Person: Cabeza Laguna, Rafael
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Cabeza Laguna
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Rafael
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Publication Open Access Differences in specific abdominal fat depots between metabolically healthy and unhealthy children with overweight/obesity: the role of cardiorespiratory fitness(Wiley, 2023) Cadenas-Sánchez, Cristina; Medrano Echeverría, María; Villanueva Larre, Arantxa; Cabeza Laguna, Rafael; Idoate, Fernando; Osés Recalde, Maddi; Rodríguez Vigil, Beatriz; Álvarez de Eulate, Natalia; Alberdi Aldasoro, Nerea; Ortega, Francisco B.; Labayen Goñi, Idoia; Ciencias de la Salud; Ingeniería Eléctrica, Electrónica y de Comunicación; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD; Institute of Smart Cities - ISC; Osasun Zientziak; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio IngeniaritzarenObjectives: Fat depots localization has a critical role in the metabolic health status of adults. Nevertheless, whether that is also the case in children remains under- studied. Therefore, the aims of this study were: (i) to examine the differ-ences between metabolically healthy (MHO) and unhealthy (MUO) overweight/obesity phenotypes on specific abdominal fat depots, and (ii) to further explore whether cardiorespiratory fitness plays a major role in the differences between metabolic phenotypes among children with overweight/obesity. Methods: A total of 114 children with overweight/obesity (10.6 ±1.1 years, 62 girls) were included. Children were classified as MHO (n=68) or MUO. visceral (VAT), abdominal subcutaneous (ASAT), intermuscular abdominal (IMAAT), psoas, hepatic, pancreatic, and lumbar bone marrow adipose tissues were measured by magnetic resonance imaging. Cardiorespiratory fitness was assessed using the 20 m shuttle run test. Results: MHO children had lower VAT and ASAT contents and psoas fat fraction compared to MUO children (difference =12.4%– 25.8%, all p<0.035). MUO- unfit had more VAT and ASAT content than those MUO- fit and MHO- fit (difference =34.8%– 45.3%, all p<0.044). MUO- unfit shows also greater IMAAT fat fraction than those MUO- fit and MHO- fit peers (difference =16.4%– 13.9% respectively, all p≤0.001). In addition, MHO- unfit presented higher IMAAT fat fraction than MHO- fit (difference =13.4%, p<0.001). MUO- unfit presented higher psoas fat fraction than MHO- fit (difference =29.1%, p=0.008). Conclusions: VAT together with ASAT and psoas fat fraction, were lower in MHO than in MUO children. Further, we also observed that being fit, regardless of metabolic phenotype, has a protective role over the specific abdominal fat depots among children with overweight/obesity.Publication Open Access Effects of a family-based lifestyle intervention plus supervised exercise training on abdominal fat depots in children with overweight or obesity: a secondary analysis of a nonrandomized clinical trial(American Medical Association, 2022) Cadenas-Sánchez, Cristina; Cabeza Laguna, Rafael; Idoate, Fernando; Osés Recalde, Maddi; Medrano Echeverría, María; Villanueva Larre, Arantxa; Arenaza, Lide; Sanz Muñoz, Aritz; Ortega, Francisco B.; Ruiz, Jonatan R.; Labayen Goñi, Idoia; Ciencias de la Salud; Ingeniería Eléctrica, Electrónica y de Comunicación; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD; Institute of Smart Cities - ISC; Osasun Zientziak; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio IngeniaritzarenImportance Excess abdominal fat is a major determinant in the development of insulin resistance and other metabolic disorders. Increased visceral adipose tissue (VAT) seems to precede the development of insulin resistance and is therefore a prime target of childhood lifestyle interventions aimed at preventing diabetes. OBJECTIVES To examine the effect of added exercise to a family-based lifestyle intervention program designed to reduce VAT plus subcutaneous (ASAT), intermuscular (IMAAT), and pancreatic (PAT) adipose tissue in children with overweight or obesity and to explore the effect of changes in VAT on insulin resistance. DESIGN, SETTING, AND PARTICIPANTS This 2-group, parallel-design clinical trial was conducted in Vitoria-Gasteiz, Spain. A total of 116 children with overweight or obesity participated and were assigned to a 22-week family-based lifestyle program (control group [n = 57]) or the same program plus an exercise intervention (exercise group [n = 59]). Data were collected between September 1, 2014, and June 30, 2017, and imaging processing for fat depot assessments and data analysis were performed between May 1, 2019, and February 12, 2021. INTERVENTIONS The compared interventions consisted of a family-based lifestyle and psychoeducation program (two 90-minute sessions per month) and the same program plus supervised exercise (three 90-minute sessions per week). MAIN OUTCOMES AND MEASURES The primary outcome of this