A real-time signal processing software package for the electrophysiology laboratory

BACKGROUND

Real-time signal processing has to date been difficult to implement in the clinical electrophysiology laboratory. To date, no open access software solutions are available in electrophysiology (EP) laboratories to facilitate real-time intraprocedural signal analysis. We aimed to develop an open access, scalable Python plug-in to allow real-time signal processing during human EP procedures.

METHODS AND RESULTS

A Python-based plug in for the widely available EnsiteX mapping system was developed. This plug-in utilized the LiveSync feature of the system to allow real-time signal analysis. An open access library was developed to allow end-users to implement real-time signal analysis using this platform, implemented in the Python programming language https://github.com/anand9176/WaveWatch5000Public.

CONCLUSION

We have developed and demonstrated the feasibility of a readily scalable and open-access Python-based plug in to an electroanatomic mapping system (EnSiteX) to allow real-time processing and display of electrogram (EGM) based information for the procedural electrophysiologist to view intraprocedurally in the electrophysiology laboratory. The availability, to the clinician, of traditional and novel EGM-based metrics at the time of intervention, such as atrial fibrillation ablation, allows for key mechanistic insights into critical unresolved questions regarding arrhythmia mechanism.

Assessing Torque Transfer in Conduction System Pacing: Development and Evaluation of an Ex Vivo Model

BACKGROUND

Conduction system pacing (CSP) faces challenges in achieving reliable and safe deployments. Complex interactions between tissue and lead tip can result in endocardial entanglement, a drill effect that prevents penetration. No verified ex vivo model exists to quantitatively assess this relationship.

OBJECTIVES

The purpose of this study was to quantitatively characterize CSP lead tip to tissue responses for 4 commonly used leads.

METHODS

CSP leads (from Medtronic, Biotronik, Boston Scientific, and Abbott) were examined for helix rotation efficiency in ex vivo ovine right ventricular septa. A custom jig was utilized for rotation measurements. Fifteen turns were executed, documenting tissue-interface changes every 90° using high-resolution photography. Response curves (input rotation vs helix rotation) were evaluated using piecewise linear regression, with a focus on output vs input response slopes and torque breakpoint events.

RESULTS

We analyzed 3,840 quarter-turn CSP insertions with 4 different lead types. Helix rotations were consistently less than input: Abbott Tendril = 0.21:1, Medtronic 3830 = 0.21:1, Biotronik Solia = 0.47:1, and Boston Scientific Ingevity = 0.56:1. Torque breakpoint events were observed on average 7.22 times per insertion (95% CI: 6.08-8.35; P = NS) across all leads. In 57.8% of insertions (37 of 64), uncontrolled torque breakpoint events occurred, signaling unexpected excess helix rotations.

CONCLUSIONS

Using a robust ex vivo model, we revealed a muted helix rotation response compared with input turns on the lead, and frequent torque change events during insertion. This is critical for CSP implanters, emphasizing the potential for unexpected torque breakpoint events, and suggesting the need for novel lead designs or deployment methods to enhance CSP efficiency and safety.

Constructing bilayer and volumetric atrial models at scale

To enable large in silico trials and personalized model predictions on clinical timescales, it is imperative that models can be constructed quickly and reproducibly. First, we aimed to overcome the challenges of constructing cardiac models at scale through developing a robust, open-source pipeline for bilayer and volumetric atrial models. Second, we aimed to investigate the effects of fibres, fibrosis and model representation on fibrillatory dynamics. To construct bilayer and volumetric models, we extended our previously developed coordinate system to incorporate transmurality, atrial regions and fibres (rule-based or data driven diffusion tensor magnetic resonance imaging (MRI)). We created a cohort of 1000 biatrial bilayer and volumetric models derived from computed tomography (CT) data, as well as models from MRI, and electroanatomical mapping. Fibrillatory dynamics diverged between bilayer and volumetric simulations across the CT cohort (correlation coefficient for phase singularity maps: left atrial (LA) 0.27 ± 0.19, right atrial (RA) 0.41 ± 0.14). Adding fibrotic remodelling stabilized re-entries and reduced the impact of model type (LA: 0.52 ± 0.20, RA: 0.36 ± 0.18). The choice of fibre field has a small effect on paced activation data (less than 12 ms), but a larger effect on fibrillatory dynamics. Overall, we developed an open-source user-friendly pipeline for generating atrial models from imaging or electroanatomical mapping data enabling in silico clinical trials at scale (https://github.com/pcmlab/atrialmtk).

