Open Access
Optimizing interoperability between video-oculographic and electromyographic systems
(Rehabilitation Research & Development Service, 2011) Navallas Irujo, Javier; Ariz Galilea, Mikel; Villanueva Larre, Arantxa; San Agustín, Javier; Cabeza Laguna, Rafael; Ingeniería Eléctrica y Electrónica; Ingeniaritza Elektrikoa eta Elektronikoa
A new system is presented that enhances the interoperability between a video-oculographic (VOG) system for mouse movement control and an electromyographic (EMG) system for mouse click detection. The proposed VOG-EMG system combines gaze and muscle information to minimize the number of undesired clicks due to involuntary activations and environmental noise. We tested the system with 24 subjects, comparing three different configurations: one in which the VOG and EMG systems worked independently and two in which we used VOG gaze information to improve the EMG click detection. Results show that the number of false-positive click detections can be reduced when VOG and EMG information is combined. In addition, the third configuration, including extra processing, can reduce the activation delay produced because of the combined use of the VOG and EMG systems. The new VOG-EMG system is meant to be used in noisy environments in which the number of false clicks may impeach a reliable human-computer interaction.
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Evaluación de algoritmos de detección de activación en señales s-EMG para integración en un sistema de eye-tracking
(2008) Ariz Galilea, Mikel; Escuela Técnica Superior de Ingenieros Industriales y de Telecomunicación; Telekomunikazio eta Industria Ingeniarien Goi Mailako Eskola Teknikoa
Open Access
Robust and accurate 2D-tracking-based 3D positioning method: application to head pose estimation
(Elsevier, 2019) Ariz Galilea, Mikel; Villanueva Larre, Arantxa; Cabeza Laguna, Rafael; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren
Head pose estimation (HPE) is currently a growing research field, mainly because of the proliferation of human–computer interfaces (HCI) in the last decade. It offers a wide variety of applications, including human behavior analysis, driver assistance systems or gaze estimation systems. This article aims to contribute to the development of robust and accurate HPE methods based on 2D tracking of the face, enhancing performance of both 2D point tracking and 3D pose estimation. We start with a baseline method for pose estimation based on POSIT algorithm. A novel weighted variant of POSIT is then proposed, together with a methodology to estimate weights for the 2D–3D point correspondences. Further, outlier detection and correction methods are also proposed in order to enhance both point tracking and pose estimation. With the aim of achieving a wider impact, the problem is addressed using a global approach: all the methods proposed are generalizable to any kind of object for which an approximate 3D model is available. These methods have been evaluated for the specific task of HPE using two different head pose video databases; a recently published one that reflects the expected performance of the system in current technological conditions, and an older one that allows an extensive comparison with state-of-the-art HPE methods. Results show that the proposed enhancements improve the accuracy of both 2D facial point tracking and 3D HPE, with respect to the implemented baseline method, by over 15% in normal tracking conditions and over 30% in noisy tracking conditions. Moreover, the proposed HPE system outperforms the state of the art on the two databases.
Open Access
Synplex: in silico modeling of the tumor microenvironment from multiplex images
(IEEE, 2023) Jiménez Sánchez, Daniel; Ariz Galilea, Mikel; Andrea, Carlos de; Ortiz de Solórzano, Carlos; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoa eta Telekomunikazio Ingeniaritza
Multiplex immunofluorescence is a novel, high-content imaging technique that allows simultaneous in situ labeling of multiple tissue antigens. This technique is of growing relevance in the study of the tumor microenvironment, and the discovery of biomarkers of disease progression or response to immune-based therapies. Given the number of markers and the potential complexity of the spatial interactions involved, the analysis of these images requires the use of machine learning tools that rely for their training on the availability of large image datasets, extremely laborious to annotate. We present Synplex, a computer simulator of multiplexed immunofluorescence images from user-defined parameters: i. cell phenotypes, defined by the level of expression of markers and morphological parameters; ii. cellular neighborhoods based on the spatial association of cell phenotypes; and iii. interactions between cellular neighborhoods. We validate Synplex by generating synthetic tissues that accurately simulate real cancer cohorts with underlying differences in the composition of their tumor microenvironment and show proof-of-principle examples of how Synplex could be used for data augmentation when training machine learning models, and for the in silico selection of clinically relevant biomarkers. Synplex is publicly available at https://github.com/djimenezsanchez/Synplex.
