Heart rate variability : a fractal analysis

Tese de mestrado. Engenharia Biomédica. Faculdade de Engenharia. Universidade do Porto. 200

Estudio de la red de abastecimiento de agua potable de Massanassa (Valencia)

Este proyecto tiene por objeto el presente proyecto el estudio para la búsqueda de deficiencias y proposición de soluciones de la red de abastecimiento de agua potable del municipio de Massanassa (Valencia).Ingeniería Técnica IndustrialIndustria Ingeniaritza Tekniko

Evaluation of Emotional Responses to Television Advertising through Neuromarketing

Desde el siglo pasado hemos presenciado una evolución constante de las técnicas de comunicación publicitarias en un intento de adaptación a las nuevas realidades sociales del mercado. Como recurso estratégico, la Neurociencia aporta una nueva perspectiva al permitir explorar aquellos motivos difíciles de verbalizar o inconscientes que hay detrás de los comportamientos de los consumidores. El presente trabajo tiene como objetivo descubrir la relación entre las emociones inducidas en los mensajes publicitarios audiovisuales y su impacto en el recuerdo de los sujetos. Para alcanzar este objetivo se ha realizado un experimento con ocho mensajes publicitarios audiovisuales (seis representativos de seis emociones básicas: alegría, sorpresa, ira, asco, miedo y tristeza; y dos racionales) en el que se han utilizado, por un lado, técnicas de Neuromarketing como son la actividad eléctrica cardíaca (ECG) y la actividad eléctrica de la dermis (AED) de los sujetos; y, por otro, una técnica de investigación convencional, un cuestionario aplicado a los sujetos que han participado en la investigación. Los resultados ponen de manifiesto variaciones en las medidas realizadas en los mensajes correspondientes a la alegría, la sorpresa y la ira, mientras que, tanto para el recuerdo sugerido del mensaje trasmitido como para la actividad del anunciante, el anuncio con mejores resultados ha sido el de la tristeza, anuncio que también ha sido considerado el más atractivo para los sujetos participantesSince the last century, we have witnessed a steady evolution of advertising techniques in an effort to adapt to the new social context in the market. As a strategic resource, Neuroscience brings a new perspective by allowing you to explore those difficult or verbally unconscious motives behind consumer behaviours. The present work aims to discover the relationship between the emotions induced in audiovisual advertising messages and their impact on the memory of the subjects. To achieve this goal, an experiment was carried out with eight audiovisual advertising messages (six representatives of the basic emotions: joy, surprise, anger, disgust, fear and sadness, and two rational ones that show the technical specifications of the product). Neuromarketing techniques such as the electrical activity of the heart (ECG) and the electrodermal activity (EDA) of the subjects are used, on one hand; and, on the other, a conventional research technique, a questionnaire applied to the subjects that participated in the research. The results show variations in the measures performed in the commercials corresponding to joy, surprise and anger, while for both, remembrance of the message transmitted and activity of the advertiser, the commercial with the best results has been the one regarding sadness, advertisement that has also been considered the most attractive for participating subject

Detection of Atrial Fibrillation Driver Locations Using CNN and Body Surface Potentials

[EN] Atrial fibrillation (AF) is characterized by complex and irregular propagation patterns, and AF onset locations and drivers responsible for its perpetuation are main targets for ablation procedures. Several Deep Learningbased methods have proposed to detect AF, but the estimation of the atrial area where the drivers are found is a topic where further research is needed. In this work, we propose to estimate the zone where AF drivers are found from body surface potentials (BSPs) and Convolutional Neural Networks (CNN), modeling a supervised classification problem. Accuracy in the test set was 0.89 when using noisy BSPs (SNR=20dB), while the Cohen¿s Kappa was 0.85. Therefore, the proposed method could help to identify target regions for ablation using a non-invasive procedure, and avoiding the use of ECG Imaging (ECGI).This work has been partially supported by: Ministerio de Ciencia e Innovacion (PID2019-105032GB-I00), Instituto de Salud Carlos III, and Ministerio de Ciencia, Innovacion y Universidades (supported by FEDER Fondo Europeo de Desarrollo Regional PI17/01106 and RYC2018-024346B-750), Consejeria de Ciencia, Universidades e Innovacion of the Comunidad de Madrid through the program RIS3 (S-2020/L2-622), EIT Health (Activity code 19600, EIT Health is supported by EIT, a body of the European Union) and the European Union's Horizon 2020 research and innovation program under the Marie Skodowska-Curie grant agreement No. 860974.Cámara-Vázquez, MÁ.; Hernández-Romero, I.; Morgado-Reyes, E.; Guillem Sánchez, MS.; Climent, AM.; Barquero-Pérez, Ó. (2021). Detection of Atrial Fibrillation Driver Locations Using CNN and Body Surface Potentials. 1-4. https://doi.org/10.22489/CinC.2021.2561

