James A. Rosengarten

A Low-Complexity ECG Feature Extraction Algorithm for Mobile Healthcare Applications

This paper introduces a low-complexity algorithm for the extraction of the fiducial points from the electrocardiogram (ECG). The application area we consider is that of remote cardiovascular monitoring, where continuous sensing and processing takes place in low-power, computationally constrained devices, thus the power consumption and complexity of the processing algorithms should remain at a minimum level. Under this context, we choose to employ the discrete wavelet transform (DWT) with the Haar function being the mother wavelet, as our principal analysis method. From the modulus-maxima analysis on the DWT coefficients, an approximation of the ECG fiducial points is extracted. These initial findings are complimented with a refinement stage, based on the time-domain morphological properties of the ECG, which alleviates the decreased temporal resolution of the DWT. The resulting algorithm is a hybrid scheme of time- and frequency-domain signal processing. Feature extraction results from 27 ECG signals from QTDB were tested against manual annotations and used to compare our approach against the state-of-the art ECG delineators. In addition, 450 signals from the 15-lead PTBDB are used to evaluate the obtained performance against the CSE tolerance limits. Our findings indicate that all but one CSE limits are satisfied. This level of performance combined with a complexity analysis, where the upper bound of the proposed algorithm, in terms of arithmetic operations, is calculated as 2.423N+214 additions and 1.093N+12 multiplications for N ≤ 861 or 2.553N+102 additions and 1.093N+10 multiplications for N > 861 (N being the number of input samples), reveals that the proposed method achieves an ideal tradeoff between computational complexity and performance, a key requirement in remote cardiovascular disease monitoring systems.

Late gadolinium enhancement cardiac magnetic resonance imaging for the prediction of ventricular tachyarrhythmic events: a meta-analysis

Approaches to the risk stratification for sudden cardiac death (SCD) remain unsatisfactory. Although late gadolinium enhancement cardiac magnetic resonance imaging (LGE‐CMR) for SCD risk stratification has been evaluated in several studies, small sample size has limited their clinical validity. We performed this meta‐analysis to better gauge the predictive accuracy of LGE‐CMR for SCD risk stratification.

A Time-Domain Morphology and Gradient based algorithm for ECG feature extraction

A Time Domain Morphology and Gradient (TDMG) based algorithm is presented in this paper for the extraction of all the fiducial time instances from a single PQRST complex. By estimating these characteristic points, all clinically important temporal ECG parameters can be calculated. The proposed algorithm is based on a combination of extrema detection and slope information, with the use of adaptive thresholding to achieve the extraction of 11 time instances. A pre-processing step removes any noise and artefacts from the captured ECG signal. Initially, the position of the R-wave and the QRS-complex boundaries are localized in time. Following, by focusing on the part of the signal that precedes and succeeds the QRS-complex, the remaining fiducial points from the P and T waves are estimated. The initial localisation of the wave boundaries is complimented by amendment steps which are introduced to cater for atypical wave morphologies, indicative of particular heart conditions. The proposed algorithm is evaluated on the QT and PTB databases against medically annotated ECG samples. The results demonstrate the ability of the proposed scheme, to estimate the ECG fiducial points with acceptable accuracy from a single-lead ECG signal. In addition, this investigation reveals the ability of the TDMG algorithm to perform accurately irrespective of the lead chosen, the different disease categories and the sampling frequency of the captured ECG signal.

Implantable cardioverter defibrillator therapy in paediatric practice: a single-centre UK experience with focus on subcutaneous defibrillation

