- Research Article
- Open Access
Complexity-Measure-Based Sequential Hypothesis Testing for Real-Time Detection of Lethal Cardiac Arrhythmias
EURASIP Journal on Advances in Signal Processing volume 2007, Article number: 020957 (2006)
A novel approach that employs a complexity-based sequential hypothesis testing (SHT) technique for real-time detection of ventricular fibrillation (VF) and ventricular tachycardia (VT) is presented. A dataset consisting of a number of VF and VT electrocardiogram (ECG) recordings drawn from the MIT-BIH database was adopted for such an analysis. It was split into two smaller datasets for algorithm training and testing, respectively. Each ECG recording was measured in a 10-second interval. For each recording, a number of overlapping windowed ECG data segments were obtained by shifting a 5-second window by a step of 1 second. During the windowing process, the complexity measure (CM) value was calculated for each windowed segment and the task of pattern recognition was then sequentially performed by the SHT procedure. A preliminary test conducted using the database produced optimal overall predictive accuracy of. The algorithm was also implemented on a commercial embedded DSP controller, permitting a hardware realization of real-time ventricular arrhythmia detection.
Cain ME, Ambos HD, Markham J, Lindsay BD, Arthur RM: Diagnostic implications of spectral and temporal analysis of the entire cardiac cycle in patients with ventricular tachycardia. Circulation 1991,83(5):1637–1648.
Thakor NV, Zhu Y-S, Pan K-Y: Ventricular tachycardia and fibrillation detection by a sequential hypothesis testing algorithm. IEEE Transactions on Biomedical Engineering 1990,37(9):837–843. 10.1109/10.58594
Chen S-W, Clarkson PM, Fan Q: A sequential technique for cardiac arrhythmia discrimination. Journal of Electrocardiology 1995,28(1):162.
Chen S-W, Clarkson PM, Fan Q: A robust sequential detection algorithm for cardiac arrhythmia classification. IEEE Transactions on Biomedical Engineering 1996,43(11):1120–1125. 10.1109/10.541254
Chen S-W: A two-stage discrimination of cardiac arrhythmias using a total least squares-based Prony modeling algorithm. IEEE Transactions on Biomedical Engineering 2000,47(10):1317–1327. 10.1109/10.871404
Ripley KL, Bump TE, Arzbaecher RC: Evaluation of techniques for recognition of ventricular arrhythmias by implanted devices. IEEE Transactions on Biomedical Engineering 1989,36(6):618–624. 10.1109/10.29456
Zhang X-S, Zhu Y-S, Thakor NV, Wang Z-Z: Detecting ventricular tachycardia and fibrillation by complexity measure. IEEE Transactions on Biomedical Engineering 1999,46(5):548–555. 10.1109/10.759055
Xu L, Zhang D, Wang K, Wang L: Arrhythmic pulses detection using Lempel-Ziv complexity analysis. EURASIP Journal on Applied Signal Processing 2006, 2006: 12 pages.
Coast DA, Stern RM, Cano GG, Briller SA: An approach to cardiac arrhythmia analysis using hidden Markov models. IEEE Transactions on Biomedical Engineering 1990,37(9):826–836. 10.1109/10.58593
Lempel A, Ziv J: On the complexity of finite sequences. IEEE Transactions on Information Theory 1976,22(1):75–81. 10.1109/TIT.1976.1055501
Fukunaga K: Introduction to Statistical Pattern Recognition. Academic Press, New York, NY, USA; 1990.
Wald AJ: Sequential Analyses. Dove, New York, NY, USA; 1947.
About this article
Cite this article
Chen, S. Complexity-Measure-Based Sequential Hypothesis Testing for Real-Time Detection of Lethal Cardiac Arrhythmias. EURASIP J. Adv. Signal Process. 2007, 020957 (2006). https://doi.org/10.1155/2007/20957
- Ventricular Tachycardia
- Ventricular Arrhythmia
- Ventricular Fibrillation
- Algorithm Training
- Data Segment