Open Access
Improved strategies for HPE employing learning-by-synthesis approaches
(IEEE, 2018) Larumbe Bergera, Andoni; Ariz Galilea, Mikel; Bengoechea Irañeta, José Javier; Segura, Rubén; Cabeza Laguna, Rafael; Villanueva Larre, Arantxa; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren
The first contribution of this paper is the presentation of a synthetic video database where the groundtruth of 2D facial landmarks and 3D head poses is available to be used for training and evaluating Head Pose Estimation (HPE) methods. The database is publicly available and contains videos of users performing guided and natural movements. The second and main contribution is the submission of a hybrid method for HPE based on Pose from Ortography and Scaling by Iterations (POSIT). The 2D landmark detection is performed using Random Cascaded-Regression Copse (R-CR-C). For the training stage we use, state of the art labeled databases. Learning-by-synthesis approach has been also used to augment the size of the database employing the synthetic database. HPE accuracy is tested by using two literature 3D head models. The tracking method proposed has been compared with state of the art methods using Supervised Descent Regressors (SDR) in terms of accuracy, achieving an improvement of 60%.
Open Access
Muscular and tendon degeneration after Achilles rupture: new insights into future repair strategies
(MDPI, 2022) Gil-Melgosa, Lara; Grasa, Jorge; Urbiola, Ainhoa; Llombart, Rafael; Susaeta Ruiz, Miguel; Montiel, Verónica; Ederra, Cristina; Calvo, Begoña; Ariz Galilea, Mikel; Ripalda-Cemborain, Purificación; Prósper, Felipe; Ortiz de Solórzano, Carlos; Pons-Villanueva, Juan; Pérez Ruiz, Ana; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoa eta Telekomunikazio Ingeniaritza
Achilles tendon rupture is a frequent injury with an increasing incidence. After clinical surgical repair, aimed at suturing the tendon stumps back into their original position, the repaired Achilles tendon is often plastically deformed and mechanically less strong than the pre-injured tissue, with muscle fatty degeneration contributing to function loss. Despite clinical outcomes, pre-clinical research has mainly focused on tendon structural repair, with a lack of knowledge regarding injury progression from tendon to muscle and its consequences on muscle degenerative/regenerative processes and function. Here, we characterize the morphological changes in the tendon, the myotendinous junction and muscle belly in a mouse model of Achilles tendon complete rupture, finding cellular and fatty infiltration, fibrotic tissue accumulation, muscle stem cell decline and collagen fiber disorganization. We use novel imaging technologies to accurately relate structural alterations in tendon fibers to pathological changes, which further explain the loss of muscle mechanical function after tendon rupture. The treatment of tendon injuries remains a challenge for orthopedics. Thus, the main goal of this study is to bridge the gap between clinicians’ knowledge and research to address the underlying pathophysiology of ruptured Achilles tendon and its consequences in the gastrocnemius. Such studies are necessary if current practices in regenerative medicine for Achilles tendon ruptures are to be improved.
Open Access
Low cost gaze estimation: knowledge-based solutions
(IEEE, 2020) Martinikorena Aranburu, Ion; Larumbe Bergera, Andoni; Ariz Galilea, Mikel; Porta Cuéllar, Sonia; Cabeza Laguna, Rafael; Villanueva Larre, Arantxa; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren
Eye tracking technology in low resolution scenarios is not a completely solved issue to date. The possibility of using eye tracking in a mobile gadget is a challenging objective that would permit to spread this technology to non-explored fields. In this paper, a knowledge based approach is presented to solve gaze estimation in low resolution settings. The understanding of the high resolution paradigm permits to propose alternative models to solve gaze estimation. In this manner, three models are presented: a geometrical model, an interpolation model and a compound model, as solutions for gaze estimation for remote low resolution systems. Since this work considers head position essential to improve gaze accuracy, a method for head pose estimation is also proposed. The methods are validated in an optimal framework, I2Head database, which combines head and gaze data. The experimental validation of the models demonstrates their sensitivity to image processing inaccuracies, critical in the case of the geometrical model. Static and extreme movement scenarios are analyzed showing the higher robustness of compound and geometrical models in the presence of user’s displacement. Accuracy values of about 3◦ have been obtained, increasing to values close to 5◦ in extreme displacement settings, results fully comparable with the state-of-the-art.
