A Deep Learning Approach to Estimate Multi-Level Mental Stress from EEG using Serious Games

Stress is revealed by the inability of individuals to cope with their environment, which is frequently evidenced by a failure to achieve their full potential in tasks or goals. This study aims to assess the feasibility of estimating the level of stress that the user is perceiving related to a specific task through an electroencephalograpic (EEG) system. This system is integrated with a Serious Game consisting of a multi-level stress driving tool, and Deep Learning (DL) neural networks are used for classification. The game involves controlling a vehicle to dodge obstacles, with the number of obstacles increasing based on complexity. Assuming that there is a direct correlation between the difficulty level of the game and the stress level of the user, a recurrent neural network (RNN) with a structure based on gated recurrent units (GRU) was used to classify the different levels of stress. The results show that the RNN model is able to predict stress levels above current state-of-the-art with up to 94% accuracy in some cases, suggesting that the use of EEG systems in combination with Serious Games and DL represents a promising technique in the prediction and classification of mental stress levels

Carrying capacity and goat botanical diet composition in an arid ecosystem, Lavalle, Argentina

8 págs, 1 tabla.-- Comunicación presentada a la XLV Reunión Científica de la Sociedad Española para el Estudio de los Pastos: "Producciones agroganaderas: gestión eficiente y conservación del medio natural" (Gijón, 28 de mayo al 3 de junio de 2005).[ES] El trabajo se llevó a cabo en el departamento de Lavalle, Mendoza, Argentina. Las unidades de pastos, más importantes desde el punto de vista forrajero son: Algarrobal de Prosopis flexuosa; Matorral con Atriplex lampa (zampal); Matorral con Tricomaria usillo (usillar); Matorral degradado con Larrea cuneifolia (jarillal) y Medanal. Los objetivos del estudio fueron estimar la capacidad sustentadora de las diferentes unidades y la composición botánica de la ingesta de los caprinos. La estimación de dicha capacidad, expresada en hectáreas por Unidades Ganadera Caprinas (ha UGC–1), se realizó mediante el método de Point Quadrat modificado para el Monte. Y por medio del análisis microhistológico de heces se determinó la composición estacional de la ingesta.Los valores medios anuales de capacidad sustentadora fueron: Algarrobal, 1,2; Zampal, 1,7; Usillar, 3,5; Jarillal, 5,8 y Médanos, 4,3 ha UGC-1. La composición de la ingesta varió durante las estaciones, observándose una predominancia de las especies arbustivas, las gramíneas perennes aparecieron en muy baja frecuencia en todas las estaciones. El Algarrobal y el Zampal son las unidades de mayor importancia forrajera, presentando receptividades ganaderas más altas y una oferta forrajera más estable a lo largo del año, respecto del resto de las unidades de pastos analizadas.[EN] The work was carried out in the department of Lavalle, Mendoza, Argentina. The units of pastures, more important from the forage matter are: Algarrobal of Prosopis flexuosa; Shrubland with Atriplex lampa (zampal); Shrubland with Tricomaria usillo (usillar); Shrubland degraded with Larrea cuneifolia (jarillal) and Dunes. The aims of the study were to estimate the carrying capacity of the different units and the botanical composition of goat diets. The carrying capacity, expressed in hectares by Units Goat (ha UG-1), was measured by the method of Point Quadrat modified for Monte and the seasonal botanical composition of goat diets, was determined by microhistological analysis of faeces. The annual average values of carrying capacity were: Algarrobal, 1.2; Zampal, 1.7; Usillar, 3.5; Jarillal, 5.8 and Dunes, 4.3 ha UG-1. The composition of the diet varied during the seasons, the predominance of the shrubs species were observed, the perennial grass appeared in low frequency in all the seasons. The Algarrobal and the Zampal are the units of greater forage importance, where forage receptivity are higher and with more stable production throughout the year, respect to the others units of pastures analyzed.Peer reviewe

Valoración Radiológica del Fracaso de las Prótesis Cervico-Cefálicas de Cadera en Fracturas de Cuello Femoral y Cirugía de Revisión

