sEMG as complementary tool for VFSS: A synchronized study in patients with neurogenic oropharyngeal dysphagia.

The neurogenic oropharyngeal dysphagia is a prevalent functional swallowing disorder resulting from neurological causes. The conventional diagnosis involves ionizing radiation in Videofluoroscopy Swallowing Studies (VFSS). Surface electromyography (sEMG) offers a non-invasive alternative by recording muscle activity. This research compares bolus passage timing through anatomical structures using VFSS and sEMG-related activation times. Fifty confirmed oropharyngeal dysphagia patients underwent synchronized VFSS and sEMG, evaluating muscle groups during cracker and fluid ingestion. sEMG revealed activation patterns in masseters, suprahyoid, and infrahyoid muscles, occurring before bolus passage through the mandibular line and concluding near the upper esophageal sphincter complex. sEMG identified differences in dysphagia severity (EAT-10 score), age, and diagnosis, contrasting VFSS results. Results indicate potential complementarity between sEMG and VFSS for dysphagia screening, diagnosis, and monitoring.

Named Entity Recognition in Electronic Health Records: A Methodological Review.

OBJECTIVES: A substantial portion of the data contained in Electronic Health Records (EHR) is unstructured, often appearing as free text. This format restricts its potential utility in clinical decision-making. Named entity recognition (NER) methods address the challenge of extracting pertinent information from unstructured text. The aim of this study was to outline the current NER methods and trace their evolution from 2011 to 2022. METHODS: We conducted a methodological literature review of NER methods, with a focus on distinguishing the classification models, the types of tagging systems, and the languages employed in various corpora. RESULTS: Several methods have been documented for automatically extracting relevant information from EHRs using natural language processing techniques such as NER and relation extraction (RE). These methods can automatically extract concepts, events, attributes, and other data, as well as the relationships between them. Most NER studies conducted thus far have utilized corpora in English or Chinese. Additionally, the bidirectional encoder representation from transformers using the BIO tagging system architecture is the most frequently reported classification scheme. We discovered a limited number of papers on the implementation of NER or RE tasks in EHRs within a specific clinical domain. CONCLUSIONS: EHRs play a pivotal role in gathering clinical information and could serve as the primary source for automated clinical decision support systems. However, the creation of new corpora from EHRs in specific clinical domains is essential to facilitate the swift development of NER and RE models applied to EHRs for use in clinical practice.

Synchronization between videofluoroscopic swallowing study and surface electromyography in patients with neurological involvement presenting symptoms of dysphagia / Sincronización entre la videodeglución y la electromiografía de superficie en pacientes con afectación neurológica y síntomas de disfagia

Introduction: Dysphagia is defined as the difficulty in transporting food and liquids from the mouth to the stomach. The gold standard to diagnose this condition is the videofluoroscopic swallowing study. However, it exposes patients to ionizing radiation. Surface electromyography is a non-radioactive alternative for dysphagia evaluation that records muscle electrical activity during swallowing. Objective: To evaluate the relationship between the relative activation times of the muscles involved in the oral and pharyngeal phases of swallowing and the kinematic events detected in the videofluoroscopy. Materials and methods: Electromiographic signals from ten patients with neurological involvement who presented symptoms of dysphagia were analyzed simultaneously with videofluoroscopy. Patients were given 5 ml of yogurt, 10 ml of water, and 3 g of crackers. Masseter, suprahyoid, and infrahyoid muscle groups were studied bilaterally. The bolus transit through the mandibular line, vallecula, and the cricopharyngeus muscle was analyzed in relation to the onset and offset times of each muscle group activation. Results: The average time of the pharyngeal phase was 0.89 ± 0.12 s. Muscle activation was mostly observed prior to the bolus transit through the mandibular line and vallecula. The end of the muscle activity suggested that the passage of the bolus through the cricopharyngeus muscle was almost complete. Conclusión: The muscle activity times, duration of the pharyngeal phase, and sequence of the muscle groups involved in swallowing were determined using sEMG validated with the videofluoroscopic swallowing study.