AIMS Sudden cardiac death (SCD) risk can be managed by implantable cardioverter defibrillators (ICD). Defibrillation shocks can be delivered via ICD generator and/or intracardiac or subcutaneous coil configurations. We present our single-centre use of childhood ICDs. METHODS AND RESULTS Twenty-three patients had ICD implantation, with median age and weight of 12.96 years and 41.35 kg. Indications included eight long QT; four hypertrophic cardiomyopathy; three Brugada syndrome; two idiopathic ventricular fibrillation; two post-congenital heart repair; two family history of SCD with abnormal repolarization; one catecholaminergic polymorphic ventricular tachycardia; and one left ventricle non-compaction. Twelve had out of hospital cardiac arrests prior to implantation. Techniques included 13 conventional ICD implants (pre-pectoral device with endocardial leads), 7 with subcutaneous defibrillation coils (sensing via epicardial or endocardial leads tunnelled to the ICD), and 3 with exclusive subcutaneous ICD (sensing and defibrillation via the same subcutaneous lead). Satisfactory defibrillation efficacy and ventricular arrhythmia sensing was confirmed at implantation. Follow-up ranged from 0.17 to 11.08 years. One child died with the ICD in situ. Ten children received appropriate shocks; five on more than one occasion. Five received inappropriate shocks (for inappropriate recognition of sinus tachycardia or supraventricular tachycardia). Five children underwent six further interventions; all had intracardiac leads. CONCLUSION Innovative shock delivery systems can be used in children requiring an ICD. The insertion technique and device used need to accommodate the age and weight of the child, and concomitant need for pacing therapy. We have demonstrated effective defibrillation with shocks delivered via configurations employing subcutaneous coils in children.

Fragmented QRS for the prediction of sudden cardiac death: a meta-analysis.

AIMS Risk stratification of sudden cardiac death (SCD) is challenging. Fragmented QRS (fQRS) is proposed as a non-invasive electrocardiogram marker associated with mortality and SCD. Results from individual studies including small numbers of patients are discrepant. We therefore performed a meta-analysis of studies evaluating fQRS as a risk stratification tool to predict all-cause mortality and SCD. METHODS AND RESULTS Electronic databases and bibliographies were systematically searched (1996-2014). Twelve studies (5009 patients) recruiting patients with coronary artery disease or non-ischaemic cardiomyopathy met our inclusion criteria. Fragmented QRS was associated with an all-cause mortality relative risk of 1.71 (CI 1.02-2.85) and a relative risk of SCD of 2.20 (CI 1.05-4.62). Subgroup analysis demonstrated greater mortality and SCD risk in those with left ventricular ejection fraction >35% and SCD risk in those with QRS duration <120 ms. CONCLUSION Fragmented QRS is associated with all-cause mortality and the occurrence of SCD and may be suited as a marker of SCD risk. The incremental benefit of fQRS should be assessed in a randomized, prospective setting.

Left Ventricular Scar Burden Specifies the Potential for Ventricular Arrhythmogenesis: An LGE-CMR Study

Late Gadolinium Enhancement and Arrhythmias. Introduction: The extent of left ventricular (LV) scar, characterized by late gadolinium enhancement cardiac MRI (LGE‐CMR), has been shown to predict the occurrence of ventricular arrhythmias in implantable cardioverter defibrillator (ICD) recipients. However, the specificity of LGE‐CMR for sudden cardiac death (SCD) versus non‐SCD is unclear. The aim of this retrospective, observational study was to evaluate this relationship in a cohort of ICD recipients.

On the Detection of Myocadial Scar Based on ECG/VCG Analysis

In this paper, we address the problem of detecting the presence of a myocardial scar from the standard electrocardiogram (ECG)/vectorcardiogram (VCG) recordings, giving effort to develop a screening system for the early detection of the scar in the point-of-care. Based on the pathophysiological implications of scarred myocardium, which results in disordered electrical conduction, we have implemented four distinct ECG signal processing methodologies in order to obtain a set of features that can capture the presence of the myocardial scar. Two of these methodologies are: 1) the use of a template ECG heartbeat, from records with scar absence coupled with wavelet coherence analysis and 2) the utilization of the VCG are novel approaches for detecting scar presence. Following, the pool of extracted features is utilized to formulate a support vector machine classification model through supervised learning. Feature selection is also employed to remove redundant features and maximize the classifiers performance. The classification experiments using 260 records from three different databases reveal that the proposed system achieves 89.22% accuracy when applying tenfold cross validation, and 82.07% success rate when testing it on databases with different inherent characteristics with similar levels of sensitivity (76%) and specificity (87.5%).

