Evaluación del temblor humano a través de dispositivos de bajo coste

El temblor humano puede definirse como un movimiento rápido y, en cierta manera, rítmico de una o más partes del cuerpo. En algunas personas, este movimiento puede ser un síntoma de alguna alteración a nivel neurológico. Desde el punto de vista matemático, el temblor humano puede ser definido como una suma ponderada de diferentes señales sinusoidales que causan oscilaciones de algunas partes del cuerpo. Esta sinusoide se repite en el tiempo pero su amplitud y frecuencia cambian lentamente. Por esta razón, la amplitud y la frecuencia son consideradas factores importantes en la clasificación del temblor y por tanto útiles en su diagnóstico. En este artículo, se presenta una herramienta de ayuda al diagnóstico del temblor humano. Esta herramienta usa un dispositivo hardware de bajo coste (<$40) y permite calcular las principales componentes de esta sinusoide asociada al temblor de una manera precisa. Como casos de estudio se presentan su aplicación a dos casos reales para probar la bondad de los algoritmos desarrollados. Los casos muestran pacientes que sufrían temblores con distinta severidad y que han realizado una serie de tests con el dispositivo para que el sistema calculara las principales componentes del temblor. Estas medidas aportadas por el sistema ayudarían en un futuro a los expertos a tomar decisiones más precisas permitiéndoles centrarse en determinadas fases del test o la realización de tests más específicos para evaluar mejor las características propias del temblor del paciente. De la experimentación realizada podemos afirmar que no todos los tests son válidos para el diagnóstico para todos los pacientes. Será finalmente la experiencia del profesional el que decidirá finalmente qué test o conjunto de tests son los más apropiados para cada paciente.

Morphine-3-glucuronide's neuro-excitatory effects are mediated via indirect activation of N-methyl-D-aspartic acid receptors: Mechanistic studies in embryonic cultured hippocampal neurones

Indirect evidence indicates that morphine-3-glucuronide (M3G) may contribute significantly to the neuro-excitatory side effects (myoclonus and allodynia) of large-dose systemic morphine. To gain insight into the mechanism underlying M3G' s excitatory behaviors, We used fluo-3 fluorescence digital imaging techniques to assess the acute effects of M3G (5-500 muM) on the cytosolic calcium concentration ([Ca2+](CYT)) in cultured embryonic hippocampal neurones. Acute (3 min) exposure of neurones to M3G evoked [Ca2+](CYT) transients that were typically either (a) transient oscillatory responses characterized by a rapid increase in [Ca2+](CYT) oscillation amplitude that was sustained for at least similar to30 s or (b) a sustained increase in [Ca2+](CYT) that slowly recovered to baseline. Naloxone-pretreatment decreased the proportion of M3G-responsive neurones by 10%-25%, implicating a predominantly non-opioidergic mechanism. Although the naloxone-insensitive M3G-induced increases in [Ca2+](CYT) were completely blocked by N-methyl-D-aspartic acid (NMDA) antagonists and 6-cyano-7-nitroquinoxaline-2,3-dione (CNQX) (alphaamino-3-hydroxy-5-methyl-4-isoxazolepropiordc acid/ kainate antagonist), CNQX did not block the large increase in [Ca2+](CYT) evoked by NMDA (as expected), confirming that N13G indirectly activates the NMDA receptor. Additionally, tetrodotoxin (Na+ channel blocker), baclofen (gamma-aminobutyric acid, agonist), MVIIC (P/Q-type calcium channel blocker), and nifedipine (L-type calcium channel blocker) all abolished M3G-induced increases in [Ca2+](CYT), suggesting that M3G may produce its neuro-excitatory effects by modulating neurotransmitter release. However, additional characterization is required.