Infra-Red Imaging to Detect Respirator Leak in Healthcare Workers During Fit-Testing Clinic

OBJECTIVE

This study addressed the problem of objectively detecting leaks in P2 respirators at point of use, an essential component for healthcare workers' protection. To achieve this, we explored the use of infra-red (IR) imaging combined with machine learning algorithms on the thermal gradient across the respirator during inhalation.

RESULTS

The study achieved high accuracy in predicting pass or fail outcomes of quantitative fit tests for flat-fold P2 FFRs. The IR imaging methods surpassed the limitations of self fit-checking.

CONCLUSIONS

The integration of machine learning and IR imaging on the respirator itself demonstrates promise as a more reliable alternative for ensuring the proper fit of P2 respirators. This innovative approach opens new avenues for technology application in occupational hygiene and emphasizes the need for further validation across diverse respirator styles.

SIGNIFICANCE STATEMENT

Our novel approach leveraging infra-red imaging and machine learning to detect P2 respirator leaks represents a critical advancement in occupational safety and healthcare workers' protection.

Percolation theory as a conceptual framework to explain spontaneous atrial fibrillation termination: a pilot study

Atrial fibrillation (AF) strikingly possesses the ability to abruptly transition into more organized electrical activity and spontaneously terminate, even after persisting for long periods. Despite being central to the clinical behavior and treatment of AF, these phenomena remain incompletely understood. In this paper, we hypothesized that the spontaneous termination of AF may represent a type of percolation phase transition, which is more likely to occur when a domain spanning cluster of refractory sites in the atrium are connected (called a 'percolation cluster'). This was assessed in n=50 computational simulations of AF developed using the Aliev-Panfilov (APV) 2-dimensional cell model. In self-terminating simulations of AF, it was found that the average refractory cluster size, χ(p) (median: 647.7), and the largest refractory cluster size, M1 (median: 1702.3), abruptly increased just prior to AF spontaneously terminating, indicating the onset of the formation of a domain spanning percolation cluster. In contrast, simulations of sustained AF did not demonstrate an increase in χ(p) (median: 463.0) and M1 (median: 1448.2). Self-terminating AF simulations also demonstrated hallmark properties characteristic of a percolation phase transition, such as an abrupt increase in χ(p) at the critical occupation probability pc. The cluster size distribution was also shown to obey a power law for various occupation probabilities p, also indicative of a percolation phase transition. Collectively, these properties suggests that the spontaneous termination of AF could be a form of percolation phase transition, which could provide new insights for AF treatment.

Markov modeling of phase singularity interaction effects in human atrial and ventricular fibrillation

Atrial and ventricular fibrillation (AF/VF) are characterized by the repetitive regeneration of topological defects known as phase singularities (PSs). The effect of PS interactions has not been previously studied in human AF and VF. We hypothesized that PS population size would influence the rate of PS formation and destruction in human AF and VF, due to increased inter-defect interaction. PS population statistics were studied in computational simulations (Aliev-Panfilov), human AF and human VF. The influence of inter-PS interactions was evaluated by comparison between directly modeled discrete-time Markov chain (DTMC) transition matrices of the PS population changes, and M/M/∞ birth-death transition matrices of PS dynamics, which assumes that PS formations and destructions are effectively statistically independent events. Across all systems examined, PS population changes differed from those expected with M/M/∞. In human AF and VF, the formation rates decreased slightly with PS population when modeled with the DTMC, compared with the static formation rate expected through M/M/∞, suggesting new formations were being inhibited. In human AF and VF, the destruction rates increased with PS population for both models, with the DTMC rate increase exceeding the M/M/∞ estimates, indicating that PS were being destroyed faster as the PS population grew. In human AF and VF, the change in PS formation and destruction rates as the population increased differed between the two models. This indicates that the presence of additional PS influenced the likelihood of new PS formation and destruction, consistent with the notion of self-inhibitory inter-PS interactions.

