Open Access
Computation of greatest common divisor for the blind deconvolution of transient impulsive signals
(Universitat Politècnica de Catalunya, 2005) Lecumberri Villamediana, Pablo; Gómez Fernández, Marisol; Carlosena García, Alfonso; Matemáticas; Ingeniería Eléctrica y Electrónica; Matematika; Ingeniaritza Elektrikoa eta Elektronikoa
We propose a new blind deconvolution method for transient impulsive signals in a single input – multiple output (SIMO) system. The method exploits the data redundancy inherent to SIMO multichannel systems to obtain an estimation of the input signal. The method is built upon the assumptions of finite-length signals and channel diversity.
Open Access
Motor abnormalities and cognitive impairment in first-episode psychosis patients, their unaffected siblings and healthy controls
(Elsevier, 2018) Cuesta, Manuel J.; Moreno-Izco, Lucía; Ribeiro Fernández, María; López-Ilundain, José M.; Lecumberri Villamediana, Pablo; Cabada Giadás, María Teresa; Lorente Omeñaca, Ruth; Sánchez Torres, Ana María; Gómez Fernández, Marisol; Peralta Martín, Víctor; Ciencias de la Salud; Osasun Zientziak; Matemáticas; Matematika
Motor abnormalities (MAs) may be already evidenced long before the beginning of illness and are highly prevalent in psychosis. However, the extent to which the whole range of MAs are related to cognitive impairment in psychosis remains understudied. This study aimed to examine comparatively the relationships between the whole range of motor abnormalities and cognitive impairments in the first-episode of psychosis (FEP), their unaffected siblings and healthy control subjects. Fifty FEP patients, 21 of their healthy siblings and 24 age- and sex matched healthy controls were included. Motor assessment included catatonic, extrapyramidal and neurological soft signs (NSS) by means of standardized instruments. An exhaustive neuropsychological battery was also performed to extract the 7 cognitive dimensions of MATRICS initiative. Higher scores on NSS but not on extrapyramidal and catatonic signs showed significant associations with worse cognitive performance in the three study groups. However, the pattern of associations regarding specific cognitive functions was different among the three groups. Moreover, extrapyramidal signs showed significant associations with cognitive impairment only in FEP patients but not in their unaffected siblings and healthy controls. Catatonic signs did not show any significant association with cognitive functioning in the three study groups. These findings add evidence to the associations between motor abnormalities, particularly NSS and extrapyramidal signs, and cognitive impairment in first-episode psychosis patients. In addition, our results suggest that the specific pattern of associations between MAs and cognitive functioning is different in FEP patients from those of the unaffected siblings and healthy subjects.
Embargo
Enhancing sensorimotor BCI performance with assistive afferent activity: an online evaluation
(Elsevier, 2019) Vidaurre Arbizu, 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
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
Women, Science and Technology Chair—Promoting women’s careers in stem fields
(IEEE, 2023) Pérez Artieda, Miren Gurutze; Gómez Fernández, Marisol; Aranguren Garacochea, Patricia; Barrenechea Tartas, Edurne; Catalán Ros, Leyre; Díaz Lucas, Silvia; Jurío Munárriz, Aránzazu; Martínez Ramírez, Alicia; Millor Muruzábal, Nora; Ortiz Nicolás, Amalia; San Martín Biurrun, Idoia; Estadística, Informática y Matemáticas; Ingeniería; Ingeniería Eléctrica, Electrónica y de Comunicación; Estatistika, Informatika eta Matematika; Ingeniaritza; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren
The Chair of Women, Science and Technology of the Universidad Pública de Navarra (UPNA) aims to increase the participation of women in the fields of science and technology. Scientific culture and dissemination are the main focus of the different actions of the Chair. These activities include: the theatrical performance "Yo quiero ser científica", experimental workshops and conferences and exhibitions for all audiences and ages. More than 6.000 people have seen the play, more than 1.500 secondary school students have participated in the workshops and the audiovisual material has received more than 20.000 visits.
Open Access
Degree of totalness: how to choose the best admissible permutation for vector fuzzy integration
(Elsevier, 2023-08-30) Ferrero Jaurrieta, Mikel; Horanská, Lubomíra; Lafuente López, Julio; Mesiar, Radko; Pereira Dimuro, Graçaliz; Takáč, Zdenko; Gómez Fernández, Marisol; Fernández Fernández, Francisco Javier; Bustince Sola, Humberto; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika
The use of aggregation operators that require ordering of the data brings a problem when the structures to be aggregated are multi-valued, since there may be several admissible orders. To addressing this problem, the concept of admissible permutation was introduced for intervals. In this paper we extend this concept to vector domain. However, the problem of selecting the best possible permutation is still an open problem. In this paper we present a novel concept in order to choose the best admissible permutation for vectors: the degree of totalness. This concept allows us to represent to which degree the admissible permutation reorder given vectors as a chain with respect to the partial order. Finally, from the best admissible permutation we construct the Choquet integral.
