Combined Nonlinear Analysis of Atrial and Ventricular Series for Automated Screening of Atrial Fibrillation

[EN] Atrial fibrillation (AF) is the most common cardiac arrhythmia in clinical practice. It often starts with asymptomatic and short episodes, which are difficult to detect without the assistance of automatic monitoring tools. The vast majority of methods proposed for this purpose are based on quantifying the irregular ventricular response (i.e., RR series) during the arrhythmia. However, although AF totally alters the atrial activity (AA) reflected on the electrocardiogram(ECG), replacing stable P-waves by chaotic and time-variant fibrillatory waves, this information has still not been explored for automated screening of AF. Hence, a pioneering AF detector based on quantifying the variability over time of the AA morphological pattern is here proposed. Results from two public reference databases have proven that the proposed method outperforms current state-of-the-art algorithms, reporting accuracy higher than 90%. A less false positive rate in the presence of other arrhythmias different from AF was also noticed. Finally, the combination of this algorithm with the classical analysis of RR series variability also yielded a promising trade-off between AF accuracy and detection delay. Indeed, this combination provided similar accuracy than RR-based methods, but with a significantly shorter delay of 10 beats.This work was supported by the Spanish Ministry of Economy and Competitiveness (Project TEC2014-52250-R).Rodenas, J.; Garcia, M.; Alcaraz, R.; Rieta, JJ. (2017). Combined Nonlinear Analysis of Atrial and Ventricular Series for Automated Screening of Atrial Fibrillation. Complexity. (2163610):1-13. doi:10.1155/2017/2163610S113216361

Sobre la presencia de Sternbergial Lutea (L.) Ker-Gawler (Amaryllidaceae) en extremadura

On the presence of Sternbergia iutea (L.) Ker-Gawler (Amaryllidaceae) in Extremadura. Palabras clave. Sternbergia, Amaryllidaceae, corología, Extremadura, España. Key words. Stern bergia, Amaryllidaceae, chorology, Extremadura, Spain

A novel wavelet-based filtering strategy to remove powerline interference from electrocardiograms with atrial fibrillation

This is an author-created, un-copyedited versíon of an article published in Physiological Measurement. IOP Publishing Ltd is not responsíble for any errors or omissíons in this versíon of the manuscript or any versíon derived from it. The Versíon of Record is available online at http://doi.org/10.1088/1361-6579/aae8b1[EN] Objective: The electrocardiogram (ECG) is currently the most widely used recording to diagnose cardiac disorders, including the most common supraventricular arrhythmia, such as atrial fibrillation (AF). However, different types of electrical disturbances, in which power-line interference (PLI) is a major problem, can mask and distort the original ECG morphology. This is a significant issue in the context of AF, because accurate characterization of fibrillatory waves (f-waves) is unavoidably required to improve current knowledge about its mechanisms. This work introduces a new algorithm able to reduce high levels of PLI and preserve, simultaneously, the original ECG morphology. Approach: The method is based on stationary wavelet transform shrinking and makes use of a new thresholding function designed to work successfully in a wide variety of scenarios. In fact, it has been validated in a general context with 48 ECG recordings obtained from pathological and non-pathological conditions, as well as in the particular context of AF, where 380 synthesized and 20 long-term real ECG recordings were analyzed. Main results: In both situations, the algorithm has reported a notably better performance than common methods designed for the same purpose. Moreover, its effectiveness has proven to be optimal for dealing with ECG recordings affected by AF, sincef-waves remained almost intact after removing very high levels of noise. Significance: The proposed algorithm may facilitate a reliable characterization of thef-waves, preventing them from not being masked by the PLI nor distorted by an unsuitable filtering applied to ECG recordings with AF.Research supported by grants DPI2017-83952-C3 MINECO/AEI/FEDER, UE and SBPLY/17/180501/000411 from Junta de Comunidades de Castilla-La Mancha.García, M.; Martínez, M.; Ródenas, J.; Rieta, JJ.; Alcaraz, R. (2018). A novel wavelet-based filtering strategy to remove powerline interference from electrocardiograms with atrial fibrillation. Physiological Measurement. 39(11):1-15. https://doi.org/10.1088/1361-6579/aae8b1S115391

