This article explores the ability of multivariate autoregressive model(MAR)and scalar AR model to extract the features from two-lead electrocardiogram signals in order to classify certain cardiac arrhythmias.The classification performance of four different ECG feature sets based on the model coefficients are shown.The data in the analysis including normal sinus rhythm, atria premature contraction,premature ventricular contraction,ventricular tachycardia,ventricular fibrillation and superventricular tachyeardia is obtained from the MIT-BIH database.The classification is performed using a quadratic diacriminant function.The results show the MAR coefficients produce the best results among the four ECG representations and the MAR modeling is a useful classification and diagnosis tool.
展开▼
机译:The Impacts of Margin Trading on Rate of Return and Volatility in the Stock Market: A Study Using the SVAR Model and Panel Regressions =融资对股价收益与波动的影响特征研究——基于SVAR模型与面板模型的实证分析
机译:Kinetics of mn-based sorbents for hot gas desulfurization: Task 2 - exploratory experimental studies. Quarterly report, march 15, 1996--June 15, 1996