Open Access
Frailty assessment based on trunk kinematic parameters during walking
(BioMed Central, 2015) Martínez Ramírez, Alicia; Martinikorena Aranburu, Ion; Gómez Fernández, Marisol; Lecumberri Villamediana, Pablo; Millor Muruzábal, Nora; Rodríguez Mañas, Leocadio; García García, Francisco José; Izquierdo Redín, Mikel; Matemáticas; Matematika
Background: Physical frailty has become the center of attention of basic, clinical and demographic research due to its incidence level and gravity of adverse outcomes with age. Frailty syndrome is estimated to affect 20 % of the population older than 75 years. Thus, one of the greatest current challenges in this field is to identify parameters that can discriminate between vulnerable and robust subjects. Gait analysis has been widely used to predict frailty. The aim of the present study was to investigate whether a collection of parameters extracted from the trunk acceleration signals could provide additional accurate information about frailty syndrome. Methods: A total of 718 subjects from an elderly population (319 males, 399 females; age: 75.4 ± 6.1 years, mass: 71.8 ± 12.4 kg, height: 158 ± 6 cm) volunteered to participate in this study. The subjects completed a 3-m walk test at their own gait velocity. Kinematic data were acquired from a tri-axial inertial orientation tracker. Findings: The spatio-temporal and frequency parameters measured in this study with an inertial sensor are related to gait disorders and showed significant differences among groups (frail, pre-frail and robust). A selection of those parameters improves frailty classification obtained to gait velocity, compared to classification model based on gait velocity solely. Interpretation: Gait parameters simultaneously used with gait velocity are able to provide useful information for a more accurate frailty classification. Moreover, this technique could improve the early detection of pre-frail status, allowing clinicians to perform measurements outside of a laboratory environment with the potential to prescribe a treatment for reversing their physical decline.
Open Access
Improving motor imagery classification during induced motor perturbations
(IOP Publishing, 2021) Vidaurre Arbizu, Carmen; Jorajuria Gómez, Tania; Ramos Murguialday, Ander; Müller, Klaus Robert; Gómez Fernández, Marisol; Nikulin, Vadim V.; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika
Objective. Motor imagery is the mental simulation of movements. It is a common paradigm to design brain-computer interfaces (BCIs) that elicits the modulation of brain oscillatory activity similar to real, passive and induced movements. In this study, we used peripheral stimulation to provoke movements of one limb during the performance of motor imagery tasks. Unlike other works, in which induced movements are used to support the BCI operation, our goal was to test and improve the robustness of motor imagery based BCI systems to perturbations caused by artificially generated movements. Approach. We performed a BCI session with ten participants who carried out motor imagery of three limbs. In some of the trials, one of the arms was moved by neuromuscular stimulation. We analysed 2-class motor imagery classifications with and without movement perturbations. We investigated the performance decrease produced by these disturbances and designed different computational strategies to attenuate the observed classification accuracy drop. Main results. When the movement was induced in a limb not coincident with the motor imagery classes, extracting oscillatory sources of the movement imagination tasks resulted in BCI performance being similar to the control (undisturbed) condition; when the movement was induced in a limb also involved in the motor imagery tasks, the performance drop was significantly alleviated by spatially filtering out the neural noise caused by the stimulation. We also show that the loss of BCI accuracy was accompanied by weaker power of the sensorimotor rhythm. Importantly, this residual power could be used to predict whether a BCI user will perform with sufficient accuracy under the movement disturbances. Significance. We provide methods to ameliorate and even eliminate motor related afferent disturbances during the performance of motor imagery tasks. This can help improving the reliability of current motor imagery based BCI systems.
Open Access
Novel multivariate methods to track frequency shifts of neural oscillations in EEG/MEG recordings
(Elsevier, 2023) Vidaurre Arbizu, Carmen; Gurunandan, Kshipra; Jamshidi Idaji, Mina; Nolte, Guido; Gómez Fernández, Marisol; Villringer, Arno; Müller, Klaus Robert; Nikulin, Vadim V.; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika
Instantaneous and peak frequency changes in neural oscillations have been linked to many perceptual, motor, and cognitive processes. Yet, the majority of such studies have been performed in sensor space and only occasionally in source space. Furthermore, both terms have been used interchangeably in the literature, although they do not reflect the same aspect of neural oscillations. In this paper, we discuss the relation between instantaneous frequency, peak frequency, and local frequency, the latter also known as spectral centroid. Furthermore, we propose and validate three different methods to extract source signals from multichannel data whose (instantaneous, local, or peak) frequency estimate is maximally correlated to an experimental variable of interest. Results show that the local frequency might be a better estimate of frequency variability than instantaneous frequency under conditions with low signal-to-noise ratio. Additionally, the source separation methods based on local and peak frequency estimates, called LFD and PFD respectively, provide more stable estimates than the decomposition based on instantaneous frequency. In particular, LFD and PFD are able to recover the sources of interest in simulations performed with a realistic head model, providing higher correlations with an experimental variable than multiple linear regression. Finally, we also tested all decomposition methods on real EEG data from a steady-state visual evoked potential paradigm and show that the recovered sources are located in areas similar to those previously reported in other studies, thus providing further validation of the proposed methods.