Automatic diagnosis of strict left bundle branch block using a wavelet-based approach

Patients with left bundle branch block (LBBB) are known to have a good clinical response to cardiac resynchronization therapy. However, the high number of false positive diagnosis obtained with the conventional LBBB criteria limits the effectiveness of this therapy, which has yielded to the definition of new stricter criteria. They require prolonged QRS duration, a QS or rS pattern in the QRS complexes at leads V1 and V2 and the presence of mid-QRS notch/slurs in 2 leads within V1, V2, V5, V6, I and aVL. The aim of this work was to develop and assess a fully-automatic algorithm for strict LBBB diagnosis based on the wavelet transform. Twelve-lead, high-resolution, 10-second ECGs from 602 patients enrolled in the MADIT-CRT trial were available. Data were labelled for strict LBBB by 2 independent experts and divided into training (n = 300) and validation sets (n = 302) for assessing algorithm performance. After QRS detection, a wavelet-based delineator was used to detect individual QRS waves (Q, R, S), QRS onsets and ends, and to identify the morphological QRS pattern on each standard lead. Then, multilead QRS boundaries were defined in order to compute the global QRS duration. Finally, an automatic algorithm for notch/slur detection within the QRS complex was applied based on the same wavelet approach used for delineation. In the validation set, LBBB was diagnosed with a sensitivity and specificity of Se = 92.9% and Sp = 65.1% (Acc = 79.5%, PPV = 74% and NPV = 89.6%). The results confirmed that diagnosis of strict LBBB can be done based on a fully automatic extraction of temporal and morphological QRS features. However, it became evident that consensus in the definition of QRS duration as well as notch and slurs definitions is necessary in order to guarantee accurate and repeatable diagnosis of complete LBBB

Response of Ventricular Repolarization to Simulated Microgravity Measured by Periodic Repolarization Dynamics Using Phase-Rectified Signal Averaging

Head-Down Bed Rest (HDBR) microgravity simulation induces cardiovascular deconditioning, including effects on ventricular repolarization. The index of Periodic Repolarization Dynamics (PRD) was developed to quantify low-frequency oscillations of cardiac repolarization. In this study, PRD was quantified by Phase Rectified Signal Averaging (PRDPRSA) and Continuous Wavelet Transform (PRDCWT) methods. PRD was analyzed in ECGs from 22 volunteers at rest and during orthostatic Tilt-Table Test (TTT) performed before and after -6° 60-days HDBR. Significant correlation was found between PRD measured by PRSA and CWT (Pearson''s ¿ = 0.93, p < 10-54 and Kendall''s t = 0.79 p < 10-38). A highly significant increase was found when PRDPRSA values were measured at POST-HDBR with respect to PRE-HDBR in the tilt phase: 1.40 [1.10] deg and 0.97 [0.90] deg (median [IQR]), p = 0.008, respectively. PRDPRSA also increased significantly in the tilt phase with respect to baseline, both at POST-HDBR (0.90 [0.57] deg, p = 0.003) and at PRE-HDBR (0.75 [0.45] deg, p = 0.011). PRD, either measured with PRSA or with CWT, is able to measure changes in ventricular repolarization induced by microgravity simulation as well as following sympathetic provocation

Commentary: Increased Beat-to-Beat Variability of T-Wave Heterogeneity Measured From Standard 12-Lead Electrocardiogram Is Associated With Sudden Cardiac Death: A Case-Control Study

The electrocardiogram (ECG) reflects the electrical activity within the heart. Following the discovery of the small electrical signals in the human heart, the Dutch scientist Willem Einthoven developed sensitive methods for detecting them and recognized their clinical implications (Kligfield, 2002). For his contributions Willem Einthoven, whose scientific roots originated from the Utrecht physiology department (Einthoven, 1885), was awarded the Nobel Prize in 1924. Since then, many enigmas of the ECG have been solved and its intricate information carries valuable clues for clinical decision making. In vivo mapping studies have established that spatial heterogeneity in repolarization is a requisite for re-entrant ventricular arrhythmias by effecting unidirectional conduction block. Important modulators of spatial heterogeneity of repolarization include autonomic tone, ischemia, heart rate and premature or ectopic beats, which can produce temporal heterogeneity in the order of seconds, minutes, or hours depending on their time-constants. In the contemporary era of dynamic surface electrocardiography, a formidable challenge is quantifying spatiotemporal repolarization heterogeneity with sufficient fidelity to image the arrhythmogenic myocardial substrate and thereby provide indices for a patient’s risk of arrhythmic death (Laguna et al., 2016). Hekkanen et al. (2020) performed a large case-control study of 200 victims..