Role of interatrial conduction in atrial fibrillation. Mechanistic insights from renewal theory-based fibrillatory dynamic analysis

Background

Interatrial conduction has been postulated to play an important role in atrial fibrillation (AF). The pathways involved in interatrial conduction during AF remain incompletely defined.

Objective

We recently showed physiological assessment of fibrillatory dynamics could be performed using renewal theory, which determines rates of phase singularity formation (λ_f) and destruction (λ_d). Using the renewal approach, we aimed to understand the role of the interatrial septum and other electrically coupled regions during AF.

Method

RENEWAL-AF is a prospective multicenter observational study recruiting AF ablation patients (ACTRN 12619001172190). We studied unipolar electrograms obtained from 16 biatrial locations prior to ablation using a 16-electrode Advisor HD Grid catheter. Renewal rate constants λ_f and λ_d were calculated, and the relationships between these rate constants in regions of interatrial connectivity were examined.

Results

Forty-one AF patients (28.5% female) were recruited. A positive linear correlation was observed between λ_f and λ_d (1) across the interatrial septum (λ_f r² = 0.5, P < .001, λ_d r² = 0.45, P < .001), (2) in regions connected by the Bachmann bundle (right atrial appendage–left atrial appendage λ_f r² = 0.29, P = .001; λ_d r² = 0.2, P = .008), and (3) across the inferior interatrial routes (cavotricuspid isthmus–left atrial septum λ_f r² = 0.67, P < .001; λ_d r² = 0.55, P < .001). Persistent AF status and left atrial volume were found to be important effect modifiers of the degree of interatrial renewal rate statistical correlation.

Conclusion

Our findings support the role of interseptal statistically determined electrical disrelation in sustaining AF. Additionally, renewal theory identified preferential conduction through specific interatrial pathways during fibrillation. These findings may be of importance in identifying clinically significant targets for ablation in AF patients.

Understanding the origins of the basic equations of statistical fibrillatory dynamics

The mechanisms governing cardiac fibrillation remain unclear; however, it most likely represents a form of spatiotemporal chaos with conservative system dynamics. Renewal theory has recently been suggested as a statistical formulation with governing equations to quantify the formation and destruction of wavelets and rotors in fibrillatory dynamics. In this perspective Review, we aim to explain the origin of the renewal theory paradigm in spatiotemporal chaos. The ergodic nature of pattern formation in spatiotemporal chaos is demonstrated through the use of three chaotic systems: two classical systems and a simulation of cardiac fibrillation. The logistic map and the baker's transformation are used to demonstrate how the apparently random appearance of patterns in classical chaotic systems has macroscopic parameters that are predictable in a statistical sense. We demonstrate that the renewal theory approach developed for cardiac fibrillation statistically predicts pattern formation in these classical chaotic systems. Renewal theory provides governing equations to describe the apparently random formation and destruction of wavelets and rotors in atrial fibrillation (AF) and ventricular fibrillation (VF). This statistical framework for fibrillatory dynamics provides a holistic understanding of observed rotor and wavelet dynamics and is of conceptual significance in informing the clinical and mechanistic research of the rotor and multiple-wavelet mechanisms of AF and VF.

Vomiting, electrolyte disturbance, and medications; the perfect storm for acquired long QT syndrome and cardiac arrest: a case report

Background

Acquired long QT syndrome is an important and preventable cause of cardiac arrest. Certain medications and electrolyte disturbance are common contributors, and often coexist. In this case, we report five contributors to cardiac arrest.

Case presentation

This case is of a 51-year-old Caucasian female patient who presented with vomiting associated with hypokalemia and hypomagnesemia. She subsequently received ondansetron and metoclopramide, on the background of chronic treatment with fluoxetine. She then suffered an in-hospital monitored cardiac arrest, with features of long QT and torsades de pointes retrospectively noted on her prearrest electrocardiogram. She was diagnosed with acquired long QT syndrome, and her QT interval later normalized after removal of offending causes.