Introducción. La disfagia se define como la dificultad para movilizar la comida desde la boca hasta el estómago. La prueba diagnóstica para esta condición es la videofluoroscopia, la cual no es totalmente inocua pues utiliza radiación ionizante. La electromiografía de superficie registra la actividad eléctrica de los músculos de manera no invasiva, por lo que puede considerarse como una alternativa para evaluar la deglución y estudiar la disfagia. Objetivo. Evaluar la relación entre los tiempos relativos de activación de los músculos implicados en la fase oral y faríngea de la deglución, con los movimientos registrados durante la videofluoroscopia. Materiales y métodos. Se analizaron las señales de la electromiografía de superficie de 10 pacientes neurológicos con síntomas de disfagia, captadas en forma simultánea con la videofluoroscopia. Se suministraron 5 ml de yogur y 10 ml de agua, y 3 g de galleta. Se estudiaron bilateralmente los grupos musculares maseteros, suprahioideos e infrahioideos. Se analizó el paso del bolo por la línea mandibular, las valleculas y el músculo cricofaríngeo, correlacionándolo con el tiempo inicial y el final de la activación de cada uno de los grupos musculares. Resultados. El tiempo promedio de la fase faríngea fue de 0,89 ± 0,12 s. En la mayoría de los casos, hubo activación muscular antes del paso por la línea mandibular y las valleculas. La terminación de la actividad muscular parece corresponder al momento en que se completa el paso del bolo alimenticio por el músculo cricofaríngeo. Conclusión. Se determinaron los tiempos de actividad muscular, la duración de la fase faríngea y la secuencia de la activación de los grupos musculares involucrados en la deglución, mediante electromiografía de superficie, validada con la videofluoroscopia.

Sincronización entre la videodeglución y la electromiografía de superficie en pacientes con afectación neurológica y síntomas de disfagia / Synchronization between videofluoroscopic swallowing study and surface electromyography in patients with neurological involvement presenting symptoms of dysphagia

Introducción. La disfagia se define como la dificultad para movilizar la comida desde la boca hasta el estómago. La prueba diagnóstica para esta condición es la videofluoroscopia, la cual no es totalmente inocua pues utiliza radiación ionizante. La electromiografía de superficie registra la actividad eléctrica de los músculos de manera no invasiva, por lo que puede considerarse como una alternativa para evaluar la deglución y estudiar la disfagia. Objetivo. Evaluar la relación entre los tiempos relativos de activación de los músculos implicados en la fase oral y faríngea de la deglución, con los movimientos registrados durante la videofluoroscopia. Materiales y métodos. Se analizaron las señales de la electromiografía de superficie de 10 pacientes neurológicos con síntomas de disfagia, captadas en forma simultánea con la videofluoroscopia. Se suministraron 5 ml de yogur y 10 ml de agua, y 3 g de galleta. Se estudiaron bilateralmente los grupos musculares maseteros, suprahioideos e infrahioideos. Se analizó el paso del bolo por la línea mandibular, las valleculas y el músculo cricofaríngeo, correlacionándolo con el tiempo inicial y el final de la activación de cada uno de los grupos musculares. Resultados. El tiempo promedio de la fase faríngea fue de 0,89 ± 0,12 s. En la mayoría de los casos, hubo activación muscular antes del paso por la línea mandibular y las valleculas. La terminación de la actividad muscular parece corresponder al momento en que se completa el paso del bolo alimenticio por el músculo cricofaríngeo. Conclusión. Se determinaron los tiempos de actividad muscular, la duración de la fase faríngea y la secuencia de la activación de los grupos musculares involucrados en la deglución, mediante electromiografía de superficie, validada con la videofluoroscopia.