Development of an Automated Updated Selvester QRS Scoring System Using SWT-Based QRS Fractionation Detection and Classification

The Selvester score is an effective means for estimating the extent of myocardial scar in a patient from low-cost ECG recordings. Automation of such a system is deemed to help implementing low-cost high-volume screening mechanisms of scar in the primary care. This paper describes, for the first time to the best of our knowledge, an automated implementation of the updated Selvester scoring system for that purpose, where fractionated QRS morphologies and patterns are identified and classified using a novel stationary wavelet transform (SWT)-based fractionation detection algorithm. This stage informs the two principal steps of the updated Selvester scoring scheme-the confounder classification and the point awarding rules. The complete system is validated on 51 ECG records of patients detected with ischemic heart disease. Validation has been carried out using manually detected confounder classes and computation of the actual score by expert cardiologists as the ground truth. Our results show that as a stand-alone system it is able to classify different confounders with 94.1% accuracy whereas it exhibits 94% accuracy in computing the actual score. When coupled with our previously proposed automated ECG delineation algorithm, that provides the input ECG parameters, the overall system shows 90% accuracy in confounder classification and 92% accuracy in computing the actual score and thereby showing comparable performance to the stand-alone system proposed here, with the added advantage of complete automated analysis without any human intervention.

Can QRS scoring predict left ventricular scar and clinical outcomes

AIMS Identifying patients with potential to benefit from implantable cardioverter defibrillator (ICD) therapy is challenging. Myocardial scar detected using cardiovascular myocardial resonance imaging with late gadolinium enhancement (CMR-LGE) is associated with ventricular arrhythmia. Its use is constrained due to limited availability, unlike electrocardiogram (ECG) which is widely available. Selvester QRS scoring detects scar, although the reported performance varies. The study aims were to determine whether QRS score (a) detects scar (b) varies with scar characteristics, and (c) can meaningfully predict sudden cardiac death. METHODS AND RESULTS We investigated 64 consecutive ICD recipients (age 66 ± 11 years, 80% male, median left ventricular ejection fraction 30%) with coronary artery disease who had undergone CMR-LGE prior to device implantation, over 4 years in a single centre (2006-2009). A modified QRS score was measured on the ECG performed prior to ICD implantation. Clinical end points were (i) appropriate ICD therapy and (ii) all cause mortality. QRS score was associated with CMR scar (r = 0.42, P = 0.001) and scar surface area (r = 0.41, P = 0.001), but not subendocardial scar. Strongest correlation was seen in those patients with transmural scar only (r = 0.62, P = 0.01). During 42 ± 13 months follow-up, QRS score was not predictive of appropriate ICD therapy, but was significantly related to all cause mortality (hazard ratio = 1.16; confidence interval = 1.03-1.30; P = 0.01). CONCLUSION QRS scoring performed best in quantifying transmural scar, and shows association with medium-term mortality risk, but not with risk of ventricular arrhythmia. It may be that the score is best suited as a risk stratifier of those with least potential to benefit from ICD.

The relationship between left ventricular scar and ventricular repolarization in patients with coronary artery disease: insights from late gadolinium enhancement magnetic resonance imaging.

AIMS The markers of ventricular repolarization corrected QT interval (QTc), QT dispersion (QTD) and Tpeak-to-Tend interval (Tpeak-end) have shown an association with sudden cardiac death (SCD) in the general population. However, their mechanistic relationship with SCD is unclear. The study aim was to evaluate the relationship between QTc, QTD, and Tpeak-end, and the extent and distribution of left ventricular (LV) scar in patients with coronary artery disease at high SCD risk. METHODS AND RESULTS We included 64 consecutive implantable cardioverter defibrillator (ICD) recipients (66 ± 11 years, 80% male, median left ventricular ejection fraction 30%) who had undergone late gadolinium enhancement cardiac magnetic resonance (CMR) imaging prior to device implantation over 4 years. Scar was quantified using the CMR images and characterized in terms of percent LV scar and number of LV segments with subendocardial/transmural scar. Repolarization parameters were measured on an electrocardiogram performed prior to ICD implantation. After adjustment for potential confounders there was a strong association between the number of limited subendocardial (1-25% transmurality) scar segments and QTc (P = 0.003), QTD (P = 0.002), and Tpeak-end (P = 0.008). However, there was no association between the repolarization parameters and percent LV scar or the amount of transmural scar. During a mean follow-up of 19 ± 10 months 19 (30%) patients received appropriate ICD therapy, but none of the repolarization parameters were associated with its occurrence. CONCLUSION In this pilot study there was a strong association between limited subendocardial LV scar and prolonged QTc, QTD, and Tpeak-end. However, there was no association between any of these repolarization markers and the delivery of appropriate ICD therapy.