A Novel Technique for Selecting EMG-Contaminated EEG Channels in Self-Paced Brain-Computer Interface Task Onset

Electromyography artefacts are a well-known problem in Electroencephalography studies (BCIs, brain mapping, and clinical areas). Blind source separation (BSS) techniques are commonly used to handle artefacts. However, these may remove not only EMG artefacts but also some useful EEG sources. To reduce this useful information loss, we propose a new technique for statistically selecting EEG channels that are contaminated with class-dependent EMG (henceforth called EMG-CCh). Methods: The EMG-CCh are selected based on the correlation between EEG and facial EMG channels. They were compared (using a Wilcoxon test) to determine whether the artefacts played a significant role in class separation. To ensure that promising results are not due to weak EMG removal, reliability tests were done. Results: In our data set, the comparison results between BSS artefact removal applied in two ways, to all channels and only to EMG-CCh, showed that ICA, PCA and BSS-CCA can yield significantly better (p<0.05) class separation with the proposed method (79% of the cases for ICA, 53% for PCA and 11% for BSS-CCA). With BCI competition data, we saw improvement in 60% of the cases for ICA and BSS-CCA. Conclusion: The simple method proposed in this paper showed improvement in class separation with both our data and the BCI competition data. Significance: There are no existing methods for removing EMG artefacts based on the correlation between EEG and EMG channels. Also, the EMG-CCh selection can be used on its own or it can be combined with pre-existing artefact handling methods. For these reasons, we believe this method can be useful for other EEG studies

Comparison between covert sound-production task (sound-imagery) vs. motor-imagery for onset detection in real-life online self-paced BCIs

Background Even though the BCI field has quickly grown in the last few years, it is still mainly investigated as a research area. Increased practicality and usability are required to move BCIs to the real-world. Self-paced (SP) systems would reduce the problem but there is still the big challenge of what is known as the ‘onset detection problem’. Methods Our previous studies showed how a new sound-imagery (SI) task, high-tone covert sound production, is very effective for onset detection scenarios and we expect there are several advantages over most common asynchronous approaches used thus far, i.e., motor-imagery (MI): 1) Intuitiveness; 2) benefits to people with motor disabilities and, especially, those with lesions on cortical motor areas; and 3) no significant overlap with other common, spontaneous cognitive states, making it easier to use in daily-life situations. The approach was compared with MI tasks in online real-life scenarios, i.e., during activities such as watching videos and reading text. In our scenario, when a new message prompt from a messenger program appeared on the screen, participants watching a video (or reading text, browsing images) were asked to open the message by executing the SI or MI tasks, respectively, for each experimental condition. Results The results showed the SI task performed statistically significantly better than the MI approach: 84.04% (SI) vs 66.79 (MI) True-False positive rate for the sliding image scenario, 80.84% vs 61.07% for watching video. The classification performance difference between SI and MI was found not to be significant in the text-reading scenario. Furthermore, the onset response speed showed SI (4.08 s) being significantly faster than MI (5.46 s). In terms of basic usability, 75% of subjects found SI easier to use. Conclusions Our novel SI task outperforms typical MI for SP onset detection BCIs, therefore it would be more easily used in daily-life situations. This could be a significant step forward for the BCI field which has so far been mainly restricted to research-oriented indoor laboratory settings

Optimization of Energy Distribution in Solar Panel Array Configurations by Graph Theory and Minkowski’s Paths

Nowadays, the development of the photovoltaic (PV) technology is consolidated as a source of renewable energy. The research in the topic of maximum improvement on the energy efficiency of the PV plants is today a major challenge. The main requirement for this purpose is to know the performance of each of the PV modules that integrate the PV field in real time. In this respect, a PLC communications based Smart Monitoring and Communications Module, which is able to monitor at PV level their operating parameters, has been developed at the University of Malaga. With this device you can check if any of the panels is suffering any type of overriding performance, due to a malfunction or partial shadowing of its surface. Since these fluctuations in electricity production from a single panel affect the overall sum of all panels that conform a string, it is necessary to isolate the problem and modify the routes of energy through alternative paths in case of PV panels array configuration.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Modelling the effects of ephaptic coupling on selectivity and response patterns during artificial stimulation of peripheral nerves

Artificial electrical stimulation of peripheral nerves for sensory feedback restoration can greatly benefit from computational models for simulation-based neural implant design in order to reduce the trial-and-error approach usually taken, thus potentially significantly reducing research and development costs and time. To this end, we built a computational model of a peripheral nerve trunk in which the interstitial space between the fibers and the tissues was modelled using a resistor network, thus enabling distance-dependent ephaptic coupling between myelinated axons and between fascicles as well. We used the model to simulate a) the stimulation of a nerve trunk model with a cuff electrode, and b) the propagation of action potentials along the axons. Results were used to investigate the effect of ephaptic interactions on recruitment and selectivity stemming from artificial (i.e., neural implant) stimulation and on the relative timing between action potentials during propagation. Ephaptic coupling was found to increase the number of fibers that are activated by artificial stimulation, thus reducing the artificial currents required for axonal recruitment, and it was found to reduce and shift the range of optimal stimulation amplitudes for maximum inter-fascicular selectivity. During propagation, while fibers of similar diameters tended to lock their action potentials and reduce their conduction velocities, as expected from previous knowledge on bundles of identical axons, the presence of many other fibers of different diameters was found to make their interactions weaker and unstable

Modelo para la adopción del comercio electrónico en el sector agroindustrial mexicano