Biopesticide activity from drimanic compounds to control tomato pathogens

Indexación: Scopus.Tomato crops can be affected by several infectious diseases produced by bacteria, fungi, and oomycetes. Four phytopathogens are of special concern because of the major economic losses they generate worldwide in tomato production; Clavibacter michiganensis subsp. michiganensis and Pseudomonas syringae pv. tomato, causative agents behind two highly destructive diseases, bacterial canker and bacterial speck, respectively; fungus Fusarium oxysporum f. sp. lycopersici that causes Fusarium Wilt, which strongly affects tomato crops; and finally, Phytophthora spp., which affect both potato and tomato crops. Polygodial (1), drimenol (2), isonordrimenone (3), and nordrimenone (4) were studied against these four phytopathogenic microorganisms. Among them, compound 1, obtained from Drimys winteri Forst, and synthetic compound 4 are shown here to have potent activity. Most promisingly, the results showed that compounds 1 and 4 affect Clavibacter michiganensis growth at minimal inhibitory concentrations (MIC) values of 16 and 32 μg/mL, respectively, and high antimycotic activity against Fusarium oxysporum and Phytophthora spp. with MIC of 64 μg/mL. The results of the present study suggest novel treatment alternatives with drimane compounds against bacterial and fungal plant pathogens. © 2018 by the authors.https://www.mdpi.com/1420-3049/23/8/205

Spatiotemporal Model-Based Estimation of High-Density Atrial Fibrillation Activation Map

Examination of activation maps using multi-electrode array (MEA) sensors can help to understand the mechanisms underlying atrial fibrillation (AF). Classically, creation of activation maps starts with detection of local activation times (LAT) based on recorded unipolar electrograms. LAT detection has a limited robustness and accuracy, and generally requires manual edition. In general, LAT detection ignores spatiotemporal information of activation embedded in the relation between electrode signals on the MEA mapping sensor. In this work, a unified approach to construct activation maps by simultaneous analysis of activation patterns from overlapping clusters of MEA electrodes is proposed. An activation model fits on the measured data by iterative optimization of the model parameters based on a cost function. The accuracy of the estimated activation maps was evaluated by comparison with audited maps created by expertelectrophysiologists during sinus rhythm (SR) and AF. During SR recordings, 25 activation maps (3100 LATs) were automatically determined resulting in an average LAT estimation error of -0.66 ±2.00msand a correlation of ¿s=0.98compared to the expert reference. During AF recordings (235 maps, 28226 LATs), the estimation error was -0.83 ±6.02mswith only a slightly lower correlation (¿s=0.93). In conclusion, complex spatial activation patterns can be decomposed into local activation patterns derived from fitting an activation model, allowing the creation of smooth and comprehensive high-density activation maps

Estimation of high-density activation maps during atrial fibrillation

The study of activation maps using multi-electrode arrays (MEA) can help to understand atrial fibrillation (AF) mechanisms. Activation mapping based on recorded unipolar electrograms (u-EGM) rely on the local activation time (LAT) detector, which has a limited robustness, accuracy, and generally requires manual post-edition. In general, LAT detection ignores spatiotemporal information about activation and conduction conveyed by the relation between signals of the MEA sensor. This work proposes an approach to construct activation maps by simultaneous analysis of u-EGMs from small clusters of MEA electrodes. The algorithm iteratively fits an activation pattern model to the acquired data. Accuracy was evaluated by comparing with audited maps created by expert electrophysiologists from a patient undergoing open-chest surgery during AF. The estimation error was -0.29 ± 6.01 ms (236 maps, 28369 LATs) with high correlation (¿ = 0.93). Therefore, activation maps can be decomposed into local activation patterns derived from fitting an activation model, resulting in smooth and comprehensive high-density activation maps

