Ponencias (Teoría de la Señal y Comunicaciones)

URI permanente para esta colecciónhttps://hdl.handle.net/11441/11424

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Propuesta para la optimización de la focalidad espacial en estimulación transcraneal por corriente directa (tDCS) mediante modelos computacionales electromagnéticos
(2020-12) Franco-Rosado, Pablo; Callejón Leblic, María Amparo; Reina Tosina, Luis Javier; Roa Romero, Laura María; Martín Rodríguez, Juan Francisco; Mir Rivera, Pablo; Teoría de la Señal y Comunicaciones; Psicología Experimental; Medicina; TIC203: Ingeniería Biomédica
Modelado computacional de bobinas para estimulación magnética transcraneal
(Visilab, 2018) Franco-Rosado, Pablo; Reina Tosina, Luis Javier; Callejón Leblic, María Amparo; Teoría de la Señal y Comunicaciones; TIC203: Ingeniería Biomédica
La estimulación cerebral profunda (DBS) de los núcleos subtalámicos (STN) del cerebro es el tratamiento quirúrgico más utilizado para mejorar los trastornos motores de los pacientes con enfermedad de Parkinson (EP) que no responden o presentan efectos colaterales al tratamiento farmacológico. Durante la cirugía para la implantación de un sistema DBS se obtienen señales a través de microelectrodos de registro (MER) a diferentes profundidades del cerebro, las cuales son analizadas por neurofisiólogos para detectar la entrada y salida del STN, así como la profundidad óptima para la implantación. En el presente trabajo se desarrolla un modelo de clasificación supervisada mediante el algoritmo K vecinos más cercanos (KNN) el cual es entrenado en forma automática a partir de características temporales de los registros MER. En particular se analiza el desempeño de KNN cuando el mismo es obtenido bajo tres formas diferentes de estandarizar sus datos de entrenamiento provenientes de registros MER de 14 pacientes con EP a los cuales se les implantó un DBS en los STN. Los resultados indicaron que KNN entrenado con datos estandarizados por hemisferio cerebral y por paciente presentó el mejor desempeño, logrando una exactitud del 94,35% frente al 81,94% (p<0.001) correspondiente a KNN entrenado con datos sin estandarizar. Los tiempos obtenidos de entrenamiento y validación menores a 0,4 s junto con la excelente exactitud obtenida permiten inferir bajo las condiciones experimentales del presente estudio que el algoritmo podría ser utilizado en tiempo real como herramienta de soporte en cirugías de implantación de DBS.
Optimización de la focalidad espacial en tDCS mediante modelos computacionales bioelectromagnéticos: un enfoque alternativo
(Universidad de Valladolid, 2020) Franco-Rosado, Pablo; Callejón Leblic, María Amparo; Reina Tosina, Luis Javier; Roa Romero, Laura María; Martín Rodríguez, Juan Francisco; Mir Rivera, Pablo; Teoría de la Señal y Comunicaciones; Psicología Experimental; Medicina; TIC203: Ingeniería Biomédica
El empleo de modelos computacionales bioelectromagnéticos para la simulación y evaluación de las técnicas de neuroestimulación no invasiva se ha asentado en los últimos años como una potente estrategia de para la predicción de la distribución y magnitud de campo eléctrico inducido. En este trabajo se propone un estudio de la estimulación trascraneal de corriente directa (tDCS), en términos de focalidad volumétrica, sobre la región sensomotora, considerándose dos montajes de electrodos: C3Fp2, montaje clásico para este objeto, y P3F3, un montaje alternativo. Los resultados presentan una ventaja concluyente del montaje alternativo para un amplio rango de intensidades de estimulación, en el que se incluyen los más prevalentes en el ámbito clínico. Estos resultados deben complementarse con estudios más extensos y validarse mediante estudios neurofisiológicos.