En este trabajo se propone un modelo para la adopción del comercio electrónico en las pequeñas y medianas empresas (pyme´s) del sector agroindustrial mexicano. El modelo final consta de dieciocho variables, distribuidas en siete submodelos, que son: Factores organizacionales, características técnicas, comunicación, factores ambientales, factores psicológicos y culturales, apoyo gubernamental y adopción del comercio electrónico. Para la medición de las variables se aplicó un cuestionario a las empresas de una muestra representativa. En la validación del modelo, se usó la técnica de mínimos cuadrados parciales (PLS). Se validó la consistencia interna del modelo mediante las pruebas de unidimensionalidad, fiabilidad, validez convergente y validez discriminante; así como la validación del modelo estructural

Novel Pseudo-Wavelet function for MMG signal extraction during dynamic fatiguing contractions

The purpose of this study was to develop an algorithm to classify muscle fatigue content in sports related scenarios. Mechanomyography (MMG) signals of the biceps muscle were recorded from thirteen subjects performing dynamic contractions until fatigue. For training and testing purposes, the signals were labeled in two classes (Non-Fatigue and Fatigue). A genetic algorithm was used to evolve a pseudo-wavelet function for optimizing the detection of muscle fatigue. Tuning of the generalized evolved pseudo-wavelet function was based on the decomposition of 70% of the conducted MMG trials. After completing 25 independent pseudo-wavelet evolution runs, the best run was selected and then tested on the remaining 30% of the data to measure the classification performance. Results show that the evolved pseudo-wavelet improved the classification rate of muscle fatigue by 4.70 percentage points to 16.61 percentage points when compared to other standard wavelet functions, giving an average correct classification of 80.63%, with statistical significance (p < 0.05). © 2014 by the authors; licensee MDPI, Basel, Switzerland

Phases Dynamic Balancer

Most of the current domestic installations are single phase, with contracted power equal to or less than 15 kW and with a potential difference of 230 V. When consumption is expected to be higher you choose to use three different alternating currents with a difference voltage of 400 V between them, which are called phases. This enables the subdivision of the installation in different single-phase circuits, fed independently with the neutral installation. These couples have, in turn, a difference in voltage of 230 V. The neutral is common for all three phases so that, if the system is balanced, no current flows through it. The problem with these installations is that they are designed to work in an offset manner, using phase loads, and simultaneously an equal amount of energy consumed by the three phases of the network. Connection to each of the phases makes independent single-phase loads or disturbance of the operation of the original phase circuit and, consequently, the corresponding increases in consumption, heating of engines, etc.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

P300-Based BCI Mouse With Genetically-Optimized Analogue Control

In this paper we propose a brain-computer interface (BCI) mouse based on P300 waves in electroencephalogram (EEG) signals. The system is analogue in that at no point a binary decision is made as to whether or not a P300 was actually produced in response to the stimuli. Instead, the 2-D motion of the pointer on the screen, using a novel BCI paradigm, is controlled by directly combining the amplitudes of the output produced by a filter in the presence of different stimuli. This filter and the features to be combined within it are optimised by an evolutionary algorithm. © 2006 IEEE

Planificacion del mantenimiento en Compania papelera del Pacifico S.A. apoyado por MPX Mantec.

95 p.Compañia Papelera del Pacífico S.A., es una empresa que utiliza papel reciclado en su proceso de fabricación, favoreciendo así al medio ambiente y reduciendo los costos de producción. La implementación de sistemas de información por parte de la compañía, pretendían realizar cambios en la gestión del mantenimiento, esperando obtener resultados inmediatos tras su incorporación. Pero esto se realizó con poca claridad tanto en el manejo de los sistemas y la gestión realizada. La planificación del mantenimiento apoyada en los sistemas de información tiene una gran importancia en la gestión de este, ya que se logra la coordinación de todas las actividades que involucran detenciones programadas, tanto de mantención como las de producción, incorporando entre ambas áreas una comunicación totalmente complementada. La incorporación de los sistemas de información por parte de la compañía ha permitido en la actualidad, lograr resultados totalmente positivos luego de un arduo trabajo en su base de datos. Se ha demostrado entonces que si el sistema es manejado de buena forma se logra todo lo presupuestado por la compañía tanto a corto y largo plazo, la cual tiene como objetivo realizar el cambio en su tipo de mantenimiento. En la actualidad el software utilizado por la compañía es MPX Mantec, en el cual se coordinan todas las actividades, ya sea mecánicas o de producción por parte del área de planificación para mejorar la gestión del mantenimiento. Todo sistema de información depende del entorno en que está inmerso y las áreas encargadas de cómo se realice el manejo del o los sistemas existentes, permitiendo así lograr lo propuesto por la compañía. Se propone como solución a algunos de los problemas detectados, que se implemente la utilización de módulos que existen en el software, y que presentan porcentajes bajos o casi nulos de trabajo. Esto luego de realizar un trabajo de diagnóstico de la base de datos existente de todos los equipos en el sistema y analizando el problema fundamental de este que es la escasa información existente de ellos. Con la incorporación de estos módulos se pretende mejorar la gestión de la planificación y tener un control más fino de todas las actividades que tienen directa relación con la mantención. También la incorporación de herramientas de análisis predictivo por parte de la compañía, y que son coordinadas por el departamento de planificación en la actualidad. Estas nuevas herramientas permiten adelantarse a la falla y reducir las detenciones imprevistas en los equipos críticos, favoreciendo el cambio tan esperado en el tipo de mantenimiento. Se debe tener en consideración que todo trabajo realizado en los sistemas de información por parte de cualquier empresa, requiere de una constante actualización para que este permita tener una gestión de la planificación del mantenimiento totalmente efectivo y duradero en el tiempo y crear una conciencia de trabajo en todo el personal que interactúa con el sistema