Catheter Ablation Outcome Prediction With Advanced Time-Frequency Features of the Fibrillatory Waves From Patients in Persistent Atrial Fibrillation

[EN] Although catheter ablation (CA) is still the first-line treatment for persistent atrial fibrillation (AF) patients, its limited long-term success rate has motivated clinical interest in preoperative prediction on the procedure¿s outcome to provide optimized patient selection, limit repeated procedures, hospitalization rates, and treatment costs. To this respect, dominant frequency (DF) and amplitude of fibrillatory waves (f-waves) reflected on the ECG have provided promising results. Hence this work explores the ability of a novel set of frequency and amplitud f-waves features, such as spectral entropy (SE), spectral flatness measure (SFM), and amplitud spectrum area (AMSA), along with DF and normalized f-wave amplitude (NFWA), to improve CA outcome prediction. Despite all single indices reported statistically significant differences between patients who relapsed to AF and those who maintained sinus rhythm after a follow-up of 9 months for 204 6 s-length ECG intervals extracted from 51 persistent AF patients, they obtained a limited discriminant ability ranging between 55 and 62%, which was overcome by 15¿23% when NFWA, SE and AMSA were combined. Consequently, this combination of frequency and amplitude features of the fwaves seems to provide new insights about the atrial substrate remodeling, which could be helpful in improving preoperative CA outcome prediction.This research has been supported by grants DPI201783952-C3 from MINECO/AEI/FEDER EU, SBPLY/17/180501/000411 from Junta de Comunidades de Castilla-la Mancha and AICO/2019/036 from Generalitat Valenciana. Moreover, Pilar Escribano holds a graduate research scholarship from University of Castilla-La ManchaEscribano, P.; Ródenas, J.; Arias, MA.; Langley, P.; Rieta, JJ.; Alcaraz, R. (2020). Catheter Ablation Outcome Prediction With Advanced Time-Frequency Features of the Fibrillatory Waves From Patients in Persistent Atrial Fibrillation. IEEE. 1-4. https://doi.org/10.22489/CinC.2020.396S1

Checklist de Festuca L. (Poaceae) en la Península Ibérica

Se ha elaborado una checklist actualizada del género Festuca en la Pe¬nínsula Ibérica. El catálogo incluye 73 especies, que suman 98 taxones si se consideran las subespecies y variedades, de los que casi el 40% son endémicos del territorio. Para cada taxón se recoge el nombre válido y las sinonimias más importantes, la indicación locotípica, el número cromosómico, las características ecológicas, la distribución general y en el territorio, y la información bibliográfica de interés. Además, se recogen en varios apéndices los nombres sin asignación, los híbridos interespecíficos detectados en el territorio, los híbridos intergenéricos conocidos, los taxones excluidos provisionamente y aquellos cuya presencia es probable en el territorio.Checklist of Festuca L. (Poaceae) in the Iberian Peninsula. We present an updated checklist of the genus Festuca in the Iberian Peninsula. The catalogue includes 73 species, suming up 98 taxa considering infraspecific taxa (subspecies and varieties). Of them, approximately 40% are endemic to the region. Information about the valid name and the most important synonyms, the locus classicus reference, the chromosome number, the ecology, the global and regional geographical distributions, and the most relevant bibliographic references is provided for each taxon. Additional information on the taxa without clear taxonomic assignation, the interspecific hybrids detected in the territory, the described intergeneric hybrids, and the taxa provisionally excluded from the Iberian checklist and those that could be present in the Iberian Peninsula is indicated in the appendices

The Relevance of Calibration in Machine Learning-Based Hypertension Risk Assessment Combining Photoplethysmography and Electrocardiography