Addressing the effect of anatomical variability on electric field focality and orientation under two alternative tDCS montages for motor cortex stimulation
(2022-08-18) Franco-Rosado, Pablo; Callejón Leblic, María Amparo; Reina Tosina, Luis Javier; Roa Romero, Laura María; Martín Rodríguez, Juan Francisco; Mir Rivera, Pablo; Teoría de la Señal y Comunicaciones; Psicología Experimental; Medicina; TIC203: Ingeniería Biomédica
Dose and inter-subject variability analysis for anodal tDCS stimulation over motor cortical network
(2023-08-18) Franco-Rosado, Pablo; Callejón Leblic, María Amparo; Reina Tosina, Luis Javier; Roa Romero, Laura María; Martín Rodríguez, Juan Francisco; Mir Rivera, Pablo; Teoría de la Señal y Comunicaciones; Psicología Experimental; Medicina; TIC203: Ingeniería Biomédica
Generalization of an Active Set Newton Algorithm with Alpha-Beta divergences for audio separation
(European Signal Processing Conference, EUSIPCO, 2021-08) Sarmiento Vega, María Auxiliadora; Durán Díaz, Iván; Fondón García, Irene; Cruces Álvarez, Sergio Antonio; Teoría de la Señal y Comunicaciones; Ministerio de Economia, Industria y Competitividad (MINECO). España; European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER); Consejería de Economía y Conocimiento, Junta de Andalucía; TIC246: Tecnologías de aprendizaje automático y procesado digital de la información
This article considers the decomposition of a nonnegative signal into a non-negative linear combination of the contributions of pre-specified atomic units, which are also nonnegative. This model, referred as compositional model, is evident in the time-frequency characterisations of audio signals, where the sound can be viewed as a blending of spectral patterns of the component sounds that are present simultaneously. The algorithm proposed in this article obtains the activation vector of the atoms through an Active-Set Newton algorithm that employ the Alpha-Beta-divergence between the observed signal and the decomposition. This divergence family has been proved to be more efficient than other more common divergences, such as the generic Kullback-Leibler divergence in various audio signal processing applications. We have evaluated the proposed algorithm in a signal separation application of polyphonic music.
On the Minimum Perimeter Criterion for Bounded Component Analysis
(Institute of Electrical and Electronics Engineers (IEEE), 2023-05-05) Cruces Álvarez, Sergio Antonio; Teoría de la Señal y Comunicaciones; Ministerio de Ciencia e Innovación (MICIN). España; Agencia Estatal de Investigación. España; European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER); Junta de Andalucía; TIC246: Tecnologías de aprendizaje automático y procesado digital de la información
Bounded component analysis refers to a set of unsupervised techniques for the identification and recovery of underlying components of observations whose support has clear boundaries. This contribution is focused on the statistical justification and practical implementation of the minimum perimeter criterion, a bounded component analysis technique that can be used for the extraction of complex signals. In particular, with the help of the isoperimetric inequality, we reveal the link of the robust optimization of a statistical risk function with this criterion. We also address the difficulties for its optimization since, at the separation solutions, the criterion is non-differentiable. A reformulation of its optimization is shown to lead to a practical implementation that, for sources with clear boundaries, outperforms the normalized MSE performance of the state-of-the-art blind separation methods, being even close to the optimal performance of supervised methods.
Sparse Regression of Power Amplifier Behavioral Models with a Stagewise Doubly Orthogonal Matching Pursuit
(Institute of Electrical and Electronics Engineers (IEEE), 2023-02-20) Becerra González, Juan Antonio; Nogales, Miguel; Marqués Valderrama, Elías; Madero Ayora, María José; Teoría de la Señal y Comunicaciones; Ministerio de Ciencia e Innovación (MICIN). España; Agencia Estatal de Investigación. España; European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER); TIC158: Sistemas de Radiocomunicación
This work presents the sparse regression of Volterra-based behavioral models and digital predistorters (DPDs) through a Stagewise Doubly Orthogonal Matching Pursuit (StDOMP). First, the general sparse regression framework is presented. The StDOMP is formulated by applying the stagewise strategy to the DOMP algorithm, i.e., allowing the technique to select a block of components in each iteration without the need to perform one iteration per atom. The block selection approach allows to reduce the computational complexity up to a certain point where the performance is expected to be degraded. Experimental results highlight the behavior of the technique in the predistortion of a class AB power amplifier (PA) working in its nonlinear regime, concluding that the StDOMP is able to reduce runtime while still holding the performance level with respect to the DOMP.