Numerical modelling of advanced modulation formats and WDM transmission

This thesis presents a theoretical investigation of the application of advanced modelling formats in high-speed fibre lightwave systems. The first part of this work focuses on numerical optimisation of dense wavelength division multiplexing (DWDM) system design. We employ advanced spectral domain filtering techniques and carrier pulse reshaping. We then apply these optimisation methods to investigate spectral and temporal domain characteristics of advanced modulation formats in fibre optic telecommunication systems. Next we investigate numerical methods used in detecting and measuring the system performance of advanced modulation formats. We then numerically study the combination of return-to-zero differential phase-shift keying (RZ-DPSK) with advanced photonic devices. Finally we analyse the dispersion management of Nx40 Gbit/s RZ-DPSK transmission applied to a commercial terrestrial lightwave system.

Manometry-Based Cough Identification Algorithm

Gastroesophageal reflux disease (GERD) is a common cause of chronic cough. For the diagnosis and treatment of GERD, it is desirable to quantify the temporal correlation between cough and reflux events. Cough episodes can be identified on esophageal manometric recordings as short-duration, rapid pressure rises. The present study aims at facilitating the detection of coughs by proposing an algorithm for the classification of cough events using manometric recordings. The algorithm detects cough episodes based on digital filtering, slope and amplitude analysis, and duration of the event. The algorithm has been tested on in vivo data acquired using a single-channel intra-esophageal manometric probe that comprises a miniature white-light interferometric fiber optic pressure sensor. Experimental results demonstrate the feasibility of using the proposed algorithm for identifying cough episodes based on real-time recordings using a single channel pressure catheter. The presented work can be integrated with commercial reflux pH/impedance probes to facilitate simultaneous 24-hour ambulatory monitoring of cough and reflux events, with the ultimate goal of quantifying the temporal correlation between the two types of events.

An efficient, approximate path-following algorithm for elastic net based nonlinear spike enhancement

Unwanted spike noise in a digital signal is a common problem in digital filtering. However, sometimes the spikes are wanted and other, superimposed, signals are unwanted, and linear, time invariant (LTI) filtering is ineffective because the spikes are wideband - overlapping with independent noise in the frequency domain. So, no LTI filter can separate them, necessitating nonlinear filtering. However, there are applications in which the noise includes drift or smooth signals for which LTI filters are ideal. We describe a nonlinear filter formulated as the solution to an elastic net regularization problem, which attenuates band-limited signals and independent noise, while enhancing superimposed spikes. Making use of known analytic solutions a novel, approximate path-following algorithm is given that provides a good, filtered output with reduced computational effort by comparison to standard convex optimization methods. Accurate performance is shown on real, noisy electrophysiological recordings of neural spikes.

Towards a Virtual-Acoustic String Instrument

In acoustic instruments, the controller and the sound producing system often are one and the same object. If virtualacoustic instruments are to be designed to not only simulate the vibrational behaviour of a real-world counterpart but also to inherit much of its interface dynamics, it would make sense that the physical form of the controller is similar to that of the emulated instrument. The specific physical model configuration discussed here reconnects a (silent) string controller with a modal synthesis string resonator across the real and virtual domains by direct routing of excitation signals and model parameters. The excitation signals are estimated in their original force-like form via careful calibration of the sensor, making use of adaptive filtering techniques to design an appropriate inverse filter. In addition, the excitation position is estimated from sensors mounted under the legs of the bridges on either end of the prototype string controller. The proposed methodology is explained and exemplified with preliminary results obtained with a number of off-line experiments.

Efficient algorithms to solve scheduling problems with a variety of optimization criteria

