Fernando Soares Schlindwein

University of Leicester | LE · Department of Engineering

Objective To improve prediction of sudden cardiac death (SCD) in patients with ischaemic cardiomyopathy (ICM). Electrical heterogeneity is known to contribute to risk of SCD. We have previously developed Regional Restitution Instability Index (R2I2), an ECG-based biomarker, which quantifies cardiac electrical instability by measuring heterogeneity...

Ablation of persistent atrial fibrillation (persAF) targeting complex fractionated atrial electrograms (CFAEs) detected by automated algorithms has produced conflicting outcomes in previous electrophysiological studies. We hypothesize that the differences in these algorithms could lead to discordant CFAE classifications by the available mapping sys...

Background: identification of arrhythmogenic regions remains a challenge in persistent atrial fibrillation (persAF). Frequency and phase analysis allows identification of potential ablation targets. Objective: This study aims to investigate the spatiotemporal association between dominant frequency (DF) and re-entrant phase activation areas. Met...

The unstable temporal behavior of atrial electrical activity during persistent atrial fibrillation (persAF) might influence ablation target identification, which could explain the conflicting persAF ablation outcomes in previous studies. We sought to investigate the temporal behavior and consistency of atrial electrogram (AEG) fractionation using d...

Purpose: Recent investigations failed to reproduce the positive rotor-guided ablation outcomes shown by initial studies for treating persistent atrial fibrillation (persAF). Phase singularity (PS) is an important feature for AF driver detection, but algorithms for automated PS identification differ. We aim to investigate the performance of four dif...

Purpose: Several studies have emphasised the significance of high dominant frequency (HDF) and rotors in the perpetuation of AF. However, the colocalisation relationship between both attributes is not completely understood yet. In this study, we aim to evaluate the spatial distributions of HDF regions and rotor sites within the left atrium (LA) pre...

Abstract: Background: 60% of patients that receive implantable cardioverter defibrillators (ICDs) for primary prevention do not receive therapy during the lifespan of the ICD, whilst up to 50% of cardiac arrests occur in individuals that are considered low risk by conventional criteria. Machine learning offers a unique data driven approach to risk...

Purpose Sites of highest dominant frequency (HDF) are implicated by many proposed mechanisms underlying persistent atrial fibrillation (persAF). We hypothesized that prospectively identifying and ablating dynamic left atrial HDF sites would favorably impact the electrophysiological substrate of persAF. We aim to assess the feasibility of prospectiv...

Introduction: The purpose of this study is to assess the ability of two new ECG markers (Regional Repolarisation Instability Index (R2I2) and Peak Electrical Restitution Slope) to predict sudden cardiac death (SCD) or ventricular arrhythmia (VA) events in patients with ischaemic cardiomyopathy undergoing implantation of an implantable cardioverter...

Growth restricted children have higher predisposition of developing metabolic syndrome, type-2 diabetes, hypertension and cardiovascular problems in later life. Numerous intelligence systems that have proved their effectiveness for detection of cardiac abnormalities to support medical diagnosis. Previous studies used heart rate variability (HRV) an...

Identifying ablation targets for persistent atrial fibrillation (PersAF) is still challenging despite attempts to guide ablation using Highest Dominant Frequency (HDF) and rotors.

Automatic detection and classification of cardiac disorders play a critical role in the analysis of clinical electro-cardiogram (ECG). Deep learning methods are effective for automated feature extraction and have shown promising results in ECG classification. In this work, we proposed a deep spatio-temporal ECG network (ST-ECGNet) to extract robust...

Electrocardiographic imaging (ECGI) is a technique to reconstruct noninvasively the electrical activity on the heart surface from body-surface potential recordings and geometric information of the torso and the heart. ECGI has shown scientific and clinical value when used to characterize and treat both atrial and ventricular arrhythmias. Regardin...

Abstract Purpose: Identifying targets for catheter ablation remains challenging in persistent atrial fibrillation (persAF). The dominant frequency (DF) of atrial electrograms during atrial fibrillation (AF) is believed to primarily reflect local activation. Highest DF (HDF) might be responsible for the initiation and perpetuation of persAF. However...

