Stability analysis on the effects of heart rate variability and premature activation of atrial ECG dynamics using ARMAX model.

Abstract

The cellular action potential of cardiac muscles generates Electrocardiogram (ECG) signals. Disturbances in cardiac cells are determined by analyzing the stability of ECG intervals. The PTa Interval (PTaI) of ECG represents the atrial Action Potential Duration (APD) and the evaluation of the causes of PTaI instability can predict the onset of arrhythmia. This study developed an Autoregressive Moving Average with Exogenous Input (ARMAX) model to explore the roles of Heart Rate Variability (HRV) and Premature Activation (PA) in PTaI dynamics using PTaI and PP Interval (PPI) as exogenous inputs. Minute ECG signals were collected from twenty Normal Sinus Rhythm (NSR) and ten Atrial Tachycardia (AT) volunteers. The EDAN PC ECG system was used in the Modified Limb Lead (MLL)configuration to evaluate instability. The instabilities of PTaI were found at the minimum model orders (Amin) of 10 and 11, in the NSR and AT groups, respectively. In the NSR group, the predominant reason for PTaI instability was HRV, whereas among AT patients, it was largely due to PA that preceded the onset of AT. The proposed model showed better prediction of PTaI with minimum Mean Square Error(MSE) between the measured and predicted PTa Intervals (PTaIs). The factor that led to PTaI instability in AT patients was found to be different from that of the NSR group. The frequency of PA (fPA) was found to contribute more in the AT than the NSR group. The developed ARMAX model was better in predicting instability of atrial ECG dynamics in both groups than other autoregressive models currently in use.