Introduction: Dysphagia is defined as the difficulty in transporting food and liquids from the mouth to the stomach. The gold standard to diagnose this condition is the videofluoroscopic swallowing study. However, it exposes patients to ionizing radiation. Surface electromyography is a non-radioactive alternative for dysphagia evaluation that records muscle electrical activity during swallowing. Objective: To evaluate the relationship between the relative activation times of the muscles involved in the oral and pharyngeal phases of swallowing and the kinematic events detected in the videofluoroscopy. Materials and methods: Electromiographic signals from ten patients with neurological involvement who presented symptoms of dysphagia were analyzed simultaneously with videofluoroscopy. Patients were given 5 ml of yogurt, 10 ml of water, and 3 g of crackers. Masseter, suprahyoid, and infrahyoid muscle groups were studied bilaterally. The bolus transit through the mandibular line, vallecula, and the cricopharyngeus muscle was analyzed in relation to the onset and offset times of each muscle group activation. Results: The average time of the pharyngeal phase was 0.89 ± 0.12 s. Muscle activation was mostly observed prior to the bolus transit through the mandibular line and vallecula. The end of the muscle activity suggested that the passage of the bolus through the cricopharyngeus muscle was almost complete. Conclusion: The muscle activity times, duration of the pharyngeal phase, and sequence of the muscle groups involved in swallowing were determined using sEMG validated with the videofluoroscopic swallowing study.

Directed Functional Coordination Analysis of Swallowing Muscles in Healthy and Dysphagic Subjects by Surface Electromyography.

Swallowing is a complex sequence of highly regulated and coordinated skeletal and smooth muscle activity. Previous studies have attempted to determine the temporal relationship between the muscles to establish the activation sequence pattern, assessing functional muscle coordination with cross-correlation or coherence, which is seriously impaired by volume conduction. In the present work, we used conditional Granger causality from surface electromyography signals to analyse the directed functional coordination between different swallowing muscles in both healthy and dysphagic subjects ingesting saliva, water, and yoghurt boluses. In healthy individuals, both bilateral and ipsilateral muscles showed higher coupling strength than contralateral muscles. We also found a dominant downward direction in ipsilateral supra and infrahyoid muscles. In dysphagic subjects, we found a significantly higher right-to-left infrahyoid, right ipsilateral infra-to-suprahyoid, and left ipsilateral supra-to-infrahyoid interactions, in addition to significant differences in the left ipsilateral muscles between bolus types. Our results suggest that the functional coordination analysis of swallowing muscles contains relevant information on the swallowing process and possible dysfunctions associated with dysphagia, indicating that it could potentially be used to assess the progress of the disease or the effectiveness of rehabilitation therapies.

Machine learning based analysis of speech dimensions in functional oropharyngeal dysphagia.

BACKGROUND AND OBJECTIVE: The normal swallowing process requires a complex coordination of anatomical structures driven by sensory and cranial nerves. Alterations in such coordination cause swallowing malfunctions, namely dysphagia. The dysphagia screening methods are quite subjective and experience dependent. Bearing in mind that the swallowing process and speech production share some anatomical structures and mechanisms of neurological control, this work aims to evaluate the suitability of automatic speech processing and machine learning techniques for screening of functional dysphagia. METHODS: Speech recordings were collected from 46 patients with functional oropharyngeal dysphagia produced by neurological causes, and 46 healthy controls. The dimensions of speech including phonation, articulation, and prosody were considered through different speech tasks. Specific features per dimension were extracted and analyzed using statistical tests. Machine learning models were applied per dimension via nested cross-validation. Hyperparameters were selected using the AUC - ROC as optimization criterion. RESULTS: The Random Forest in the articulation related speech tasks retrieved the highest performance measures (AUC=0.86±0.10, sensitivity=0.91±0.12) for individual analysis of dimensions. In addition, the combination of speech dimensions with a voting ensemble improved the results, which suggests a contribution of information from different feature sets extracted from speech signals in dysphagia conditions. CONCLUSIONS: The proposed approach based on speech related models is suitable for the automatic discrimination between dysphagic and healthy individuals. These findings seem to have potential use in the screening of functional oropharyngeal dysphagia in a non-invasive and inexpensive way.

Functional Atrial Endocardial-Epicardial Dissociation in Patients With Structural Heart Disease Undergoing Cardiac Surgery.