Complex kernels for proper complex-valued signals: a review
(TIC155: Tratamiento de Señales y Comunicaciones (IEEE), 2015-12) Boloix Tortosa, Rafael; Payán Somet, Francisco Javier; Arias de Reyna Domínguez, Eva María; Murillo Fuentes, Juan José; Teoría de la Señal y Comunicaciones; Ministerio de Educación y Ciencia (MEC). España; TIC155: Tratamiento de Señales y Comunicaciones
In this paper we investigate the conditions that complex kernels must satisfy for proper complex-valued signals. We study the structure that complex kernels for proper complex-valued signals must have. Also, we demonstrate that complex kernels that have been previously proposed and used in adaptive filtering of complex-valued signals assume that those signals are proper, i.e, they are not correlated with their complex conjugate. We provide an example of how a complex-valued kernel suitable for a particular model is designed, with a procedure that could help in other designs. The experiments included show the good behavior of the proposed kernel in the task of nonlinear channel equalization.
Blind adaptive channel estimation for OFDM systems
(Institute of Electrical and Electronics Engineers (IEEE), 2009-06) Boloix Tortosa, Rafael; Simois Tirado, Francisco José; Murillo Fuentes, Juan José; Teoría de la Señal y Comunicaciones; TIC-155: Tratamiento de señales y comunicaciones
In this paper, we face the problem of blind channel estimation in zero padding OFDM systems. Based on the assumption that the transmitted symbols are independent and identically distributed, we propose a blind adaptive estimation algorithm for minimum phase channels, based on Independent Component Analysis, that exploits the particular structure of the ZP-OFDM system model. Some included simulations show that this novel algorithm can yield comparable performance as the SVD methods with a reduced computational complexity.
Gaussian processes regressors for complex proper signals in digital communications
(Institute of Electrical and Electronics Engineers (IEEE), 2014-06) Boloix Tortosa, Rafael; Payán Somet, Francisco Javier; Murillo Fuentes, Juan José; Teoría de la Señal y Comunicaciones; TIC-155: Tratamiento de señales y comunicaciones
In this paper we develop the complex-valued version of the Gaussian processes for regression (GPR) for proper complex signals. This tool has proved to be useful in the nonlinear detection in digital communications in real valued models. GPRs can be cast as nonlinear MMSE where hyperparameters can be tuned optimizing a marginal likelihood (ML). This feature allows for a flexible kernel that can easily adapt either to a linear or nonlinear solution. We introduce the complex-valued form of the GPR, and develop it for the proper complex case. We also deal with the optimization of the ML. Some experiments included illustrate the good performance of the proposal.
A Virtual Reality Prototype as a Tool Against Verbal Abuse in Classrooms: A Multidisciplinary Approach
(Science and Technology Publications, Lda, 2024) Fondón García, Irene; Elena Pérez, María del Mar; Jiménez Lagares, Irene; Gaytán Guía, Susana Pilar; Fisiología; Psicología Evolutiva y de la Educación; Ingeniería Electrónica; Teoría de la Señal y Comunicaciones
The exploration of affective response and its vegetative correlate to verbal abuse (VA) is a relevant research area to prevent bullying at schools. Taking advantage of the possibilities that virtual reality offers regarding to immersion in non-real environments inducing feelings in the users, this paper presents a virtual reality application focused on the study of VA in a school context. The versatility of the proposed project is directly related to its applicability. It has been designed under the premises of the psycho-neural effect of VA. The tool is intended to be used under professional and parental supervision, to perform experiments regarding bulling awareness. In this first stage, the authors propose a prototype that will be optimized and upgraded in future versions.
