Person:
Gómez Fernández, Marisol

Last Name

Gómez Fernández

First Name

Marisol

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Matemática e Informática

ORCID

0000-0003-3431-1256

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279

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Now showing 1 - 10 of 24

Open Access
Design of low-cost smart accelerometers
(Universitat Politècnica de Catalunya, 2005) Carlosena García, Alfonso; López Martín, Antonio; Massarotto, Marco; Cruz Blas, Carlos Aristóteles de la; Lecumberri Villamediana, Pablo; Gómez Fernández, Marisol; Pintor Borobia, Jesús María; Gárriz Sanz, Sergio; Ingeniería Eléctrica y Electrónica; Matemáticas; Ingeniería Mecánica, Energética y de Materiales; Ingeniaritza Elektrikoa eta Elektronikoa; Matematika; Mekanika, Energetika eta Materialen Ingeniaritza
The goal of this project is to design a low-cost smart accelerometer, making use of a piezoelectric element as basic sensing material, and adding a mixed-mode conditioning circuit.
Open Access
Relevance of sex, age and gait kinematics when predicting fall-risk and mortality in older adults
(Elsevier, 2020) Porta Cuéllar, Sonia; Martínez Ramírez, Alicia; Millor Muruzábal, Nora; Gómez Fernández, Marisol; Izquierdo Redín, Mikel; Ingeniería Eléctrica, Electrónica y de Comunicación; Estadística, Informática y Matemáticas; Ciencias de la Salud; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Estatistika, Informatika eta Matematika; Osasun Zientziak; Gobierno de Navarra / Nafarroako Gobernua, 87/10
Approximately one-third of elderly people fall each year with severe consequences, including death. The aim of this study was to identify the most relevant features to be considered to maximize the accuracy of a logistic regression model designed for prediction of fall/mortality risk among older people. This study included 261 adults, aged over 65 years. Men and women were analyzed separately because sex stratification was revealed as being essential for our purposes of feature ranking and selection. Participants completed a 3-m walk test at their own gait velocity. An inertial sensor attached to their lumbar spine was used to record acceleration data in the three spatial directions. Signal processing techniques allowed the extraction of 21 features representative of gait kinematics, to be used as predictors to train and test the model. Age and gait speed data were also considered as predictors. A set of 23 features was considered. These features demonstrate to be more or less relevant depending on the sex of the cohort under analysis and the classification label (risk of falls and mortality). In each case, the minimum size subset of relevant features is provided to show the maximum accuracy prediction capability. Gait speed has been largely used as the single feature for the prediction fall risk among older adults. Nevertheless, prediction accuracy can be substantially improved, reaching 70% in some cases, if the task of training and testing the model takes into account some other features, namely, sex, age and gait kinematic parameters. Therefore we recommend considering sex, age and step regularity to predict fall-risk.
Open Access
Valoración de la capacidad funcional en el ámbito domiciliario y en la clínica. Nuevas posibilidades de aplicación de la acelerometría para la valoración de la marcha, equilibrio y potencia muscular en personas mayores
(Gobierno de Navarra, 2008) Izquierdo Redín, Mikel; Martínez Ramírez, Alicia; Larrión, J. L.; Irujo Espinosa, M.; Gómez Fernández, Marisol; Matemáticas; Matematika
Dentro de cualquier población de individuos mayores de 65 años, una proporción sustancial (entre el 6% y el 25%) sufre diferentes síntomas del síndrome de fragilidad. A pesar de la complejidad del termino fragilidad y de las imprecisiones en cuanto a su definición existe un consenso sobre sus síntomas y signos. Las personas que poseen este síndrome presentan pérdidas de fuerza muscular, fatiga, disminución de la actividad física, con un aumento del riesgo de padecer anorexia-pérdida de peso, delirium, hospitalización, declive funcional, deterioro cognitivo, mortalidad, ingreso en residencias, caídas e inestabilidad. Bajo este contexto, surge la necesidad de desarrollar tests que sean capaces de predecir de la forma más precoz posible la fragilidad y la discapacidad. La acelerometría es una herramienta adecuada para la monitorización de movimientos humanos de una forma objetiva y fiable, aplicable en la vida diaria de los sujetos sin implicar grandes costes. Los acelerómetros están siendo utilizados en la monitorización de diferentes movimientos. Se pueden obtener una amplio abanico de medidas como: clasificación de movimientos, valoración del nivel de actividad física, estimación del gasto de energía metabólica, medida del equilibrio, ritmo de marcha y control al levantarse-sentarse. Combinando la acelerometría con giróscopos y magnetómetros se podrá añadir información relacionada con la orientación y los cambios de posición. Esta revisión analiza las herramientas y tecnologías existentes que puedan llegar a detectar de manera precoz posibles signos y síntomas de la fragilidad y permitan a los individuos vivir autónomamente de forma más prolongada y en condiciones de mayor seguridad.
Open Access
Multichannel blind deconvolution of impulsive signals
(2005) Lecumberri Villamediana, Pablo; Gómez Fernández, Marisol; Carlosena García, Alfonso; Matemáticas; Ingeniería Eléctrica y Electrónica; Matematika; Ingeniaritza Elektrikoa eta Elektronikoa