OBJECTIVES: The goal of this study was to describe functional endocardial-epicardial dissociation (FEED), signal complexities, and three-dimensional activation dynamics of the human atrium with structural heart disease (SHD). BACKGROUND: SHD commonly predisposes to arrhythmias. Although progressive remodeling is implicated, direct demonstration of FEED in the human atrium has not been reported previously. METHODS: Simultaneous intraoperative mapping of the endocardial and epicardial lateral right atrial wall was performed by using 2 high-density grid catheters during sinus rhythm, pacing drive (600 ms and 400 ms cycle length), and premature extrastimulation (PES). Unipolar electrograms (EGMs) were exported into custom-made software for activation and phase mapping. Difference of ≥20 ms between paired endocardial and epicardial electrodes defined dissociation. EGMs with ≥3 deflections were classified as fractionated. RESULTS: Sixteen patients (mean age 60.5 ± 4.1 years; 18.7% with a history of atrial fibrillation) with SHD (43% ischemia, 57% valvular disease) were included. A total of 9,218 EGMs were analyzed. Compared with sinus rhythm, phase and activation analyses showed significant FEED during pacing at 600 ms and 400 ms (phase mapping 22.4% vs. 10% [p < 0.0001] and 25.8% vs. 10% [p < 0.0001], respectively; activation mapping 25.4% vs. 7.8% [p < 0.0001] and 27.7% vs. 7.8% [p < 0.0001]) and PES (phase mapping 34% vs. 10% [p < 0.0001]; activation mapping 29.5% vs. 7.8% [p < 0.0001]). Fractionated EGMs occurred significantly more during PES compared with sinus rhythm (50.2% vs. 39.5%; p < 0.0001). Activation patterns differed significantly during pacing drive and PES, with preferential epicardial exit during the latter (15.9% vs. 13.8%; p = 0.046). CONCLUSIONS: Simultaneous endocardial-epicardial mapping revealed significant FEED with signal fractionation and preferential epicardial breakthroughs with PES. Such complex three-dimensional interaction in electrical activation provides mechanistic insights into atrial arrhythmogenesis with SHD.

Electroanatomical mapping based on discrimination of electrograms clusters for localization of critical sites in atrial fibrillation.

Locating critical sites on the atrial surface during AF to guide the ablation procedures is an open problem. Electrogram-guided approaches have been proposed. However, electrograms (EGM) are complex and not well-described type of signals and anatomically-based pulmonary vein isolation remains been recommended as the cornerstone procedure. We introduce a method that builds an electroanatomical map to visualize the distribution of different morphological patterns of the EGM signals over the atrial surface. The proposed scheme uses EGM signals recorded with a commercial cardiac mapping. Likewise, two morphological and two non-linear features are computed from each single EGM. Patterns are discriminated using a semi-supervised clustering approach that does not need a priory definition of EGM morphologies or classes. The method was tested under two scenarios: a set of EGM signals recorded in AF patients and a set of signals obtained from 2D simulations of atrial conduction sustained by rotors. Our method was able to locate the clusters in a map of the atrial surface of each patient. These locations allow the specialist to study the distribution of critical AF sites. The method was able to locate the pivot point of the rotors in the 2D models. Our results suggest that the proposed method is a potential assisting tool for guided ablation procedures. Further clinical studies are needed to establish the relationship between clusters and arrhythmogenic substrates in AF, and to validate the usefulness of the method to locate critical conduction sites in patients.

Entropy Mapping Approach for Functional Reentry Detection in Atrial Fibrillation: An In-Silico Study.

