Mario Martínez-Zarzuela

TL;DR: The automation of the human body parts motion monitoring, its analysis in relation to the psychomotor exercise indicated to the patient, and the storage of the result of the realization of a set of exercises free the rehabilitation experts of doing such demanding tasks.

TL;DR: This work combines the ensemble method with a recently proposed transfer entropy estimator to make transfer entropy estimation applicable to non-stationary time series and tests the performance and robustness of the implementation on data from numerical simulations of stochastic processes.

TL;DR: A new methodological approach for short‐term predictions of time series of volume data at isolated cross sections using a self‐organizing fuzzy neural network for learning and recognition of patterns that characterize the evolution of its samples over a fixed prediction horizon is proposed.

TL;DR: In this article, the authors presented a fully automatic brain tumor segmentation and classification model using a deep convolutional neural network that includes a multiscale approach, where input images are processed in three spatial scales along different processing pathways.

TL;DR: The development of a customized virtual reality system based on a serious game which allows the user to carry out physical and cognitive rehabilitation therapies using a natural user interface based on Microsoft© Kinect is introduced.