Conclusions

This case highlights the importance of proper consideration prior to prescribing QT prolonging medications, especially in patients who have other risk factors for prolonged QT, such as electrolyte disturbances and pretreatment with QT prolonging medications.

The inspection paradox: An important consideration in the evaluation of rotor lifetimes in cardiac fibrillation

Background and Objective: Renewal theory is a statistical approach to model the formation and destruction of phase singularities (PS), which occur at the pivots of spiral waves. A common issue arising during observation of renewal processes is an inspection paradox, due to oversampling of longer events. The objective of this study was to characterise the effect of a potential inspection paradox on the perception of PS lifetimes in cardiac fibrillation. Methods: A multisystem, multi-modality study was performed, examining computational simulations (Aliev-Panfilov (APV) model, Courtmanche-Nattel model), experimentally acquired optical mapping Atrial and Ventricular Fibrillation (AF/VF) data, and clinically acquired human AF and VF. Distributions of all PS lifetimes across full epochs of AF, VF, or computational simulations, were compared with distributions formed from lifetimes of PS existing at 10,000 simulated commencement timepoints. Results: In all systems, an inspection paradox led towards oversampling of PS with longer lifetimes. In APV computational simulations there was a mean PS lifetime shift of +84.9% (95% CI, ± 0.3%) (p < 0.001 for observed vs overall), in Courtmanche-Nattel simulations of AF +692.9% (95% CI, ±57.7%) (p < 0.001), in optically mapped rat AF +374.6% (95% CI, ± 88.5%) (p = 0.052), in human AF mapped with basket catheters +129.2% (95% CI, ±4.1%) (p < 0.05), human AF-HD grid catheters 150.8% (95% CI, ± 9.0%) (p < 0.001), in optically mapped rat VF +171.3% (95% CI, ±15.6%) (p < 0.001), in human epicardial VF 153.5% (95% CI, ±15.7%) (p < 0.001). Conclusion: Visual inspection of phase movies has the potential to systematically oversample longer lasting PS, due to an inspection paradox. An inspection paradox is minimised by consideration of the overall distribution of PS lifetimes.

WITHDRAWN: Impact of Racial Differences on the Epidemiology and Clinical Outcomes of Atrial Fibrillation

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Reconceptualising Atrial Fibrillation Using Renewal Theory: A Novel Approach to the Assessment of Atrial Fibrillation Dynamics

Despite a century of research, the mechanisms of AF remain unresolved. A universal motif within AF research has been unstable re-entry, but this remains poorly characterised, with competing key conceptual paradigms of multiple wavelets and more driving rotors. Understanding the mechanisms of AF is clinically relevant, especially with regard to treatment and ablation of the more persistent forms of AF. Here, the authors outline the surprising but reproducible finding that unstable re-entrant circuits are born and destroyed at quasi-stationary rates, a finding based on a branch of mathematics known as renewal theory. Renewal theory may be a way to potentially unify the multiple wavelet and rotor theories. The renewal rate constants are potentially attractive because they are temporally stable parameters of a defined probability distribution (the exponential distribution) and can be estimated with precision and accuracy due to the principles of renewal theory. In this perspective review, this new representational architecture for AF is explained and placed into context, and the clinical and mechanistic implications are discussed.

Spatial concentration and distribution of phase singularities in human atrial fibrillation: Insights for the AF mechanism

BACKGROUND

Atrial fibrillation (AF) is characterized by the repetitive regeneration of unstable rotational events, the pivot of which are known as phase singularities (PSs). The spatial concentration and distribution of PSs have not been systematically investigated using quantitative statistical approaches.

OBJECTIVES

We utilized a geospatial statistical approach to determine the presence of local spatial concentration and global clustering of PSs in biatrial human AF recordings.

METHODS

64-electrode conventional basket (~5 min, n = 18 patients, persistent AF) recordings were studied. Phase maps were produced using a Hilbert-transform based approach. PSs were characterized spatially using the following approaches: (i) local "hotspots" of high phase singularity (PS) concentration using Getis-Ord Gi* (Z ≥ 1.96, P ≤ .05) and (ii) global spatial clustering using Moran's I (inverse distance matrix).