Catheter ablation of critical electrical propagation sites is a promising tool for reducing the recurrence of atrial fibrillation (AF). The spatial identification of the arrhythmogenic mechanisms sustaining AF requires the evaluation of electrograms (EGMs) recorded over the atrial surface. This work aims to characterize functional reentries using measures of entropy to track and detect a reentry core. To this end, different AF episodes are simulated using a 2D model of atrial tissue. Modified Courtemanche human action potential and Fenton-Karma models are implemented. Action potential propagation is modeled by a fractional diffusion equation, and virtual unipolar EGM are calculated. Episodes with stable and meandering rotors, figure-of-eight reentry, and disorganized propagation with multiple reentries are generated. Shannon entropy ( S h E n ), approximate entropy ( A p E n ), and sample entropy ( S a m p E n ) are computed from the virtual EGM, and entropy maps are built. Phase singularity maps are implemented as references. The results show that A p E n and S a m p E n maps are able to detect and track the reentry core of rotors and figure-of-eight reentry, while the S h E n results are not satisfactory. Moreover, A p E n and S a m p E n consistently highlight a reentry core by high entropy values for all of the studied cases, while the ability of S h E n to characterize the reentry core depends on the propagation dynamics. Such features make the A p E n and S a m p E n maps attractive tools for the study of AF reentries that persist for a period of time that is similar to the length of the observation window, and reentries could be interpreted as AF-sustaining mechanisms. Further research is needed to determine and fully understand the relation of these entropy measures with fibrillation mechanisms other than reentries.

Automatic detection of oral and pharyngeal phases in swallowing using classification algorithms and multichannel EMG.

Swallowing is a complex process that involves sequential voluntary and involuntary muscle contractions. Malfunctioning of swallowing related muscles could lead to dysphagia. However, there is a lack of standardized and non-invasive methods that support and improve the diagnosis and ambulatory care. This paper presents a classification scheme of two swallowing phases (oral and pharyngeal) based on signals of surface electromyography (sEMG). Eight acquisition channels recorded the EMG activity of 47 healthy subjects while they swallowed water, yogurt and saliva. Every signal was processed, segmented and labeled with background activity, oral or pharyngeal classes. Nine time domain and four frequency domain features were extracted from the segments, assessed individually and then compared in groups according to a correlation analysis. A support vector machine (SVM) with radial basis function kernel and a feedforward artificial neural network (ANN) with one hidden layer were used as classifiers. Different hyperparameters of the SVM and number of hidden neurons of the ANN were assessed for the proposed scheme. The recognition accuracy of SVM (92,03%) was higher than ANN's (90,26%). Time domain features were found to have better capability of representation than their frequency domain counterpart. Nevertheless, expanding the feature space improved the performance of the classifiers. Experimental results show that proposed sEMG-based method can correctly distinguish between oral and pharyngeal swallowing phases and can be used for assessment of continuous swallowing tasks. This paper extends previous reported findings to small muscles with low signal-to-noise ratio and high crosstalk acquired in multichannel systems.

Improving surface EMG burst detection in infrahyoid muscles during swallowing using digital filters and discrete wavelet analysis.

The visual inspection is a widely used method for evaluating the surface electromyographic signal (sEMG) during deglutition, a process highly dependent of the examiners expertise. It is desirable to have a less subjective and automated technique to improve the onset detection in swallowing related muscles, which have a low signal-to-noise ratio. In this work, we acquired sEMG measured in infrahyoid muscles with high baseline noise of ten healthy adults during water swallowing tasks. Two methods were applied to find the combination of cutoff frequencies that achieve the most accurate onset detection: discrete wavelet decomposition based method and fixed steps variations of low and high cutoff frequencies of a digital bandpass filter. Teager-Kaiser Energy operator, root mean square and simple threshold method were applied for both techniques. Results show a narrowing of the effective bandwidth vs. the literature recommended parameters for sEMG acquisition. Both level 3 decomposition with mother wavelet db4 and bandpass filter with cutoff frequencies between 130 and 180Hz were optimal for onset detection in infrahyoid muscles. The proposed methodologies recognized the onset time with predictive power above 0.95, that is similar to previous findings but in larger and more superficial muscles in limbs.

Semi-supervised clustering of fractionated electrograms for electroanatomical atrial mapping.