In this communication, the problem of blind deconvolution of transient, impulsive signals in a multichannel environment is addressed. This kind of signals arise naturally, or are used as external excitation, in many mechanical and acoustical systems and can only be observed indirectly, after propagation through the medium. Blind deconvolution or identi cation methods published to date are not suitable for recovering these sources or the system response, as identi ability conditions are not met. We fully develop here a deterministic subspace method for the blind deconvolution in a multichannel environment which does not impose any restrictions on the excitation signals or on the impulse response of propagation channels, apart from nite length and channel diversity. The method is also extended to cope with signals in noisy environments.
Open Access
A fast SSVEP-based brain-computer interface
(Springer, 2020) Jorajuría, Tania; Gómez Fernández, Marisol; Vidaurre, Carmen; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika
Literature of brain-computer interfacing (BCI) for steady-state visual evoked potentials (SSVEP) shows that canonical correlation analysis (CCA) is the most used method to extract features. However, it is known that CCA tends to rapidly overfit, leading to a decrease in performance. Furthermore, CCA uses information of just one class, thus neglecting possible overlaps between different classes. In this paper we propose a new pipeline for SSVEP-based BCIs, called corrLDA, that calculates correlation values between SSVEP signals and sine-cosine reference templates. These features are then reduced with a supervised method called shrinkage linear discriminant analysis that, unlike CCA, can deal with shorter time windows and includes between-class information. To compare these two techniques, we analysed an open access SSVEP dataset from 24 subjects where four stimuli were used in offline and online tasks. The online task was performed both in control condition and under different perturbations: listening, speaking and thinking. Results showed that corrLDA pipeline outperforms CCA in short trial lengths, as well as in the four additional noisy conditions.
Open Access
Initiative to increment the number of women in STEM degrees: women, science and technology chair of the Public University of Navarre
(IEEE, 2020) Aranguren Garacochea, Patricia; San Martín Biurrun, Idoia; Catalán Ros, Leyre; Martínez Ramírez, Alicia; Jurío Munárriz, Aránzazu; Díaz Lucas, Silvia; Pérez Artieda, Miren Gurutze; Gómez Fernández, Marisol; Barrenechea Tartas, Edurne; Estadística, Informática y Matemáticas; Ingeniería; Ingeniería Eléctrica, Electrónica y de Comunicación; Estatistika, Informatika eta Matematika; Ingeniaritza; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Gobierno de Navarra / Nafarroako Gobernua; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
The Public University of Navarre joined with Navarre Government has created the Women, Science and Technology Chair. This chair arises due to the plummeting tendency of the percentage of women in STEM degrees with the aim of reversing this trend. The programme of activities is defined throughout this contribution by six activities: a Theatre Play, a Poster Award on Final Degree/Masters Project, The 1st Week of Women, Science and Technology, the Promotion of Technical Degrees in schools and high-schools, a Workshop about Gender Stereotypes and the Fostering of Women among Science and Environment. Each activity gained great success and the preset goals were highly accomplished, especially, the 1st Week of Women, Science and Technology activity. The latter achieved a great success both in participation and in repercussion, contributing to visualize the role of women in science and technology.
Open Access
Impacto en el personal sanitario de urgencias extrahospitalarias de las cargas elevadas en la movilización de pacientes con silla de transporte
(Asociación de Especialistas en Enfermería del Trabajo, 2018) Arenal Gota, Tania; Viana Gárriz, Juan Luis; Millor Muruzábal, Nora; Martínez Ramírez, Alicia; Gómez Fernández, Marisol; Belzunegui Otano, Tomás; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Ciencias de la Salud; Osasun Zientziak
Introducción. El objetivo del estudio es valorar el esfuerzo físico realizado por el personal de la urgencia extrahospitalaria al trasladar pacientes de su domicilio a la ambulancia. Material y métodos. Estudio observacional transversal con un muestreo no probabilístico de conveniencia. Se comparan tres grupos: bomberos, mujeres y hombres técnicos en emergencias sanitarias (TES), utilizando sensores inerciales con los que obtenemos datos relativos del movimiento que ejecutan 10 profesionales sanitarios del ámbito extrahospitalario (4 bomberos y 6 TES) al bajar un paciente por las escaleras en condiciones similares a una urgencia. Resultados. Los sujetos que se encuentran en la posición de arriba en el desplazamiento de la carga presentan mayor aceleración en el plano suelo-techo y en la pierna izquierda. Las mujeres presentaron mayor aceleración en piernas y brazos que el resto, sin embargo, es en los brazos donde es significativamente superior. Cuando el sujeto que está en la posición de abajo en el desplazamiento de la carga, bajando la silla de espaldas, la aceleración de las piernas es superior que al bajarla en sentido de la marcha. Conclusiones. Los sujetos presentan mayor aceleración en piernas, siendo el lugar del cuerpo que sufre la suma del peso del paciente y del trabajador. Las mujeres presentan una mayor aceleración por lo que su esfuerzo físico es más acusado. Bajar la silla en sentido de la marcha, disminuye la aceleración en las piernas por lo que está posición es ergonómicamente mejor. Cuanto mayor es la estabilidad al bajar la silla y mayor seguridad del trabajador al desempeñar este trabajo, disminuye su aceleración y por lo tanto el esfuerzo físico que realiza.
Embargo
Enhancing sensorimotor BCI performance with assistive afferent activity: an online evaluation