RESULTS

Episodes of AF were analyzed from basket catheter recordings (H: 41 epochs, 120 000 s, n = 18 patients). The Getis-Ord Gi* statistic showed local PS hotspots in 12/41 basket recordings. As a metric of spatial clustering, Moran's I showed an overall mean of 0.033 (95% CI: 0.0003-0.065), consistent with the notion of complete spatial randomness.

CONCLUSION

Using a systematic, quantitative geospatial statistical approach, evidence for the existence of spatial concentrations ("hotspots") of PSs were detectable in human AF, along with evidence of spatial clustering. Geospatial statistical approaches offer a new approach to map and ablate PS clusters using substrate-based approaches.

Atrial fibrosis and substrate based characterization in atrial fibrillation: Time to move forwards

Atrial fibrillation (AF) is the most commonly encountered cardiac arrhythmia in clinical practice. However, current therapeutic interventions for atrial fibrillation have limited clinical efficacy as a consequence of major knowledge gaps in the mechanisms sustaining atrial fibrillation. From a mechanistic perspective, there is increasing evidence that atrial fibrosis plays a central role in the maintenance and perpetuation of atrial fibrillation. Electrophysiologically, atrial fibrosis results in alterations in conduction velocity, cellular refractoriness, and produces conduction block promoting meandering, unstable wavelets and micro-reentrant circuits. Clinically, atrial fibrosis has also linked to poor clinical outcomes including AF-related thromboembolic complications and arrhythmia recurrences post catheter ablation. In this article, we review the pathophysiology behind the formation of fibrosis as AF progresses, the role of fibrosis in arrhythmogenesis, surrogate markers for detection of fibrosis using cardiac magnetic resonance imaging, echocardiography and electroanatomic mapping, along with their respective limitations. We then proceed to review the current evidence behind therapeutic interventions targeting atrial fibrosis, including drugs and substrate-based catheter ablation therapies followed by the potential future use of electro phenotyping for AF characterization to overcome the limitations of contemporary substrate-based methodologies.

M/M/Infinity Birth-Death Processes - A Quantitative Representational Framework to Summarize and Explain Phase Singularity and Wavelet Dynamics in Atrial Fibrillation

Rationale

A quantitative framework to summarize and explain the quasi-stationary population dynamics of unstable phase singularities (PS) and wavelets in human atrial fibrillation (AF) is at present lacking. Building on recent evidence showing that the formation and destruction of PS and wavelets in AF can be represented as renewal processes, we sought to establish such a quantitative framework, which could also potentially provide insight into the mechanisms of spontaneous AF termination.

Objectives

Here, we hypothesized that the observed number of PS or wavelets in AF could be governed by a common set of renewal rate constants λ _f (for PS or wavelet formation) and λ _d (PS or wavelet destruction), with steady-state population dynamics modeled as an M/M/∞ birth-death process. We further hypothesized that changes to the M/M/∞ birth-death matrix would explain spontaneous AF termination.

Methods and Results

AF was studied in in a multimodality, multispecies study in humans, animal experimental models (rats and sheep) and Ramirez-Nattel-Courtemanche model computer simulations. We demonstrated: (i) that λ _f and λ _d can be combined in a Markov M/M/∞ process to accurately model the observed average number and population distribution of PS and wavelets in all systems at different scales of mapping; and (ii) that slowing of the rate constants λ _f and λ _d is associated with slower mixing rates of the M/M/∞ birth-death matrix, providing an explanation for spontaneous AF termination.

Conclusion

M/M/∞ birth-death processes provide an accurate quantitative representational architecture to characterize PS and wavelet population dynamics in AF, by providing governing equations to understand the regeneration of PS and wavelets during sustained AF, as well as providing insight into the mechanism of spontaneous AF termination.

Prospective cross-sectional study using Poisson renewal theory to study phase singularity formation and destruction rates in atrial fibrillation (RENEWAL-AF): Study design

BACKGROUND

Unstable functional reentrant circuits known as rotors have been consistently observed in atrial fibrillation and are mechanistically believed critical to the maintenance of the arrhythmia. Recently, using a Poisson renewal theory-based quantitative framework, we have demonstrated that rotor formation (λf) and destruction rates (λd) can be measured using in vivo electrophysiologic data. However, the association of λf and λd with clinical, electrical, and structural markers of atrial fibrillation phenotype is unknown.