Growth restricted children have higher predisposition of developing metabolic syndrome, type-2 diabetes, hypertension and cardiovascular problems in later life. Researchers have developed numerous intelligence systems that have proved their effectiveness for detection of cardiac abnormalities to support medical diagnosis. Previous studies used hear...

Automated detection and classification of clinical elec-trocardiogram (ECG) play a critical role in the analysis of cardiac disorders. Deep learning is effective for automated feature extraction and has shown promising results in ECG classification. Most of these methods, however, assume that multiple cardiac disorders are mutually exclusive. In th...

Changes in atrial fibrillation cycle length (AF-CL) are broadly used as a 'ground truth' to assess the effect of substrate modification during AF ablation. This work sought to optimize thresholds for changes in coronary sinus CL (CS-CL) after local ablation using different atrial electrogram (AEG)-derived markers. 834 AEGs were collected from 11 pa...

In-silico cardiac patches with a non-conductive fibrotic areas were used to investigate the occurrence and characteristics of rotors described by phase singularities (PSs). A rotor was generated in a virtual tissue patch represented by a Courtemanche model adapted to mimic AF conditions. Non-conductive fibrotic elements were incorporated around the...

Objective: Ablation treatment for persistent atrial fibrillation (persAF) remains challenging due to the absence of a "ground truth" for atrial substrate characterization and the presence of multiple mechanisms driving the arrhythmia. We implemented an unsupervised classification to identify AEG clusters with similar patterns, which were then vali...

This study presents an electrocardiogram (ECG) monitoring and processing system which can observe subjects in real time and display the resultant ECG signals on a computer for observation. The primary application is for the remote observation of cardiac patients. This paper aims to determine its reliability by analysing its portability and wireless...

Funding Acknowledgements This work was supported by the NIHR Leicester Biomedical Research Centre. XL was funded by MRC(MR/S037306/1) and BHF (PG/18/33/33780) Background It remains controversial as to whether rotors detected using phase mapping during persistent atrial fibrillation (persAF) represent main drivers of the underlying mechanism as oth...

BACKGROUND Identifying ablation targets for persistent atrial fibrillation (persAF) is still challenging. Targeting high frequency sites has been previously proposed as a treatment strategy. Recently, attention has been given to the hypothesis that ablating rotor regions might be a good strategy for treating persAF. STUDY OBJECTIVES This study aim...

The nonlinear analysis of biological time series provides new possibilities to improve computer aided diagnostic systems, traditionally based on linear techniques. The Cardiotocography (CTG) examination records simultaneoulsly the fetal heart rate (FHR) and the maternal uterine contractions (UC). This paper shows, at first, that both signals presen...

We read with great interest the study by Baher et al.1 Their work helps to consolidate the use of recurrence quantification analysis (RQA) in the investigation of cardiac dynamics during atrial fibrillation (AF). It also motivates further discussion on creative methods and biomarkers for studying such complex cardiac disorder.As clearly pointed out...

Introduction: Early detection of sepsis are critical for improving outcomes. We trained a convolutional neural network (CNN) for early detection of sepsis. Methods: Hourly physiological data of 40 variables from 40,336 patients admitted to intensive care unit (ICU) were used. The database appeared imbalanced, and the class (positive) with small num...

Atrial fibrillation (AF) catheter ablation success depends on the possibility to accurately determine areas on the atrial endocardium at which AF activation originates. One way to determine if major AF activation pathways originate at identified source is through causality analysis. This work assessed to what extent left atrial highest dominant fre...

Understanding the spatiotemporal behaviour of ‘rotors’ in human atrial fibrillation (AF) is important for using them as targets for ablation. However, the spatiotemporal stability of such targets during long recording remains unclear. This study aims to track the spatiotemporal stability of rotors over 5 min time interval during persistent atrial f...