Open Access
Automatic segmentation and quantification of Nigrosome-1 neuromelanin and iron in MRI: A candidate biomarker for parkinson's disease
(Wiley, 2023) Ariz Galilea, Mikel; Martínez, Martín; Álvarez, Ignacio; Fernández Seara, María A.; Castellanos, Gabriel; Catalonian Neuroimaging Parkinson's Disease Consortium; Pastor, Pau; Pastor, María A.; Ortiz de Solórzano, Carlos; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoa eta Telekomunikazio Ingeniaritza; Institute of Smart Cities - ISC
Background: There is a lack of automated tools for the segmentation and quantification of neuromelanin (NM) and iron in the nigrosome-1 (N1). Existing tools evaluate the N1 sign, i.e., the presence or absence of the ‘swallow-tail’ in iron-sensitive MRI, or globally analyze the MRI signal in an area containing the N1, without providing a volumetric delineation. Purpose: Present an automated method to segment the N1 and quantify differences in N1's NM and iron content between Parkinson's disease (PD) patients and healthy controls (HCs). Study whether N1 degeneration is clinically related to PD and could be used as a biomarker of the disease. Study Type: Prospective. Subjects: Seventy-one PD (65.3 ± 10.3 years old, 34 female/37 male); 30 HC (62.7 ± 7.8 years old, 17 female/13 male). Field Strength/Sequence: 3 T Anatomical T1-weighted MPRAGE, NM-MRI T1-weighted gradient with magnetization transfer, susceptibility-weighted imaging (SWI). Assessment: N1 was automatically segmented in SWI images using a multi-image atlas, populated with healthy N1 structures manually annotated by a neurologist. Relative NM and iron content were quantified and their diagnostic performance assessed and compared with the substantia nigra pars compacta (SNc). The association between image parameters and clinically relevant variables was studied. Statistical Tests: Nonparametric tests were used (Mann-Whitney's U, chi-square, and Friedman tests) at P = 0.05. Results: N1's relative NM content decreased and relative iron content increased in PD patients compared with HCs (NM-CRHC = 22.55 ± 1.49; NM-CRPD = 19.79 ± 1.92; NM-nVolHC = 2.69 × 10-5 ± 1.02 × 10-5; NM-nVolPD = 1.18 × 10-5 ± 0.96 × 10−5; Iron-CRHC = 10.51 ± 2.64; Iron-CRPD = 19.35 ± 7.88; Iron-nVolHC = 0.72 × 10-5 ± 0.81 × 10-5; Iron-nVolPD = 2.82 × 10−5 ± 2.04 × 10−5). Binary logistic regression analyses combining N1 and SNc image parameters yielded a top AUC = 0.955. Significant correlation was found between most N1 parameters and both disease duration (ρNM-CR = -0.31; ρiron-CR = 0.43; ρiron-nVol = 0.46) and the motor status ρNM-nVol = -0.27; ρiron-CR = 0.33; ρiron-nVol = 0.28), suggesting NM reduction along with iron accumulation in N1 as the disease progresses. Data Conclusion: This method provides a fully automatic N1 segmentation, and the analyses performed reveal that N1 relative NM and iron quantification improves diagnostic performance and suggest a relative NM reduction along with a relative iron accumulation in N1 as the disease progresses. Evidence Level: 1. Technical Efficacy: Stage 1.
