Abstract
Abnormal intra-QRS potentials (AIQPs) are commonly observed in patients at high risk for ventricular tachycardia. We present a method for approximating a measured QRS complex using a non-linear neural network with all radial basis functions having the same smoothness. We extracted the high frequency, but low amplitude intra-QRS potentials using the approximation error to identify possible ventricular tachycardia. With a specified number of neurons, we performed an orthogonal least squares algorithm to determine the center of each Gaussian radial basis function. We found that the AIQP estimation error arising from part of the normal QRS complex could cause clinicians to misjudge patients with ventricular tachycardia. Our results also show that it is possible to correct this misjudgment by combining multiple AIQP parameters estimated using various spread parameters and numbers of neurons. Clinical trials demonstrate that higher AIQP-to-QRS ratios in the X, Y and Z leads are visible in patients with ventricular tachycardia than in normal subjects. A linear combination of 60 AIQP-to-QRS ratios can achieve 100% specificity, 90% sensitivity, and 95.8% total prediction accuracy for diagnosing ventricular tachycardia.
Highlights
As a noninvasive diagnostic tool for detecting ventricular arrhythmia, a signal-averaged electrocardiogram can be employed to detect low amplitude, high frequency ventricular late potentials (VLPs) at the end of a QRS complex, or abnormal intra-QRS potentials (AIQPs)
We expected that a normal QRS complex could be synthesized by an RBF neural network, and low amplitude, high frequency AIQP would account for the observed approximation error
This study has successfully demonstrated the usefulness of a proposed RBF neural network for diagnosing ventricular tachycardia (VT) patients at high risk of ventricular arrhythmias
Summary
As a noninvasive diagnostic tool for detecting ventricular arrhythmia, a signal-averaged electrocardiogram can be employed to detect low amplitude, high frequency ventricular late potentials (VLPs) at the end of a QRS complex, or abnormal intra-QRS potentials (AIQPs). VLPs have been reliably applied to assessing risk among VT patients recovering from myocardial infarction, diagnosing patients who are unconsciousness for unknown reasons, and detecting ischemic heart diseases [1]. They have been applied to diagnosing patients with thalassemia [2], epilepsy [3], cardiac sarcoidosis [4]. The presence of an arrhythmic substrate leads to a reentrant excitation, and may even cause lethal ventricular arrhythmia, including ventricular tachycardia (VT) and ventricular fibrillation [1]. Several studies have pointed out that a QRS complex has extended duration owing to Sensors 2016, 16, 1580; doi:10.3390/s16101580 www.mdpi.com/journal/sensors
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