Hybrid and customized approach in telemedicine systems: An unavoidable destination
(IOS Press, 2005) Prado-Velasco, Manuel ; Roa Romero, Laura María; Reina Tosina, Luis Javier; Teoría de la Señal y Comunicaciones; Ingeniería Gráfica; Instituto de Salud Carlos III; Instituto de Salud Carlos III
Several important problems in the majority of industrialized countries have challenged the centralized and overburdened current model of healthcare. Telehealthcare systems are presented as a new paradigm, offering high expectations to provide effective solutions to this picture. With this paper we present a new methodological approach for telehealthcare systems that pursues the generation of clinical and physiological knowledge of the patient in a real time and personalized manner. This approach is based on a computational component, identified as patient physiological image (PPI), which is responsible for generating an image of the state of the patient and therapy devices. Three key issues of the proposed methodological approach are evaluated. With the objective to validate the capability of the PPI to determine the internal state of a patient, a digital simulation experiment over the mathematical model of a PPI is done. Numerical results are compared to those obtained by a validated mathematical model. Secondly, a laboratory prototype of a novel human physical activity monitor that follows the designed methodological approach will be tested, in order to evaluate the trade-off between processing capacity, portability, and cost-efficiency and power consumption, which are necessary to assure its compliance with the methodology. As a third key issue, the capability of our methodology to integrate physiological information belonging to different scales is analyzed. This is done by means of a case study related to the integration of the regulation of water function of AQP2 channels (genomic, proteomic and cellular levels) into a kidney collecting duct epithelium mathematical model of a PPI. The analysis and preliminary evaluation of the proposed telehealthcare methodological approach, featured by an advanced personalization of health assistance, have been satisfactory.
Ambient Assisted Living: A methodological approach
(IEEE (Institute of Electrical and Electronics Engineers), 2010) Estudillo Valderrama, Miguel Ángel; Roa Romero, Laura María; Reina Tosina, Luis Javier; Román Martínez, Isabel; Teoría de la Señal y Comunicaciones
In this paper, the most important challenges and trends related to the application of Ambient Assisted Living (AAL) methods and techniques to the social/healthcare context are discussed. In order to find out technical solutions to these challenges, the main methodological issues concerning the design of open and distributed architectures are analyzed. The objective is to improve the efficiency/cost ratio in the provision of social and healthcare services to citizens with special needs, through the application of new paradigms in the context of AAL environments. Finally, some results and conclusions regarding the proposed open architecture are illustrated for the case of a distributed biomedical sensor network designed by the authors following this methodology.
Experimental Setup and Protocol for Creating an EEG-signal Database for Emotion Analysis Using Virtual Reality Scenarios
(SciTePress, 2023) Marqués Valderrama, Elías; Sarmiento Vega, María Auxiliadora; Durán Díaz, Iván; Becerra González, Juan Antonio; Fondón García, Irene; Teoría de la Señal y Comunicaciones; Fondón García, Irene; European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER); Ministerio de Ciencia, Innovación y Universidades (MICINN). España; Agencia Estatal de Investigación. España; TIC246: Tecnologías de Aprendizaje Automático y Procesado Digital de la Información
Automatic emotion recognition systems aim to identify human emotions from physiological signals, voice, facial expression or even physical activity. Among these types of signals, the usefulness of signals from electroencephalography (EEG) should be highlighted. However, there are few publicly accessible EEG databases in which the induction of emotions is performed through virtual reality (VR) scenarios. Recent studies have shown that VR has great potential to evoke emotions in an effective and natural way within a laboratory environment. This work describes an experimental setup developed for the acquisition of EEG signals in which the induction of emotions is performed through a VR environment. Participants are introduced to the VR environment via head-mounted displays (HMD) and 14-channel EEG signals are collected. The experiments carried out with 12 participants (5 male and 7 female) are also detailed, with promising results, which allow us to think about the future development of our own dataset.
Detección Automática de Microaneurismas en Retinografías
(Universidad Carlos III de Madrid, 2010-11) Núñez Benjumea, Francisco José; Fondón García, Irene; Acha Piñero, Begoña; Serrano Gotarredona, María del Carmen; Jiménez Carmona, Soledad; Alemany Márquez, Pedro; Teoría de la Señal y Comunicaciones
La detección de microaneurismas (MA) en retinografías es esencial a la hora de realizar un diagnóstico precoz de la retinopatía diabética (RD). Con esta finalidad, se presenta una herramienta automática que, tras preprocesar la retinografía con métodos basados en intensidad y tras realizar una selección de semillas mediante una umbralización adaptativa, obtiene una serie de candidatos a MA mediante un proceso de crecimiento de regiones, a partir de las cuales se seleccionan los verdaderos MA mediante una clasificación con una red neuronal Fuzzy ARTMAP. La evaluación del algoritmo se ha realizado con una base de datos consistente en 53 retinografías con 256 MA marcados por un oftalmólogo experto. 42 (204 MA) de estas imágenes han sido empleadas para entrenar al clasificador sirviendo las 11 (52 MA) restantes para la fase de prueba. La presente propuesta obtiene una sensibilidad (S) de 78.85% y una media de 9 falsos positivos por imagen (FPpI).