study was the change in VAT between baseline and 22 weeks as estimated by magnetic resonance imaging. The secondary outcomes were changes in ASAT, IMAAT, and PAT. The effect of changes in VAT area on insulin resistance was also recorded. RESULTS The 116 participants included in the analysis (62 girls [53.4%]) had a mean (SD) age of 10.6 (1.1) years, and 67 (57.8%) presented with obesity. Significantly greater reductions were recorded for the exercise group in terms of reduction in VAT (−18.1% vs −8.5% for the control group; P = .004), ASAT (−9.9% vs −3.0%; P = .001), and IMAAT (−6.0% vs −2.6%; P = .02) fat fractions compared with the control group. Changes in VAT explained 87.6% of the improvement seen in insulin resistance (β = −0.102 [95% CI, −0.230 to −0.002]). CONCLUSIONS AND RELEVANCE These findings suggest that the addition of exercise to a lifestyle intervention program substantially enhanced the positive effects on abdominal fat depots in children with overweight or obesity. In addition, the reduction in VAT seemed to largely mediate the improvement of insulin sensitivity. These results highlight the importance of including exercise as part of lifestyle therapies aimed at treating childhood obesity and preventing the development of type 2 diabetes.Publication Open Access Synthetic gaze data augmentation for improved user calibration(Springer, 2021) Garde Lecumberri, Gonzalo; Larumbe Bergera, Andoni; Porta Cuéllar, Sonia; Cabeza Laguna, Rafael; Villanueva Larre, Arantxa; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; Ingeniería Eléctrica, Electrónica y de ComunicaciónIn this paper, we focus on the calibration possibilitiesó of a deep learning based gaze estimation process applying transfer learning, comparing its performance when using a general dataset versus when using a gaze specific dataset in the pretrained model. Subject calibration has demonstrated to improve gaze accuracy in high performance eye trackers. Hence, we wonder about the potential of a deep learning gaze estimation model for subject calibration employing fine-tuning procedures. A pretrained Resnet-18 network, which has great performance in many computer vision tasks, is fine-tuned using user’s specific data in a few shot adaptive gaze estimation approach. We study the impact of pretraining a model with a synthetic dataset, U2Eyes, before addressing the gaze estimation calibration in a real dataset, I2Head. The results of the work show that the success of the individual calibration largely depends on the balance between fine-tuning and the standard supervised learning procedures and that using a gaze specific dataset to pretrain the model improves the accuracy when few images are available for calibration. This paper shows that calibration is feasible in low resolution scenarios providing outstanding accuracies below 1.5 ∘ ∘ of error.Publication Open Access Development of a prediction protocol for the screening of metabolic associated fatty liver disease in children with overweight or obesity(Wiley, 2022) Osés Recalde, Maddi; Cadenas-Sánchez, Cristina; Medrano Echeverría, María; Galbete Jiménez, Arkaitz; Miranda Ferrúa, Emiliano; Ruiz, Jonatan R.; Sánchez-Valverde, Felix; Ortega, Francisco B.; Cabeza Laguna, Rafael; Villanueva Larre, Arantxa; Idoate, Fernando; Labayen Goñi, Idoia; Osasun Zientziak; Institute of Smart Cities - ISC; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD; Ciencias de la Salud; Gobierno de Navarra / Nafarroako GobernuaBackground: the early detection and management of children with metabolic associ-ated fatty liver disease (MAFLD) is challenging. Objective: to develop a non-invasive and accurate prediction protocol for the identi-fication of MAFLD among children with overweight/obesity candidates to confirma-tory diagnosis. Methods: a total of 115 children aged 8–12 years with overweight/obesity, rec-ruited at a primary care, were enrolled in this cross-sectional study. The external vali-dation was performed using a cohort of children with overweight/obesity (N=46)aged 8.5–14.0 years. MAFLD (≥5.5% hepatic fat) was diagnosed by magnetic reso-nance imaging (MRI). Fasting blood biochemical parameters were measured, and25 candidates’ single nucleotide polymorphisms (SNPs) were determined. Variablespotentially associated with the presence of MAFLD were included in a multivariatelogistic regression. Results: children with MAFLD (36%) showed higher plasma triglycerides (TG),insulin, homeostasis model assessment ofinsulin resistance (HOMA-IR), alanineaminotransferase (ALT), aspartate transaminase (AST), glutamyl-transferase (GGT)and ferritin (p< 0.05). The distribution of the risk-alleles of PPARGrs13081389, PPARGrs1801282, HFErs1800562 and PNLPLA3rs4823173 was significantly different between children with and without MAFLD (p<0.05). Threebiochemical- and/or SNPs-based predictive models were developed, showingstrong discriminatory capacity (AUC-ROC: 