METHODS

RENEWAL-AF is a multicenter prospective cross-sectional study recruiting adult patients with paroxysmal or persistent atrial fibrillation undergoing clinically indicated catheter ablation. Patients will undergo intraprocedural electrophysiologic atrial fibrillation mapping, with λf and λd to be determined from 2-minute unipolar electrogram recordings acquired before ablation. The primary objective will be to determine the association of λf and λd as markers of fibrillatory dynamics with clinical, electrical, and structural markers of atrial fibrillation clinical phenotype, measured by preablation transthoracic echocardiogram and cardiac magnetic resonance imaging. An exploratory objective is the noninvasive assessment of λf and λd using surface ECG characteristics via a machine learning approach.

RESULTS

Not applicable.

CONCLUSION

This pilot study will provide insight into the correlation between λf/λd with clinical, electrophysiological, and structural markers of atrial fibrillation phenotype and provide a foundation for the development of noninvasive assessment of λf/λd using surface ECG characteristics will help expand the use of λf/λd in clinical practice.

Renewal Theory as a Universal Quantitative Framework to Characterize Phase Singularity Regeneration in Mammalian Cardiac Fibrillation

BACKGROUND

Despite a century of research, no clear quantitative framework exists to model the fundamental processes responsible for the continuous formation and destruction of phase singularities (PS) in cardiac fibrillation. We hypothesized PS formation/destruction in fibrillation could be modeled as self-regenerating Poisson renewal processes, producing exponential distributions of interevent times governed by constant rate parameters defined by the prevailing properties of each system.

METHODS

PS formation/destruction were studied in 5 systems: (1) human persistent atrial fibrillation (n=20), (2) tachypaced sheep atrial fibrillation (n=5), (3) rat atrial fibrillation (n=4), (5) rat ventricular fibrillation (n=11), and (5) computer-simulated fibrillation. PS time-to-event data were fitted by exponential probability distribution functions computed using maximum entropy theory, and rates of PS formation and destruction (λ_f/λ_d) determined. A systematic review was conducted to cross-validate with source data from literature.

RESULTS

In all systems, PS lifetime and interformation times were consistent with underlying Poisson renewal processes (human: λ_f, 4.2%/ms±1.1 [95% CI, 4.0-5.0], λ_d, 4.6%/ms±1.5 [95% CI, 4.3-4.9]; sheep: λ_f, 4.4%/ms [95% CI, 4.1-4.7], λ_d, 4.6%/ms±1.4 [95% CI, 4.3-4.8]; rat atrial fibrillation: λ_f, 33%/ms±8.8 [95% CI, 11-55], λ_d, 38%/ms [95% CI, 22-55]; rat ventricular fibrillation: λ_f, 38%/ms±24 [95% CI, 22-55], λ_f, 46%/ms±21 [95% CI, 31-60]; simulated fibrillation λ_d, 6.6-8.97%/ms [95% CI, 4.1-6.7]; R²≥0.90 in all cases). All PS distributions identified through systematic review were also consistent with an underlying Poisson renewal process.

CONCLUSIONS

Poisson renewal theory provides an evolutionarily preserved universal framework to quantify formation and destruction of rotational events in cardiac fibrillation.

Temporal stability and specificity of high bipolar electrogram entropy regions in sustained atrial fibrillation: Implications for mapping

BACKGROUND

The potential utility of entropy (En) for atrial fibrillation (AF) mapping has been demonstrated in previous studies by multiple groups, where an association between high bipolar electrogram (EGM) entropy and the pivot of rotors has been shown. Though En is potentially attractive new approach to ablation, no studies have examined its temporal stability and specificity, which are critical to the application of entropy to clinical ablation. In the current study, we sought to objectively measure the temporal stability and specificity of bipolar EGM entropy in medium to long term recordings using three studies: i) a human basket catheter AF study, ii) a tachypaced sheep AF study and iii) a computer simulation study.