The visual analysis of Cardiotocographic (CTG) examinations is a very subjective process. The accurate detection and segmentation of the fetal heart rate (FHR) features and their correlation with the uterine contractions (UC) in time allow a better diagnostic and the possibility of anticipation of many problems related to fetal distress. This paper...

Theresa May has been causing irregular heartbeats nationally. Yet, atrial fibrillation (AF) is the most frequently diagnosed heart condition involving an irregular heart rate (also known as Heart Arrhythmia). It can lead to a stroke or heart failure. With over 1.3 million sufferers in the UK, its treatment development is rather important. Aims of t...

Non-invasive analysis of atrial fibrillation (AF) using body surface mapping (BSM) has gained significant interest, with attempts at interpreting atrial spectro-temporal parameters from body surface signals. As these body surface signals could be affected by properties of the torso volume conductor, this interpretation is not always straightforward...

Introduction The temporal behavior of atrial electrograms (AEGs) collected during persistent atrial fibrillation (persAF) directly affects ablative treatment outcomes. We investigated different durations of AEGs collected during persAF using recurrence quantification analysis (RQA). Methods 797 bipolar AEGs with different durations (from 0.5 s to...

Atrial fibrillation (AF) is regarded as a complex arrhythmia, with one or more co-existing mechanisms, resulting in an intricate structure of atrial activations. Fractionated atrial electrograms (AEGs) were thought to represent arrhythmogenic tissue, and hence have been suggested as targets for radiofrequency ablation. However, current methods for...

Sudden cardiac death (SCD) is a major cause of mortality presenting a significant unmet clinical need. Patients at risk of SCD are implanted with implantable cardioverter defibrillators (ICDs) according to international guidelines based on clinical trial evidence. ICDs are not inexpensive and not without problem in terms of inappropriate shocks and...

Prospective non-invasive evaluation of a novel ECG-based restitution biomarker for prediction of sudden cardiac death risk in ischaemic cardiomyopathy S. Siddiqui1; WB. Nicolson2; X. Li1; R. Somani2; AJ. Sandilands2; PJ. Stafford2; FS. Schlindwein1; GA. Ng11University of Leicester, Leicester, United Kingdom; 2University Hospitals of Leicester NHS T...

Atrial fibrillation (AF) is a cardiac arrhythmia characterised by turbulent and disorganised atrial activations. The temporal behaviour of atrial electrograms (AEGs) collected during persistent AF (persAF) directly affects its treatment based on radiofrequency ablation. In the present work, different durations of AEGs collected during persAF were i...

Introduction: Early data has shown beneficial outcomes after rotor-guided catheter ablation in persistent atrial fibrillation (persAF). We aim to investigate the rotor characteristics at ablation sites that terminated AF (terminators) compared to those at sites that did not (non-terminators). Methods: 10 patients undergoing left atrial (LA) persAF...

Introduction: Identification of areas for successful ablation in patients with persistent atrial fibrillation (persAF) remains challenging. We aim to improve ablation target identification using frequency and phase mapping to better understand the underlying mechanisms of persAF. Methods: A quasi-real-time software platform with graphic user interf...

Introduction: Identification of areas for successful ablation in patients with persistent atrial fibrillation (persAF) remains challenging. We aim to improve ablation target identification using frequency and phase mapping to better understand the underlying mechanisms of persAF. Methods: A quasi-real-time software platform with graphic user interf...

Introduction: Early data has shown beneficial outcomes after rotor-guided catheter ablation in persistent atrial fibrillation (persAF). We aim to investigate the rotor characteristics at ablation sites that terminated AF (terminators) compared to those at sites that did not (non-terminators). Methods: 10 patients undergoing left atrial (LA) persAF...

Purpose – Complex fractionated atrial electrograms (CFAE)-guided ablation after pulmonary vein isolation (PVI) has been used for persistent atrial fibrillation (persAF) therapy. This strategy, however, has shown suboptimal outcomes due to, among other factors, undetected changes in the atrial tissue following PVI. In the present work, we investigat...