Categorization of Mining Materials for Restoration Projects by Means of Pollution Indices and Bioassays

Sulfide mining wastes may lead to severe environmental and human health risks. This study aims to use geochemical and ecotoxicological indicators for the assessment of the ecological risks of potentially toxic elements (PTEs) in the San Quintín mining group to categorize wastes prior to mining restoration. Ecotoxicity was evaluated using crustacean (Dahpnia magna, Thamnocephalus platyurus) and algae (Raphidocelis subcapitata) bioassays. The geochemical and mineralogical results suggested that the mining residues underwent intense weathering processes, with active processes of acidity generation and metal mobility. Total PTEs concentrations indicated that the mining materials were extremely polluted, with Pb, Zn and Cd geoaccumulation index (Igeo) values higher than 5 in more than 90% of the samples. The pollution load index (PLI) showed average values of 18.1, which classifies them as very highly polluted. The toxicity tests showed a higher toxicity for plants than crustaceans, being the highest values of toxicity related to toxic elements (Pb, Cd and Zn), electrical conductivity and to pH. This paper presents for the first time the combination of indices in the categorization of mining waste prior to its restoration. The combination of them has made it possible to categorize the waste and adapt the restoration and remediation procedures.Depto. de Mineralogía y PetrologíaFac. de Ciencias GeológicasTRUEMinisterio de Ciencia e Innovaciónpu

Regularization Techniques for ECG Imaging during Atrial Fibrillation: A Computational Study

The inverse problem of electrocardiography is usually analyzed during stationary rhythms. However, the performance of the regularization methods under fibrillatory conditions has not been fully studied. In this work, we assessed different regularization techniques during atrial fibrillation (AF) for estimating four target parameters, namely, epicardial potentials, dominant frequency (DF), phase maps, and singularity point (SP) location. We use a realistic mathematical model of atria and torso anatomy with three different electrical activity patterns (i.e., sinus rhythm, simple AF, and complex AF). Body surface potentials (BSP) were simulated using Boundary Element Method and corrupted with white Gaussian noise of different powers. Noisy BSPs were used to obtain the epicardial potentials on the atrial surface, using 14 different regularization techniques. DF, phase maps, and SP location were computed from estimated epicardial potentials. Inverse solutions were evaluated using a set of performance metrics adapted to each clinical target. For the case of SP location, an assessment methodology based on the spatial mass function of the SP location, and four spatial error metrics was proposed. The role of the regularization parameter for Tikhonov-based methods, and the effect of noise level and imperfections in the knowledge of the transfer matrix were also addressed. Results showed that the Bayes maximum-a-posteriori method clearly outperforms the rest of the techniques but requires a priori information about the epicardial potentials. Among the purely non-invasive techniques. Tikhonov-based methods performed as well as more complex techniques in realistic fibrillatory conditions, with a slight gain between 0.02 and 0.2 in terms of the correlation coefficient. Also, the use of a constant regularization parameter may be advisable since the performance was similar to that obtained with a variable parameter (indeed there was no difference for the zero-order Tikhonov method in complex fibrillatory conditions). Regarding the different targets. DF and SP location estimation were more robust with respect to pattern complexity and noise, and most algorithms provided a reasonable estimation of these parameters, even when the epicardial potentials estimation was inaccurate. Finally, the proposed evaluation procedure and metrics represent a suitable framework for techniques benchmarking and provide useful insights for the clinical practice.This work has been partially supported by TEC2013-46067-R (Ministerio de Economia y Competitividad, Spanish Government).Figuera C; Suárez Gutiérrez V; Hernández-Romero, I.; Rodrigo Bort, M.; Liberos Mascarell, A.; Atienza, F.; Guillem Sánchez, MS.... (2016). Regularization Techniques for ECG Imaging during Atrial Fibrillation: A Computational Study. Frontiers in Physiology. 7(466):1-17. https://doi.org/10.3389/fphys.2016.00466S117746