BACKGROUND: Electrogram-guided ablation procedures have been proposed as an alternative strategy consisting of either mapping and ablating focal sources or targeting complex fractionated electrograms in atrial fibrillation (AF). However, the incomplete understanding of the mechanism of AF makes difficult the decision of detecting the target sites. To date, feature extraction from electrograms is carried out mostly based on the time-domain morphology analysis and non-linear features. However, their combination has been reported to achieve better performance. Besides, most of the inferring approaches applied for identifying the levels of fractionation are supervised, which lack of an objective description of fractionation. This aspect complicates their application on EGM-guided ablation procedures. METHODS: This work proposes a semi-supervised clustering method of four levels of fractionation. In particular, we make use of the spectral clustering that groups a set of widely used features extracted from atrial electrograms. We also introduce a new atrial-deflection-based feature to quantify the fractionated activity. Further, based on the sequential forward selection, we find the optimal subset that provides the highest performance in terms of the cluster validation. The method is tested on external validation of a labeled database. The generalization ability of the proposed training approach is tested to aid semi-supervised learning on unlabeled dataset associated with anatomical information recorded from three patients. RESULTS: A joint set of four extracted features, based on two time-domain morphology analysis and two non-linear dynamics, are selected. To discriminate between four considered levels of fractionation, validation on a labeled database performs a suitable accuracy (77.6 %). Results show a congruence value of internal validation index among tested patients that is enough to reconstruct the patterns over the atria to located critical sites with the benefit of avoiding previous manual classification of AF types. CONCLUSIONS: To the best knowledge of the authors, this is the first work reporting semi-supervised clustering for distinguishing patterns in fractionated electrograms. The proposed methodology provides high performance for the detection of unknown patterns associated with critical EGM morphologies. Particularly, obtained results of semi-supervised training show the advantage of demanding fewer labeled data and less training time without significantly compromising accuracy. This paper introduces a new method, providing an objective scheme that enables electro-physiologist to recognize the diverse EGM morphologies reliably.

Effect of the electrograms density in detecting and ablating the tip of the rotor during chronic atrial fibrillation: an in silico study.

AIMS: Identification in situ of arrhythmogenic mechanisms could improve the rate of ablation success in atrial fibrillation (AF). Our research group reported that rotors could be located through dynamic approximate entropy (DApEn) maps. However, it is unknown how much the spatial resolution of catheter electrodes could affect substrates localization. The present work looked for assessing the electrograms (EGMs) spatial resolution needed to locate the rotor tip using DApEn maps. METHODS AND RESULTS: A stable rotor in a two-dimensional computational model of human atrial tissue was simulated using the Courtemanche electrophysiological model and implementing chronic AF features. The spatial resolution is 0.4 mm (150 × 150 EGM). Six different lower resolution arrays were obtained from the initial mesh. For each array, DApEn maps were constructed using the inverse distance weighting (IDW) algorithm. Three simple ablation patterns were applied. The full DApEn map detected the rotor tip and was able to follow the small meander of the tip through the shape of the area containing the tip. Inverse distance weighting was able to reconstruct DApEn maps after applying different spatial resolutions. These results show that spatial resolutions from 0.4 to 4 mm accurately detect the rotor tip position. An ablation line terminates the rotor only if it crosses the tip and ends at a tissue boundary. CONCLUSION: A previous work has shown that DApEn maps successfully detected simulated rotor tips using a high spatial resolution. In this work, it was evinced that DApEn maps could be applied using a spatial resolution similar to that available in commercial catheters, by adding an interpolation stage. This is the first step to translate this tool into medical practice with a view to the detection of ablation targets.

Dynamic approximate entropy electroanatomic maps detect rotors in a simulated atrial fibrillation model.

There is evidence that rotors could be drivers that maintain atrial fibrillation. Complex fractionated atrial electrograms have been located in rotor tip areas. However, the concept of electrogram fractionation, defined using time intervals, is still controversial as a tool for locating target sites for ablation. We hypothesize that the fractionation phenomenon is better described using non-linear dynamic measures, such as approximate entropy, and that this tool could be used for locating the rotor tip. The aim of this work has been to determine the relationship between approximate entropy and fractionated electrograms, and to develop a new tool for rotor mapping based on fractionation levels. Two episodes of chronic atrial fibrillation were simulated in a 3D human atrial model, in which rotors were observed. Dynamic approximate entropy maps were calculated using unipolar electrogram signals generated over the whole surface of the 3D atrial model. In addition, we optimized the approximate entropy calculation using two real multi-center databases of fractionated electrogram signals, labeled in 4 levels of fractionation. We found that the values of approximate entropy and the levels of fractionation are positively correlated. This allows the dynamic approximate entropy maps to localize the tips from stable and meandering rotors. Furthermore, we assessed the optimized approximate entropy using bipolar electrograms generated over a vicinity enclosing a rotor, achieving rotor detection. Our results suggest that high approximate entropy values are able to detect a high level of fractionation and to locate rotor tips in simulated atrial fibrillation episodes. We suggest that dynamic approximate entropy maps could become a tool for atrial fibrillation rotor mapping.