OBJECTIVE

To characterize the temporal dynamics and specificity of Approximate, Sample and Shannon entropy (ApEn/SampEn/ShEn) in human (H), sheep (S), and computer simulated AF.

METHODS

64-electrode basket bi-atria sustained AF recordings (H:15 min; S:40 min) were separated into 5 s segments. ShEn/ApEn/SampEn were computed, and co-registered with NavX 3D maps. Temporal stability was determined in terms of: (i) global pattern stability of En and (ii) the relative stability the top 10% of En regions. To provide mechanistic insights into underlying mechanisms, stability characteristics were compared to models depicting various propagation patterns. To verify these results, cross-validation was performed across multiple En algorithms, across species, and compared with dominant frequency (DF) temporal characteristics. The specificity of En was also determined by looking at the association of En to rotors and areas of wave cross propagation.

RESULTS

Episodes of AF were analysed (H:26 epochs, 6040 s; S:15 epochs, 14,160 s). The global pattern of En was temporally unstable (CV- H:13.42% ± 4.58%; S:14.13% ± 8.13%; Friedman- H: p > 0.001; S: p > 0.001). However, within this dynamic flux, the top 10% of ApEn/SampEn/ShEn regions were relatively temporally stable (Kappa >0.6) whilst the top 10% of DF regions were unstable (Kappa <0.06). In simulated AF scenarios, the experimental data were optimally reproduced in the context of an AF pattern with stable rotating waves surrounded by wavelet breakup (Kappa: 0.610; p < 0.0001).

CONCLUSION

En shows global temporal instability, however within this dynamic flux, the top 10% regions exhibited relative temporal stability. This suggests that high En regions may be an appealing ablation target. Despite this, high En was associated with not just the pivot of rotors but also with areas of cross propagation, which suggests the need for future work before clinical application is possible.

Information Theory and Atrial Fibrillation (AF): A Review

Atrial Fibrillation (AF) is the most common cardiac rhythm disorder seen in hospitals and in general practice, accounting for up to a third of arrhythmia related hospitalizations. Unfortunately, AF treatment is in practice complicated by the lack of understanding of the fundamental mechanisms underlying the arrhythmia, which makes detection of effective ablation targets particularly difficult. Various approaches to AF mapping have been explored in the hopes of better pinpointing these effective targets, such as Dominant Frequency (DF) analysis, complex fractionated electrograms (CFAE) and unipolar reconstruction (FIRM), but many of these methods have produced conflicting results or require further investigation. Exploration of AF using information theoretic-based approaches may have the potential to provide new insights into the complex system dynamics of AF, whilst also providing the benefit of being less reliant on empirically derived definitions in comparison to alternate mapping approaches. This work provides an overview of information theory and reviews its applications in AF analysis, with particular focus on AF mapping. The works discussed in this review demonstrate how understanding AF from a signal property perspective can provide new insights into the arrhythmic phenomena, which may have valuable clinical implications for AF mapping and ablation in the future.

A comparison of independent component analysis algorithms and measures to discriminate between EEG and artifact components

Independent Component Analysis (ICA) is a powerful statistical tool capable of separating multivariate scalp electrical signals into their additive independent or source components, specifically EEG or electroencephalogram and artifacts. Although ICA is a widely accepted EEG signal processing technique, classification of the recovered independent components (ICs) is still flawed, as current practice still requires subjective human decisions. Here we build on the results from Fitzgibbon et al. [1] to compare three measures and three ICA algorithms. Using EEG data acquired during neuromuscular paralysis, we tested the ability of the measures (spectral slope, peripherality and spatial smoothness) and algorithms (FastICA, Infomax and JADE) to identify components containing EMG. Spatial smoothness showed differentiation between paralysis and pre-paralysis ICs comparable to spectral slope, whereas peripherality showed less differentiation. A combination of the measures showed better differentiation than any measure alone. Furthermore, FastICA provided the best discrimination between muscle-free and muscle-contaminated recordings in the shortest time, suggesting it may be the most suited to EEG applications of the considered algorithms. Spatial smoothness results suggest that a significant number of ICs are mixed, i.e. contain signals from more than one biological source, and so the development of an ICA algorithm that is optimised to produce ICs that are easily classifiable is warranted.