Role of age and comorbidities in mortality of patients with infective endocarditis

[Purpose]: The aim of this study was to analyse the characteristics of patients with IE in three groups of age and to assess the ability of age and the Charlson Comorbidity Index (CCI) to predict mortality. [Methods]: Prospective cohort study of all patients with IE included in the GAMES Spanish database between 2008 and 2015.Patients were stratified into three age groups:<65 years,65 to 80 years,and ≥ 80 years.The area under the receiver-operating characteristic (AUROC) curve was calculated to quantify the diagnostic accuracy of the CCI to predict mortality risk. [Results]: A total of 3120 patients with IE (1327 < 65 years;1291 65-80 years;502 ≥ 80 years) were enrolled.Fever and heart failure were the most common presentations of IE, with no differences among age groups.Patients ≥80 years who underwent surgery were significantly lower compared with other age groups (14.3%,65 years; 20.5%,65-79 years; 31.3%,≥80 years). In-hospital mortality was lower in the <65-year group (20.3%,<65 years;30.1%,65-79 years;34.7%,≥80 years;p < 0.001) as well as 1-year mortality (3.2%, <65 years; 5.5%, 65-80 years;7.6%,≥80 years; p = 0.003).Independent predictors of mortality were age ≥ 80 years (hazard ratio [HR]:2.78;95% confidence interval [CI]:2.32–3.34), CCI ≥ 3 (HR:1.62; 95% CI:1.39–1.88),and non-performed surgery (HR:1.64;95% CI:11.16–1.58).When the three age groups were compared,the AUROC curve for CCI was significantly larger for patients aged <65 years(p < 0.001) for both in-hospital and 1-year mortality. [Conclusion]: There were no differences in the clinical presentation of IE between the groups. Age ≥ 80 years, high comorbidity (measured by CCI),and non-performance of surgery were independent predictors of mortality in patients with IE.CCI could help to identify those patients with IE and surgical indication who present a lower risk of in-hospital and 1-year mortality after surgery, especially in the <65-year group

Assessment of Classification Models and Relevant Features on Nonalcoholic Steatohepatitis Using Random Forest

Nonalcoholic fatty liver disease (NAFLD) is the hepatic manifestation of metabolic syndrome and is the most common cause of chronic liver disease in developed countries. Certain conditions, including mild inflammation biomarkers, dyslipidemia, and insulin resistance, can trigger a progression to nonalcoholic steatohepatitis (NASH), a condition characterized by inflammation and liver cell damage. We demonstrate the usefulness of machine learning with a case study to analyze the most important features in random forest (RF) models for predicting patients at risk of developing NASH. We collected data from patients who attended the Cardiovascular Risk Unit of Mostoles University Hospital (Madrid, Spain) from 2005 to 2021. We reviewed electronic health records to assess the presence of NASH, which was used as the outcome. We chose RF as the algorithm to develop six models using different pre-processing strategies. The performance metrics was evaluated to choose an optimized model. Finally, several interpretability techniques, such as feature importance, contribution of each feature to predictions, and partial dependence plots, were used to understand and explain the model to help obtain a better understanding of machine learning-based predictions. In total, 1525 patients met the inclusion criteria. The mean age was 57.3 years, and 507 patients had NASH (prevalence of 33.2%). Filter methods (the chi-square and Mann–Whitney–Wilcoxon tests) did not produce additional insight in terms of interactions, contributions, or relationships among variables and their outcomes. The random forest model correctly classified patients with NASH to an accuracy of 0.87 in the best model and to 0.79 in the worst one. Four features were the most relevant: insulin resistance, ferritin, serum levels of insulin, and triglycerides. The contribution of each feature was assessed via partial dependence plots. Random forest-based modeling demonstrated that machine learning can be used to improve interpretability, produce understanding of the modeled behavior, and demonstrate how far certain features can contribute to predictions

