Listar por autor "Rodríguez Rodríguez, Ignacio"
Mostrando ítems 1-6 de 6
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A Comparison of Feature Selection and Forecasting Machine Learning Algorithms for Predicting Glycaemia in Type 1 Diabetes Mellitus
(IOAP-MPDI, 2021-02-16)Type 1 diabetes mellitus (DM1) is a metabolic disease derived from falls in pancreatic insulin production resulting in chronic hyperglycemia. DM1 subjects usually have to undertake a number of assessments of blood glucose ... -
Generation of Virtual Children for testing a Recommendation System for Interventions with Children with Dyslexia.
Mateo-Trujillo, J. Ignacio; Rodríguez Rodríguez, Ignacio; Castillo-Barnes, Diego; Ortiz-García, Andrés
; Luque-Vilaseca, Juan Luis (2024)
The LEEDUCA project has developed a recommendation system to generate intervention sessions tailored to children with dyslexia. Due to the limitations in obtaining real data for preliminary testing, the generation of in ... -
Inter-channel Granger Causality for Estimating EEG Phase Connectivity Patterns in Dyslexia
Rodríguez Rodríguez, Ignacio; Ortiz-García, Andrés; Formoso, Marco A.; Gallego-Molina, Nicolás J.; Luque-Vilaseca, Juan Luis (2022)
Methods like Electroencephalography (EEG) and magnetoencephalogram (MEG) record brain oscillations and provide an invaluable insight into healthy and pathological brain function. These signals are helpful to study and ... -
Nonlinear Neural Dynamics of Language Processing: A Recurrence Quantification Analysis of EEG in Dyslexia.
Rodríguez Rodríguez, Ignacio; Mateo-Trujillo, J. Ignacio; Formoso, Marco A.; Gallego-Molina, Nicolás J.; Ortiz-García, Andrés; Luque-Vilaseca, Juan Luis[et al.] (2024)
This study investigates the application of chaos theory and Recurrence Quantification Analysis (RQA) to EEG signals in skilled and dyslexic readers. By quantifying the nonlinear dynamics of brain activity, we aim to identify ... -
Tecnologías digitales disruptivas aplicadas a la gestión de la pandemia por COVID-19: un análisis a través de la producción científica
(UMA Editorial, 2022)Este libro presenta un estudio acerca de las tecnologías digitales disruptivas (Internet of Things, Machine Learning, Blockchain y otras) que se han aplicado a la gestión de la pandemia ocasionada por la COVID-19. La ... -
Using the Uniform Theory of Diffraction to Analyze Radio Wave Propagation along Urban Street Canyons for Device-to-Device Communication
(IOAP-MDPI, 2023-01-25)This paper examines the propagation of radio waves in so-called urban street canyons through formulations based on Geometrical Optics (GO) and the Uniform Theory of Diffraction (UTD). As this type of environment comprises ...