Lo s autore s analiza n los diferentes signos radiológicos que sugieren intolerancia de la s prótesis cérvico-cefálicas de cader a implantada s po r fractur a cervical que será n sometida s a Cirugí a de Revisión. Se estudian retrospectivamente 61 casos intervenidos entre los años 77 al 89, analizándos e la evolución de los diferentes modelos: Monk, Austin-Moore, Thompson, Mülle r y Robert-Mathys. Asimismo se estudia n la presencia de calcificaciones intr a y periarticulare s y la aparició n de complicaciones. Po r último, se pretende concretar la indicación de la Artroplasti a parcia l de cader a en paciente s anciano s con alto riesgo quirúrgico en oposición a un mejor resultad o de la Artroplasti a Total en el resto de pacientes.The author s analys e the different radiologica l feature s suggestin g intoleranc e o f the cervical-cephali c hi p prosthesis, implante d b y cervica l fractur e a n d submitte d t o revisio n surgery. Retrospectivel y 6 1 cases, whic h wer e carrie d ou t betwee n 197 7 an d 1989, ar e studied, an d the evolutio n o f the different pattern s i n analysed : Monk, Austin-Moore , Thompson , Mülle r an d Robert-Mathys. A t the sam e time , the presenc e o f intr a an d peri-articula r calcification s an d the appearanc e o f complication s ar e examined . Finally , they inten d t o summariz e th e indicatio n o f the hi p hemiarthroplast y i n ol d patien s wit h a hig h surgica l risk oppositio n t o a bette r result o f the tota l hi p arthroplast y in the rest o f th e patients

The C-terminal region of OVGP1 remodels the zona pellucida and modifies fertility parameters

[EN] OVGP1 is the major non-serum glycoprotein in the oviduct fluid at the time of fertilization and early embryo development. Its activity differs among species. Here, we show that the C-terminal region of recombinant OVGP1 regulates its binding to the extracellular zona pellucida and affects its activity during fertilization. While porcine OVGP1 penetrates two-thirds of the thickness of the zona pellucida, shorter OVGP1 glycoproteins, including rabbit OVGP1, are restricted to the outer one-third of the zona matrix. Deletion of the C-terminal region reduces the ability of the glycoprotein to penetrate through the zona pellucida and prevents OVGP1 endocytosis. This affects the structure of the zona matrix and increases its resistance to protease digestion. However, only full-length porcine OVGP1 is able to increase the efficiency rate of in vitro fertilization. Thus, our findings document that the presence or absence of conserved regions in the C-terminus of OVGP1 modify its association with the zona pellucida that affects matrix structure and renders the zona matrix permissive to sperm penetration and OVGP1 endocytosis into the eggSIThe research was supported by the Spanish MINECO (Spain) and FEDER (AGL2012-40180-C03-01-02 and AGL2015-70159-P) and the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013)/ERC grant agreement 260759 [L.J.]. We thank the Electron Microscopy Service, Image Analysis and Molecular Biology Sections of University of Murcia for their technical assistanc

A Comparison of Myoelectric Control Modes for an Assistive Robotic Virtual Platform

In this paper, we propose a daily living situation where objects in a kitchen can be grasped and stored in specific containers using a virtual robot arm operated by different myoelectric control modes. The main goal of this study is to prove the feasibility of providing virtual environments controlled through surface electromyography that can be used for the future training of people using prosthetics or with upper limb motor impairments. We propose that simple control algorithms can be a more natural and robust way to interact with prostheses and assistive robotics in general than complex multipurpose machine learning approaches. Additionally, we discuss the advantages and disadvantages of adding intelligence to the setup to automatically assist grasping activities. The results show very good performance across all participants who share similar opinions regarding the execution of each of the proposed control modes

Neuropsychological Test Barcelona-2: Theoretical and Practical Aspects

The Barcelona test (TB) is an instrument of neuropsychological assessment, developed under the influence of Luria’s ideas, and published in 1990 [1]. It explores the main cognitive functions and allows the design of graphic profiles similar to those of the Boston Test for the diagnosis of aphasia. Objective: To present the theoretical and practical characteristics of a new version of the test, the Test Barcelona-2. The new and computerized versions of test structure is described here with six modules established: (1) Language-attention-orientation; (2) Reading and writing; (3) Motorpraxis; (4) Perception-gnosis; (5) Memory; (6) Abstraction-execution. As a novelty, test allows the selection for specific profiles: alpha, beta, abbreviated, aphasia, andecological-forensic approach. The types of variables condition a different statistical approach and a differentiated form of graphic expression. The new test presents a modular structure, which allows determining intra- and inter-module dissociations. Computerization greatly facilitates the work of the clinician. In the case of aphasia the test allows to differentiate easily all its clinical forms. Keywords: Test Barceona-2, neuropsychological test; computerized workstation, modular structur

Clasificación EEG del estrés mental inducido por un Serious Game mediante Deep Learning

Este estudio propone un sistema de electroencefalografía (EEG) para la clasificación de diferentes niveles de estrés mental utilizando un Serious Game que consiste en esquivar obstáculos controlando un coche, donde en cada nivel de dificultad se aumenta el numero de obstáculos presentes. Para ello, se ha medido el estrés tomando como referencia el nivel de dificultad jugado y se ha desarrollado un modelo de Deep Learning conformado por redes recurrentes (RNN), basado en unidades recurrentes cerradas (GRU). Los resultados muestran que el modelo es capaz de predecir los niveles de estrés con hasta una exactitud del 94 %, lo que sugiere que este sistema puede ser una técnica efectiva para predecir y clasificar el nivel de estrés mental