Continuous perception for deformable objects understanding

We present a robot vision approach to deformable object classification, with direct application to autonomous service robots. Our approach is based on the assumption that continuous perception provides robots with greater visual competence for deformable objects interpretation and classification. Our approach thus classifies the category of clothing items by continuously perceiving the dynamic interactions of the garment’s material and shape as it is being picked up. Our proposed solution consists of extracting continuously visual features of a RGB-D video sequence and fusing features by means of the Locality Constrained Group Sparse Representation (LGSR) algorithm. To evaluate the performance of our approach, we created a fully annotated database featuring 150 garment videos in random configurations. Experiments demonstrate that by continuously observing an object deform, our approach achieves a classification score of 66.7%, outperforming state-of-the-art approaches by a ∼ 27.3% increase

Characterization of Propagation Patterns with Omnipolar EGM in Epicardial Multi-Electrode Arrays

Omnipolar Electrogram (OP-EGM) is a recently proposed technique to characterize myocardial propagation in multi-electrode catheters regardless of the angle between propagation direction and catheter bipolar. This work aims to evaluate the accuracy of atrial propagation parameters obtained with OP-EGM in sinus rhythm (SR) and in different patterns of atrial fibrillation (AF).Real and simulated unipolar electrograms (u-EGMs) were used in this study. For both types of data, conduction velocity was obtained for each clique of 4 neighbour electrodes using OP-EGM. As a reference, conduction velocity was also computed from local activation times (LATs) using a linear propagation model.Analysis of simulated data showed that conduction velocity had good concordance with propagation patterns for both estimations, although the LAT-based errors were lower in most of the cases. When conduction velocity magnitude (CV) was 1 mm/ms, its estimation errors (expressed as mean ± std) calculated with OP-EGM and from LATs were 0.053 ± 0.005 mm/ms and 0.003 ±2.1 ×10-5 mm/ms, respectively, when focus was at 30 mm from the bottom of the tissue slice, while propagation direction angular errors were 6.64 ± 4.3°and 4.35 ± 2.8°. In real data, maps obtained with OP-EGM presented smoother and more coherent patterns than those based on LATs

Análisis de un algoritmo para la clasificación semiautomática de latidos en ECG

En este trabajo se presenta un algoritmo para la clasificación de latidos en la señal deECG, que puede operar tanto de manera automática como asistida. El mismo se compone porun clasificador automático previamente validado, y un algoritmo de clustering. Tanto elclasificador automático como el algoritmo de clustering utilizan características descrciptivasdel ritmo de los latidos y de su morfología. Mediante la integración de las decisiones de ambosalgoritmos, el algoritmo presentado puede desempeñarse de manera automática o condiversos grados de asistencia, dependiendo de la idoneidad del usuario. El algoritmo fueevaluado en la base de datos de arritmias del MIT‐BIH con el propósito de comparar surendimiento. En el modo automático de funcionamiento, el algoritmo propuesto ha obtenidoun rendimiento ligeramente superior al clasificador automático original; pero con solo 5 latidosanotados manualmente en 22 registros, se ha obtenido una mejora del 5% en exactitud (A),sensibilidad (S) y valor predictivo positivo (P^{+}) globales. Para el modo completamenteasistido, este algoritmo ha igualado el rendimiento de referencia con 55 veces menos esfuerzomanual y lo ha superado con 42. Estos resultados representan una mejora en el estado delarte, concluyendo que el rendimiento de un clasificador automático puede mejorarsemediante el uso eficiente de la ayuda provista por un experto

Mechanisms of Spontaneous and Amplified Spontaneous Emission in CH3 NH3 Pb I3 Perovskite Thin Films Integrated in an Optical Waveguide

In this paper, the physical mechanisms responsible for optical gain in CH3NH3PbI3 (MAPI) polycrystalline thin films are investigated experimentally and theoretically. Waveguide structures composed by a MAPI film embedded in between PMMA and silica layers are used as an efficient geometry to confine emitted light in MAPI films and minimize the energy threshold for amplified spontaneous emission (ASE). We show that photogenerated exciton density at the ASE threshold is as low as (2.4-12)×1016cm-3, which is below the Mott transition density reported for this material and the threshold transparency condition deduced with the free-carrier model. Such a low threshold indicates that the formation of excitons plays an important role in the generation of optical gain in MAPI films. The rate-equation model including gain is incorporated into a beam-propagation algorithm to describe waveguided spontaneous emission and ASE in MAPI films, while using the optical parameters experimentally determined in this work. This model is a useful tool to design active photonic devices based on MAPI and other metal-halide semiconductors