(Elsevier, 2019) Vidaurre, Carmen; Ramos Murguialday, Ander; Haufe, Stefan; Gómez Fernández, Marisol; Müller, Klaus Robert; Nikulin, Vadim V.; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika
An important goal in Brain-Computer Interfacing (BCI) is tofind and enhance procedural strategies for users for whom BCI control is not sufficiently accurate. To address this challenge, we conducted offline analyses and online experiments to test whether the classification of different types of motor imagery could be improved when the training of the classifier was performed on the data obtained with the assistive muscular stimulation below the motor threshold. 10 healthy participants underwent three different types of experimental conditions: a) Motor imagery (MI) of hands and feet b) sensory threshold neuromuscular electrical stimulation (STM) of hands and feet while resting and c) sensory threshold neuromuscular electrical stimulation during performance of motor imagery (BOTH). Also, another group of 10 participants underwent conditions a) and c). Then, online experiments with 15 users were performed. These subjects received neurofeedback during MI using classifiers calibrated either on MIor BOTH data recorded in the same experiment. Offline analyses showed that decoding MI alone using a classifier based on BOTH resulted in a better BCI accuracy compared to using a classifier based on MI alone. Online experiments confirmed accuracy improvement of MI alone being decoded with the classifier trained on BOTH data. In addition, we observed that the performance in MI condition could be predicted on the basis of a more pronounced connectivity within sensorimotor areas in the frequency bands providing the best performance in BOTH. Thesefinding might offer a new avenue for training SMR-based BCI systems particularly for users having difficulties to achieve efficient BCI control. It might also be an alternative strategy for users who cannot perform real movements but still have remaining afferent pathways (e.g., ALS and stroke patients).
Open Access
MEANSP: How many channels are needed to predict the performance of a SMR-Based BCI?
(IEEE, 2023) Jorajuría, Tania; Nikulin, Vadim V.; Kapralov, Nikolai; Gómez Fernández, Marisol; Vidaurre, Carmen; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika
Predicting whether a particular individual would reach an adequate control of a Brain-Computer Interface (BCI) has many practical advantages. On the one hand, participants with low predicted performance could be trained with specifically designed sessions and avoid frustrating experiments; on the other hand, planning time and resources would be more efficient; and finally, the variables related to an accurate prediction could be manipulated to improve the prospective BCI performance. To this end, several predictors have been proposed in the literature, most of them based on the power estimation of EEG signals at the specific frequency bands. Many of these studies evaluate their predictors in relatively small datasets and/or using a relatively high number of channels. In this manuscript, we propose a novel predictor called MEANSP to predict the performance of participants using BCIs that are based on the modulation of sensorimotor rhythms. This novel predictor has been positively evaluated using only 2, 3, 4 or 5 channels. MEANSP has shown to perform as well as or better than other state-of-the-art predictors. The best sets of different number of channels are also provided, which have been tested in two different settings to prove their robustness. The proposed predictor has been successfully evaluated using two large-scale datasets containing 150 and 80 participants, respectively. We also discuss predictor thresholds for users to expect good performance in feedback experiments and show the advantages in comparison to a competing algorithm.
Embargo
Canonical maximization of coherence: a novel tool for investigation of neuronal interactions between two datasets
(Elsevier, 2019) Vidaurre, Carmen; Nolte, Guido; Vries, I. E. J. de; Gómez Fernández, Marisol; Boonstra, Tjeerd W.; Müller, Klaus Robert; Villringer, Arno; Nikulin, Vadim V.; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika
Synchronization between oscillatory signals is considered to be one of the main mechanisms through which neuronal populations interact with each other. It is conventionally studied with mass-bivariate measures utilizing either sensor-to-sensor or voxel-to-voxel signals. However, none of these approaches aims at maximizing syn-chronization, especially when two multichannel datasets are present. Examples include cortico-muscular coherence (CMC), cortico-subcortical interactions or hyperscanning (where electroencephalographic EEG/magnetoencephalographic MEG activity is recorded simultaneously from two or more subjects). For all of these cases, a method which could find two spatial projections maximizing the strength of synchronization would be desirable. Here we present such method for the maximization of coherence between two sets of EEG/MEG/EMG(electromyographic)/LFP (localfield potential) recordings. We refer to it as canonical Coherence (caCOH). caCOH maximizes the absolute value of the coherence between the two multivariate spaces in the frequency domain. Thisallows very fast optimization for many frequency bins. Apart from presenting details of the caCOH algorithm, we test its efficacy with simulations using realistic head modelling and focus on the application of caCOH to the detection of cortico-muscular coherence. For this, we used diverse multichannel EEG and EMG recordings and demonstrate the ability of caCOH to extract complex patterns of CMC distributed across spatial and frequency domains. Finally, we indicate other scenarios where caCOH can be used for the extraction of neuronal interactions.