[EN] The detection of hypertension (HT) is of great importance for the early diagnosis of cardiovascular diseases (CVDs), as subjects with high blood pressure (BP) are asymptomatic until advanced stages of the disease. The present study proposes a classification model to discriminate between normotensive (NTS) and hypertensive (HTS) subjects employing electrocardiographic (ECG) and photoplethysmographic (PPG) recordings as an alternative to traditional cuff-based methods. A total of 913 ECG, PPG and BP recordings from 69 subjects were analyzed. Then, signal preprocessing, fiducial points extraction and feature selection were performed, providing 17 discriminatory features, such as pulse arrival and transit times, that fed machine-learning-based classifiers. The main innovation proposed in this research uncovers the relevance of previous calibration to obtain accurate HT risk assessment. This aspect has been assessed using both close and distant time test measurements with respect to calibration. The k-nearest neighbors-classifier provided the best outcomes with an accuracy for new subjects before calibration of 51.48%. The inclusion of just one calibration measurement into the model improved classification accuracy by 30%, reaching gradually more than 96% with more than six calibration measurements. Accuracy decreased with distance to calibration, but remained outstanding even days after calibration. Thus, the use of PPG and ECG recordings combined with previous subject calibration can significantly improve discrimination between NTS and HTS individuals. This strategy could be implemented in wearable devices for HT risk assessment as well as to prevent CVDs.This research received financial support from grants PID2021-00X128525-IV0, PID2021123804OB-I00 and TED2021-129996B-I00 of the Spanish Government 10.13039/501100011033 jointly with the European Regional Development Fund (EU), SBPLY/17/180501/000411 from Junta de Comunidades de Castilla-La Mancha and AICO/2021/286 from Generalitat Valenciana.Cano, J.; Fácila, L.; Gracia-Baena, JM.; Zangróniz, R.; Alcaraz, R.; Rieta, JJ. (2022). The Relevance of Calibration in Machine Learning-Based Hypertension Risk Assessment Combining Photoplethysmography and Electrocardiography. Biosensors. 12(5):1-14. https://doi.org/10.3390/bios1205028911412

Using Design Patterns in a HSDPA System Simulator

Abstract-Wireless network simulators have become a fundamental tool to study, evaluate and improve wireless networks. The quick evolution of wireless technology involves the necessity of continuous changes and updates in these simulators which makes them more complicated and time demanding. Regarding software design, wireless network simulators are generally based on the object-oriented paradigm. However, the use of more advanced programming techniques (such as UML and design patterns) is still an issue for further research. This paper discusses the application of design patterns in a HSDPA system simulator, pointing the suitable pattern and its application place in the wireless system. We focus on the strategy pattern whose implementation is showed in two points of the simulator: the scheduler and the radio channel. Strategy pattern allows us to change the scheduling mechanism or the radio channel even in execution time and simplifies the inclusion of new scheduling schemes or new radio channels

Effects of tension stiffening and shrinkage on the flexural behavior of reinforced UHPFRC beams

[EN] This paper presents a study on the flexural behavior of Ultra-High-Performance Fiber-Reinforced Concrete (UHPFRC) beams, which included conventional reinforcing bars. The study focuses on critical design aspects, such as concrete shrinkage and cracking implications on the tension-stiffening phenomenon. An experimental program with two different sized flexural reinforced UHPFRC beams was run. Beams were cast and tested in a four-point bending test (4PBT) using UHPFRC with different amounts of fibers: 130 and 160 kg/m(3) (1.66% and 2.00% in vol.) to cover a wide range of strain-softening and strain-hardening constitutive UHPFRC behaviors. A nonlinear finite element model (NLFEM) was developed to validate the mechanical tensile characterization of UHPFRC when applied to reinforced elements. Both shrinkage and tension-stiffening effects were considered to improve the model. After the NLFEM simulation, very reliable results were obtained at both the service and ultimate load levels compared to the experimental ones. Finally, some aspects about the design of reinforced UHPFRC cross-sections under bending forces are addressed and satisfactorily compared to the experimental results.This work forms part of Project "BIA2016-78460-C3-1-R" supported by the State Research Agency of Spain and the project "Rethinking coastal defence and Green-energy Service infrastructures through enHancEd-durAbiLity high-performance cement-based materials-ReSHEALience", funded by the European Union Horizon 2020 research and innovation programme under GA No 760824.Mezquida-Alcaraz, EJ.; Navarro-Gregori, J.; Martí Vargas, JR.; Serna Ros, P. (2021). Effects of tension stiffening and shrinkage on the flexural behavior of reinforced UHPFRC beams. Case Studies in Construction Materials. 15:1-28. https://doi.org/10.1016/j.cscm.2021.e007461281