0.708–0.888) but limited diagnosticperformance (sensitivity 67%–82% and specificity 63%–69%). A prediction proto-col with elevated sensitivity (72%) and specificity (84%) based on two consecutive steps was developed. The external validation showed similar results: sensitivity of 70% and specificity of 85%. Conclusions: the HEPAKID prediction protocol is an accurate, easy to implant, minimally invasive and low economic cost tool useful for the early identification and management of paediatric MAFLD in primary care.Publication 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 IngeniaritzarenEye 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.Publication Open Access Accurate pupil center detection in off-the-shelf eye tracking systems using convolutional neural networks(MDPI, 2021) Larumbe Bergera, Andoni; Garde Lecumberri, Gonzalo; Porta Cuéllar, Sonia; Cabeza Laguna, Rafael; Villanueva Larre, Arantxa; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Universidad Pública de Navarra / Nafarroako Unibertsitate PublikoaRemote eye tracking technology has suffered an increasing growth in recent years due to its applicability in many research areas. In this paper, a video-oculography method based on convolutional neural networks (CNNs) for pupil center detection over webcam images is proposed. As the first contribution of this work and in order to train the model, a pupil center manual labeling procedure of a facial landmark dataset has been performed. The model has been tested over both real and synthetic databases and outperforms state-of-the-art methods, achieving pupil center estimation errors below the size of a constricted pupil in more than 95% of the images, while reducing computing time by a 8 factor. Results show the importance of use high quality training data and well-known architectures to achieve an outstanding performance.Publication Open Access Time-restricted eating and supervised exercise for improving hepatic steatosis and cardiometabolic health in adults with obesity: protocol for the TEMPUS randomised controlled trial(BMJ Publishing Group, 2024) Camacho-Cardenosa, Alba; Clavero-Jimeno, Antonio; Martín-Olmedo, Juan J.; Amaro Gahete, Francisco J.; Cupeiro, Rocío; González Cejudo, María Trinidad; García Pérez, Patricia Virginia; Hernández-Martínez, Carlos; Sevilla-Lorente, Raquel; O, Alejandro de la; López-Vázquez, Alejandro; Molina-Fernández, Marcos; Carneiro-Barrera, Almudena; García, Federico; Rodríguez-Nogales, Alba; Gálvez Peralta, Julio Juan; Cabeza Laguna, Rafael; Martín-Rodríguez, José L.; Muñoz-Garach, Araceli; Muñoz Torres, Manuel; Labayen Goñi, Idoia; Ruiz, Jonatan R.; Ciencias de la Salud; Osasun Zientziak; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoa eta Telekomunikazio Ingeniaritza; Institute on Innovation and Sustainable Development in Food Chain - ISFOODIntroduction. Metabolic dysfunction-associated steatotic liver disease is a major public health problem considering its high prevalence and its strong association with extrahepatic diseases. Implementing strategies based on an intermittent fasting approach and supervised exercise may mitigate the risks. This study aims to investigate the effects of a 12-week time-restricted eating (TRE) intervention combined with a supervised exercise intervention, compared with TRE or supervised exercise alone and with a usual-care control group, on hepatic fat (primary outcome) and cardiometabolic health (secondary outcomes) in adults with obesity. Methods and análisis. An anticipated 184 adults with obesity (50% women) will be recruited from Granada (south of Spain) for this parallel-group, randomised controlled trial (TEMPUS). Participants will be randomly designated to usual care, TRE alone, supervised exercise alone or TRE combined with supervised exercise, using a parallel design with a 1:1:1:1 allocation ratio. The TRE and TRE combined with supervised exercise groups will select an 8-hour eating window before the intervention and will maintain it over the intervention. The exercise alone and TRE combined with exercise groups will perform 24 sessions (2 sessions per week+walking intervention) of supervised exercise combining resistance and aerobic high-intensity interval training. All participants will receive nutritional counselling throughout the intervention. The primary outcome is change from baseline to 12 weeks in hepatic fat; secondary outcomes include measures of cardiometabolic health. Ethics and dissemination. This study was approved by Granada Provincial Research Ethics Committee (CEI Granada—0365-N-23). All participants will be asked to provide written informed consent. The findings will be disseminated in scientific journals and at international scientific conferences. Trial registration number NCT05897073.Publication Open Access Low-cost eye tracking calibration: a knowledge-based study(MDPI, 2021) Garde Lecumberri, Gonzalo; Larumbe Bergera, Andoni; Bossavit, Benoît; Porta