Novel multi-step region growing algorithm for the segmentation of burn images
(2005-11) Serrano Gotarredona, María del Carmen; Acha Piñero, Begoña; Fondón García, Irene; Teoría de la Señal y Comunicaciones
In this paper, a novel region growing algorithm for segmenting burn wounds in digital photographs of the skin is presented. This segmentation step has been developed as part of a CAD tool for burn diagnosis. During the region growing the inclusion condition relies on a tolerance parameter, which is adaptively determined. It initially has a low value and this is recursively increased until a stop condition is reached. This condition is based on the analysis of the statistical distribution of the pixels within the grown region. The great advantage of the method is that it does not rely on fine-tune parameters. The algorithm has been tested with 44 images of burn wounds obtaining very good results. Its performance has been measured quantitatively by comparing it with a ground truth obtained from the manual segmentation of five experts.
Detection of microcalcifications in mammograms using 2D prediction filtering and a new statistical measure of the right tail weight
(2005-11) Acha Piñero, Begoña; Serrano Gotarredona, María del Carmen; Rangayyan, Rangaraj M.; Teoría de la Señal y Comunicaciones
In this paper, a new method to detect microcalcifications in mammograms is presented. The method is based on a candidate selection procedure which consists of a two-dimensional linear prediction adaptive filtering followed by a statistical parameter calculation developed by the authors and called tail ratio (TR). The parameter TR characterizes the presence of microcalcifications in a ROI, and is extracted from the local probability distribution within a small region surrounding each candidate. Afterward a group of new and previously published features are used to feed a neural network that classifies the candidates into microcalcification or non-microcalcification. The algorithm has been tested with 38 digitized mammograms obtaining a sensitivity of 0.93 for a positive predictive value of 0.88.
Detección automática de microaneurismas en angiogramas de retina
(Sociedad Española de Ingeniería Biomédica, 2002) Cordero García, José Manuel; Serrano Gotarredona, María del Carmen; Acha Piñero, Begoña; Teoría de la Señal y Comunicaciones
En este artículo se presenta un nuevo método de detección automática de microaneurismas en angiogramas de retina, con el objetivo de servir de ayuda al diagnóstico de la retinopatía diabética en su etapa más precoz. Las características de esta enfermedad aconsejan un pronto diagnóstico, para el que resultan idóneas estas pequeñas lesiones retinianas, que se manifiestan especialmente claras en los angiogramas fluoresceínicos. El algoritmo propuesto para su detección y recuento se basa en la compensación ante variaciones locales y globales de las características de las imágenes, en la morfología matemática particularizada en el filtrado Top-Hat y en la validación de los microaneurismas a partir de tres novedosos criterios: intensidad, contraste y forma, que se combinan de forma que, tras haberse probado en diversos casos, se obtiene una tasa de acierto que habitualmente supera el 80%. Asimismo, se ha desarrollado un interfaz gráfico amigable que facilita su uso por parte del médico.
Global pattern classification in dermoscopic images based on modelling
(Sociedad Española de Ingeniería Biomédica, 2014) Sáez Manzano, Aurora; Acha Piñero, Begoña; Serrano Gotarredona, María del Carmen; Teoría de la Señal y Comunicaciones
In this paper a model-based method of classificationof global patterns in dermoscopic images is proposed. Global patterns identification is included in the pattern analysisframework, the melanoma diagnosis method most used amongdermatologists. The modelling is performed in two senses: first adermoscopic image is modelled by a finite symmetric conditionalMarkov model applied to colour space and the estimatedparameters of this model are treated as features. In turn, thedistribution of these features are supposed that follow a Gaussian mixturemodel along a lesion. The classification is carried out by an image retrieval approachwith different distance metrics. A 78.44% success rate in average is achieved when globular, homogeneous, and reticularare classified and a 72.91% success rate when the multicomponent pattern is added.

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