf2db (Access time: 28.10.2009).
14. N. E. Huang, M. C. Wu, S. R. Long, S. S. P. Shen, W. Qu, P. Gloersen and K. L. Fan, A Confidence Limit for the Empirical Mode Decomposition and Hilbert Spectrum Analysis, Proc. R. Soc. Lond. A, 459, 2317-2345, 2003.