Cuéllar, Sonia; Cabeza Laguna, Rafael; Villanueva Larre, Arantxa; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio IngeniaritzarenSubject calibration has been demonstrated to improve the accuracy in high-performance eye trackers. However, the true weight of calibration in off-the-shelf eye tracking solutions is still not addressed. In this work, a theoretical framework to measure the effects of calibration in deep learning-based gaze estimation is proposed for low-resolution systems. To this end, features extracted from the synthetic U2Eyes dataset are used in a fully connected network in order to isolate the effect of specific user’s features, such as kappa angles. Then, the impact of system calibration in a real setup employing I2Head dataset images is studied. The obtained results show accuracy improvements over 50%, probing that calibration is a key process also in low-resolution gaze estimation scenarios. Furthermore, we show that after calibration accuracy values close to those obtained by high-resolution systems, in the range of 0.7°, could be theoretically obtained if a careful selection of image features was performed, demonstrating significant room for improvement for off-the-shelf eye tracking systemsPublication Open Access The effect of a multicomponent intervention on steatosis is partially mediated by the reduction of intermuscular abdominal adipose tissue in children with overweight or obesity: the EFIGRO Project(American Diabetes Association, 2022) Cadenas-Sánchez, Cristina; Idoate, Fernando; Cabeza Laguna, Rafael; Villanueva Larre, Arantxa; Rodríguez Vigil, Beatriz; Medrano Echeverría, María; Osés Recalde, Maddi; Ortega, Francisco B.; Ruiz, Jonatan R.; Labayen Goñi, Idoia; Osasun Zientziak; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Institute of Smart Cities - ISC; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD; Ciencias de la Salud; Ingeniería Eléctrica, Electrónica y de Comunicación; Gobierno de Navarra / Nafarroako GobernuaOBJECTIVE: In adults, there is evidence that improvement of metabolic-associated fatty liver disease (MAFLD) depends on the reduction of myosteatosis. In children, in whom the prevalence of MAFLD is alarming, this muscle-liver crosstalk has not been tested. Therefore, we aimed to explore whether the effects of a multicomponent intervention on hepatic fat is mediated by changes in intermuscular abdominal adipose tissue (IMAAT) in children with overweight/obesity. RESEARCH DESIGN AND METHODS: A total of 116 children with overweight/obesity were allocated to a 22-week family-based lifestyle and psychoeducational intervention (control group, n = 57) or the same intervention plus supervised exercise (exercise group, n = 59). Hepatic fat percentage and IMAAT were acquired by MRI at baseline and at the end of the intervention. RESULTS: Changes in IMAAT explained 20.7% of the improvements in hepatic steatosis (P < 0.05). Only children who meaningfully reduced their IMAAT (i.e., responders) had improved hepatic steatosis at the end of the intervention (within-group analysis: responders -20% [P = 0.005] vs. nonresponders -1.5% [P = 0.803]). Between-group analysis showed greater reductions in favor of IMAAT responders compared with nonresponders (18.3% vs. 0.6%, P = 0.018), regardless of overall abdominal fat loss. CONCLUSIONS: The reduction of IMAAT plays a relevant role in the improvement of hepatic steatosis after a multicomponent intervention in children with overweight/obesity. Indeed, only children who achieved a meaningful reduction in IMAAT at the end of the intervention had a reduced percentage of hepatic fat independent of abdominal fat loss. Our findings suggest that abdominal muscle fat infiltration could be a therapeutic target for the treatment of MAFLD in childhood.Publication Open Access Gaze estimation problem tackled through synthetic images(Association for Computing Machinery (ACM), 2020) Garde Lecumberri, Gonzalo; Larumbe Bergera, Andoni; Bossavit, Benoît; Cabeza Laguna, Rafael; Porta Cuéllar, Sonia; Villanueva Larre, Arantxa; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio IngeniaritzarenIn this paper, we evaluate a synthetic framework to be used in the field of gaze estimation employing deep learning techniques. The lack of sufficient annotated data could be overcome by the utilization of a synthetic evaluation framework as far as it resembles the behavior of a real scenario. In this work, we use U2Eyes synthetic environment employing I2Head datataset as real benchmark for comparison based on alternative training and testing strategies. The results obtained show comparable average behavior between both frameworks although significantly more robust and stable performance is retrieved by the synthetic images. Additionally, the potential of synthetically pretrained models in order to be applied in user's specific calibration strategies is shown with outstanding performances.