Detection of ventricular fibrillation by sequential hypothesis testing of Binary sequences

Computers in Cardiology

Volumn 34, Issue , 2007, Pages 573-576

  Pardey, J ^a  

^a Huntleigh Healthcare   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

HYPOTHESIS TESTING; LEMPEL-ZIV COMPLEXITY; NEURAL NETWORK CLASSIFIERS; THRESHOLD CROSSINGS; VENTRICULAR FIBRILLATIONS;

CARDIOLOGY; NEURAL NETWORKS;

BINARY SEQUENCES;

EID: 62949150443     PISSN: 02766574     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CIC.2007.4745550     Document Type: Conference Paper

References (15)

1. Thakor NV, Zhu YS, Pan KY. Ventricular tachycardia and fibrillation detection by a sequential hypothesis testing algorithm. IEEE Trans Biomed Eng 1990; 37: 837-43.
2. Clayton RH, Murray A, Campbell RWF. Comparison of four techniques for recognition of ventricular fibrillation from the surface ECG. Med & Biol Eng & Comput 1993;31:111-7.
3. Chen S-W, Clarkson PM, Fan Q. A robust sequential detection algorithm for cardiac arrhythmia classification. IEEE Trans Biomed Eng 1996; 43:1120-5.
4. Zhang X-S, Zhu Y-S, Thakor NV, Wang Z-Z. Detecting ventricular tachycardia and fibrillation by complexity measure. IEEE Trans Biomed Eng 1999; 46:548-55.
5. Moraes JC, Blechner M, Vilani FN, Costa EV. Ventricular fibrillation detection using a leakage / complexity measure method. IEEE Computers in Cardiology 2002; 29:213-6.
6. Amann A, Tratnig R, Unterkofler K. Reliability of old and new ventricular fibrillation detection algorithms for automated external defibrillators. Biomed Eng Online 2005; 4(60).
7. Chen S-W. Complexity measure based sequential hypothesis testing for real time detection of lethal cardiac arrhythmias. EURASIP Journal on Advances in Signal Processing 2007.
8. ANSI/AAMI EC38:1998 Ambulatory Electrocardiographs.
9. ANSI/AAMI EC57:1998 Testing and Reporting Performance Results of Cardiac Rhythm and ST Segment Measurement Algorithms.
10. Lempel A, Ziv J. On the complexity of finite sequences. IEEE Trans Inf Theory 1976; 22:75- 81.
11. Clayton RH, Murray A, Campbell RWF. Recognition of ventricular fibrillation using neural networks. Med & Biol Eng & Comput 1994; 32:217-20.
12. Pardey J, Jouravleva S. The next generation Holter revolution: from analyse-edit-print to analyse-print. IEEE Computers in Cardiology 2004; 31:373-6.
13. Pardey J. On the use of artificial neural networks in a commercial Holter algorithm. IEEE Computers in Cardiology 2006; 33:485-8.
14. Kuo S, Dillman R. Computer detection of ventricular fibrillation. IEEE Computers in Cardiology 1978; 347-9.
15. Barro S, Ruiz R, Cabello D, Mira J. Algorithmic sequential decision making in the frequency domain for life threatening ventricular arrhythmias and imitative artifacts: a diagnostic system. J Biomed Eng 1989; 11:320-8.