activity
20202023
most citedEEG Connectivity Analysis Using Denoising Autoencoders for the Detection of Dyslexia

41 citations · 57 across the 5 of their papers we have counts for

collaborators

5 papers

q-bio.NC2023★ 41 cited

EEG Connectivity Analysis Using Denoising Autoencoders for the Detection of Dyslexia

Francisco Jesus Martinez-Murcia, Andrés Ortiz, Juan Manuel Górriz +4

The Temporal Sampling Framework (TSF) theorizes that the characteristic phonological difficulties of dyslexia are caused by an atypical oscillatory sampling at one or more temporal…

q-bio.NC2021★ 2 cited

Temporal EigenPAC for dyslexia diagnosis

Nicolás Gallego-Molina, Marco Formoso, Andrés Ortiz +2

Electroencephalography signals allow to explore the functional activity of the brain cortex in a non-invasive way. However, the analysis of these signals is not straightforward due…

q-bio.NC2021

Modelling Brain Connectivity Networks by Graph Embedding for Dyslexia Diagnosis

Marco A. Formoso, Andrés Ortiz, Francisco J. Martínez-Murcia +2

Several methods have been developed to extract information from electroencephalograms (EEG). One of them is Phase-Amplitude Coupling (PAC) which is a type of Cross-Frequency Coupli…

eess.SP2020★ 12 cited

Dyslexia detection from EEG signals using SSA component correlation and Convolutional Neural Networks

Andrés Ortiz, Francisco J. Martinez-Murcia, Marco A. Formoso +2

Objective dyslexia diagnosis is not a straighforward task since it is traditionally performed by means of the intepretation of different behavioural tests. Moreover, these tests ar…

cs.LG2020★ 2 cited

A Neural Approach to Ordinal Regression for the Preventive Assessment of Developmental Dyslexia

F. J. Martinez-Murcia, A. Ortiz, Marco A. Formoso +3

Developmental Dyslexia (DD) is a learning disability related to the acquisition of reading skills that affects about 5% of the population. DD can have an enormous impact on the int…