IDENTIFICACIÓN DE ZONAS SUSCEPTIBLES DE ABLACIÓN EN FIBRILACIÓN AURICULAR PERMANENTE IMPLEMENTANDO ENTROPÍA APROXIMADA EN UN MODELO 2D / IDENTIFICATION OF TARGET SITES FOR ABLATION DURING PERMANENT ATRIAL FIBRILLATION IMPLEMENTING APPROXIMATE ENTROPY IN A 2D MODEL / IDENTIFICAÇÃO DE ÁREAS SUSCETÍVEIS DE ABLAÇÃO PERMANENTE DE FIBRILAÇÃO ATRIAL NA IMPLEMENTAÇÃO ENTROPY APROXIMADO UM MODELO 2D

La fibrilación auricular (FA) es la arritmia cardiaca más común. La ablación con catéter se ha convertido en la principal estrategia terapéutica para el tratamiento de la FA paroxística, sin embargo, los resultados en FA permanente no son completamente satisfactorios. Se propone la ablación de los electrogramas auriculares complejos fragmentados (CFAE) para la terminación de un rotor como mecanismo de mantenimiento de FA permanente. El objetivo de este trabajo es caracterizar los CFAE mediante la implementación de entropía aproximada (ApEn) y correlacionarlos con el tip de un rotor simulado. Para esto, se desarrolló un modelo 2D de tejido de aurícula humana bajo condiciones de FA permanente; se registraron electrogramas unipolares durante la actividad del rotor y se desarrolló un algoritmo para la medida de ApEn. La ApEn permitió localizar los CFAE con una alta precisión y relacionarlos con el tip del rotor. Por lo que este índice podría ser muy eficaz en la identificación de zonas susceptibles de ablación.

Atrial fibrillation (AF) is the most common cardiac arrhythmia. Catheter ablation has become the main therapeutic strategy for the treatment of paroxysmal AF, however, results in permanent AF are not completely satisfactory. Ablation of complex fractionated atrial electrograms (CFAE) is proposed for the termination of a rotor as mechanism of permanent AF maintenance. The aim of this work is to characterize the CFAE by implementing approximate entropy (ApEn) and to correlate with the tip of a simulated rotor. For this, a 2D model of human atrial tissue under permanent FA conditions was developed. Unipolar electrograms were recorded during the rotor activity and an algorithm to measure ApEn was developed. The ApEn allowed locate the CFAE with high precision and relate them to the tip of the rotor. So this index could be very effective in identifying target sites for ablation.

A fibrilação atrial (FA) é a arritmia cardíaca mais comum. A ablação por cateter tornou-se a principal estratégia terapêutica para o tratamento da fibrilação atrial paroxística, no entanto, resulta em FA permanente não são completamente satisfatórios. Ablação de fones de ouvido eletrocardiogramas complexos fragmentada (CFAE) para a conclusão de um rotor como um mecanismo de manutenção da FA permanente, é proposto. O objetivo deste trabalho é caracterizar o CFAE através da implementação de entropia aproximada (ApEn) e correlacioná-los com a ponta de um rotor simulado. Para isso, um modelo em 2D do tecido atrial humano sob condições de FA permanente desenvolvido; unipolares electrogramas foram registados durante a actividade do rotor e um algoritmo para medir ApEn desenvolvido. O ApEn permitido CFAE localizar com precisão elevada e relacioná-los com a ponta do rotor. Portanto, esta taxa pode ser muito eficaz na identificação de áreas suscetíveis a ablação.