Open Access
Astrocytic GLUT1 reduction paradoxically improves central and peripheral glucose homeostasis
(American Association for the Advancement of Science, 2024-10-18) Ardanaz, Carlos G.; Cruz, Aida de la; Minhas, Paras S.; Hernández-Martín, Nira; Pozo, Miguel Ángel ; Valdecantos, M. Pilar; Martínez Valverde, Ángela; Villa-Valverde, Palmira; Elizalde-Horcada, Marcos; Puerta, Elena; Ramírez, María J.; Ortega, Jorge E.; Urbiola, Ainhoa; Ederra, Cristina; Ariz Galilea, Mikel; Ortiz de Solórzano, Carlos; Fernández Irigoyen, Joaquín; Santamaría Martínez, Enrique; Karsenty, Gerard; Brüning, Jens C. ; Solas, Maite; Ciencias de la Salud; Osasun Zientziak; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoa eta Telekomunikazio Ingeniaritza
Astrocytes are considered an essential source of blood-borne glucose or its metabolites to neurons. Nonetheless, the necessity of the main astrocyte glucose transporter, i.e., GLUT1, for brain glucose metabolism has not been defined. Unexpectedly, we found that brain glucose metabolism was paradoxically augmented in mice with astrocytic GLUT1 reduction (GLUT1ΔGFAP mice). These mice also exhibited improved peripheral glucose metabolism especially in obesity, rendering them metabolically healthier. Mechanistically, we observed that GLUT1-deficient astrocytes exhibited increased insulin receptor–dependent ATP release, and that both astrocyte insulin signaling and brain purinergic signaling are essential for improved brain function and systemic glucose metabolism. Collectively, we demonstrate that astrocytic GLUT1 is central to the regulation of brain energetics, yet its depletion triggers a reprogramming of brain metabolism sufficient to sustain energy requirements, peripheral glucose homeostasis, and cognitive function.
Open Access
In vitro modeling of polyclonal infection dynamics within the human airways by Haemophilus influenzae differential fluorescent labeling
(American Society for Microbiology, 2023) Rapún Araiz, Beatriz; Sorzabal-Bellido, Ioritz; Asensio López, Javier; Lázaro-Díez, María; Ariz Galilea, Mikel; Sobejano de la Merced, Carlos; Euba, Begoña; Fernández Calvet, Ariadna; Cortés Domínguez, Iván; Burgui Erice, Saioa; Toledo Arana, Alejandro; Ortiz de Solórzano, Carlos; Garmendia García, Juncal; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoa eta Telekomunikazio Ingeniaritza; Institute of Smart Cities - ISC
Standardized clinical procedures for antibiotic administration rely on pathogen identification and antibiotic susceptibility testing, often performed on single-colony bacterial isolates. For respiratory pathogens, this could be questionable, as chronic patients may be persistently colonized by multiple clones or lineages from the same bacterial pathogen species. Indeed, multiple strains of nontypeable Haemophilus influenzae, with different antibiotic susceptibility profiles, can be co-isolated from cystic fibrosis and chronic obstructive pulmonary disease sputum specimens. Despite this clinical evidence, we lack information about the dynamics of H. influenzae polyclonal infections, which limits the optimization of therapeutics. Here, we present the engineering and validation of a plasmid toolkit (pTBH, toolbox for Haemophilus), with standardized modules consisting of six reporter genes for fluorescent or bioluminescent labeling of H. influenzae. This plasmid set was independently introduced in a panel of genomically and phenotypically different H. influenzae strains, and two of them were used as a proof of principle to analyze mixed biofilm growth architecture and antibiotic efficacy, and to visualize the dynamics of alveolar epithelial co-infection. The mixed biofilms showed a bilayer architecture, and antibiotic efficacy correlated with the antibiotic susceptibility of the respective single-species strains. Furthermore, differential kinetics of bacterial intracellular location within subcellular acidic compartments were quantified upon co-infection of cultured airway epithelial cells. Overall, we present a panel of novel plasmid tools and quantitative image analysis methods with the potential to be used in a whole range of bacterial host species, assay types, and¿or conditions and generate meaningful information for clinically relevant settings.