Evaluación de las respuestas emocionales a la publicidad televisiva desde el Neuromarketing

Desde el siglo pasado hemos presenciado una evolución constante de las técnicas de comunicación publicitarias en un intento de adaptación a las nuevas realidades sociales del mercado. Como recurso estratégico, la Neurociencia aporta una nueva perspectiva al permitir explorar aquellos motivos difíciles de verbalizar o inconscientes que hay detrás de los comportamientos de los consumidores. El presente trabajo tiene como objetivo descubrir la relación entre las emociones inducidas en los mensajes publicitarios audiovisuales y su impacto en el recuerdo de los sujetos. Para alcanzar este objetivo se ha realizado un experimento con ocho mensajes publicitarios audiovisuales (seis representativos de seis emociones básicas: alegría, sorpresa, ira, asco, miedo y tristeza; y dos racionales) en el que se han utilizado, por un lado, técnicas de Neuromarketing como son la actividad eléctrica cardíaca (ECG) y la actividad eléctrica de la dermis (AED) de los sujetos; y, por otro, una técnica de investigación convencional, un cuestionario aplicado a los sujetos que han participado en la investigación. Los resultados ponen de manifiesto variaciones en las medidas realizadas en los mensajes correspondientes a la alegría, la sorpresa y la ira, mientras que, tanto para el recuerdo sugerido del mensaje trasmitido como para la actividad del anunciante, el anuncio con mejores resultados ha sido el de la tristeza, anuncio que también ha sido considerado el más atractivo para los sujetos participantes.Since the last century, we have witnessed a steady evolution of advertising techniques in an effort to adapt to the new social context in the market. As a strategic resource, Neuroscience brings a new perspective by allowing you to explore those difficult or verbally unconscious motives behind consumer behaviours. The present work aims to discover the relationship between the emotions induced in audiovisual advertising messages and their impact on the memory of the subjects. To achieve this goal, an experiment was carried out with eight audiovisual advertising messages (six representatives of the basic emotions: joy, surprise, anger, disgust, fear and sadness, and two rational ones that show the technical specifications of the product). Neuromarketing techniques such as the electrical activity of the heart (ECG) and the electrodermal activity (EDA) of the subjects are used, on one hand; and, on the other, a conventional research technique, a questionnaire applied to the subjects that participated in the research. The results show variations in the measures performed in the commercials corresponding to joy, surprise and anger, while for both, remembrance of the message transmitted and activity of the advertiser, the commercial with the best results has been the one regarding sadness, advertisement that has also been considered the most attractive for participating subjects

A Modified Hilbert-Huang Algorithm to Assess Spectral Parameters in Intense Exercise

Abstract Spectral indices are widely used to assess Heart Rate Variability (HRV) during exercise. HRV signal spectrum comprises two main bands, High Frequency (HF) and Low Frequency (LF), the first related to parasympathetic activity and the second related to both parasympathetic and sympathetic activity. HF and LF powers are mostly obtained by Fast Fourier Transform (FFT) based algorithms, however there is a major problem due to the non-stationary and non-linear properties of the signal. Also, FFT based algorithms usually provide single LF and HF indices for temporal windows of several minutes. In the present study, our aim was to achieve a deeper understanding on the autonomic regulation mechanisms during intense exercise and recovery. For this purpose, we obtained the instantaneous LF and HF indices using a modified version of the Hilbert-Huang (HH) algorithm to track the HRV evolution on eight male amateur triathletes in an All Out Exercise Test (AOET). Both HH-based and FFT-based algorithms revealed severely depressed LF and HF powers during exercise. However, using the FFT the LF/HF ratio was always lower than one during intense exercise, while the mean of the instantaneous LF/HF ratio was lower than one only in one case. The HH-based algorithm allowed a deeper insight about the sympathetic and parasympathetic balance during exercise