La programmation par contraintes est une technique puissante pour résoudre, entre autres, des problèmes d’ordonnancement de grande envergure. L’ordonnancement vise à allouer dans le temps des tâches à des ressources. Lors de son exécution, une tâche consomme une ressource à un taux constant. Généralement, on cherche à optimiser une fonction objectif telle la durée totale d’un ordonnancement. Résoudre un problème d’ordonnancement signifie trouver quand chaque tâche doit débuter et quelle ressource doit l’exécuter. La plupart des problèmes d’ordonnancement sont NP-Difficiles. Conséquemment, il n’existe aucun algorithme connu capable de les résoudre en temps polynomial. Cependant, il existe des spécialisations aux problèmes d’ordonnancement qui ne sont pas NP-Complet. Ces problèmes peuvent être résolus en temps polynomial en utilisant des algorithmes qui leur sont propres. Notre objectif est d’explorer ces algorithmes d’ordonnancement dans plusieurs contextes variés. Les techniques de filtrage ont beaucoup évolué dans les dernières années en ordonnancement basé sur les contraintes. La proéminence des algorithmes de filtrage repose sur leur habilité à réduire l’arbre de recherche en excluant les valeurs des domaines qui ne participent pas à des solutions au problème. Nous proposons des améliorations et présentons des algorithmes de filtrage plus efficaces pour résoudre des problèmes classiques d’ordonnancement. De plus, nous présentons des adaptations de techniques de filtrage pour le cas où les tâches peuvent être retardées. Nous considérons aussi différentes propriétés de problèmes industriels et résolvons plus efficacement des problèmes où le critère d’optimisation n’est pas nécessairement le moment où la dernière tâche se termine. Par exemple, nous présentons des algorithmes à temps polynomial pour le cas où la quantité de ressources fluctue dans le temps, ou quand le coût d’exécuter une tâche au temps t dépend de t.

Bitcoin mining is about to become a lot less profitable.

Imagine being told that your wage was going to be cut in half. Well, that’s what’s soon going to happen to those who make money from Bitcoin mining, the process of earning the online currency Bitcoin. The current expected date for this change is 11 July 2016. Many see this as the day when Bitcoin prices will rocket and when Bitcoin owners could make a great deal of money. Others see it as the start of a Bitcoin crash. At present no one quite knows which way it will go. Bitcoin was created in 2009 by someone known as Satoshi Nakamoto, borrowing from a whole lot of research methods. It is a cryptocurrency, meaning it uses digital encryption techniques to create bitcoins and secure financial transactions. It doesn’t need a central government or organisation to regulate it, nor a broker to manage payments. Conventional currencies usually have a central bank that creates money and controls its supply. Bitcoin is instead created when individuals “mine” for it by using their computers to perform complex calculations through special software. The algorithm behind Bitcoin is designed to limit the number of bitcoins that can ever be created. All Bitcoin transactions are recorded on a public database known as a blockchain. Every time someone mines for Bitcoin, it is recorded with a new block that is transmitted to every Bitcoin app across the network, like a bank updating its online records.

An automatic classifier of emotions built from entropy of noise

The electrocardiogram (ECG) signal has been widely used to study the physiological substrates of emotion. However, searching for better filtering techniques in order to obtain a signal with better quality and with the maximum relevant information remains an important issue for researchers in this field. Signal processing is largely performed for ECG analysis and interpretation, but this process can be susceptible to error in the delineation phase. In addition, it can lead to the loss of important information that is usually considered as noise and, consequently, discarded from the analysis. The goal of this study was to evaluate if the ECG noise allows for the classification of emotions, while using its entropy as an input in a decision tree classifier. We collected the ECG signal from 25 healthy participants while they were presented with videos eliciting negative (fear and disgust) and neutral emotions. The results indicated that the neutral condition showed a perfect identification (100%), whereas the classification of negative emotions indicated good identification performances (60% of sensitivity and 80% of specificity). These results suggest that the entropy of noise contains relevant information that can be useful to improve the analysis of the physiological correlates of emotion.

Colocated multiple-input multiple-output radars for smart mobility

In recent years, radars have been used in many applications such as precision agriculture and advanced driver assistant systems. Optimal techniques for the estimation of the number of targets and of their coordinates require solving multidimensional optimization problems entailing huge computational efforts. This has motivated the development of sub-optimal estimation techniques able to achieve good accuracy at a manageable computational cost. Another technical issue in advanced driver assistant systems is the tracking of multiple targets. Even if various filtering techniques have been developed, new efficient and robust algorithms for target tracking can be devised exploiting a probabilistic approach, based on the use of the factor graph and the sum-product algorithm. The two contributions provided by this dissertation are the investigation of the filtering and smoothing problems from a factor graph perspective and the development of efficient algorithms for two and three-dimensional radar imaging. Concerning the first contribution, a new factor graph for filtering is derived and the sum-product rule is applied to this graphical model; this allows to interpret known algorithms and to develop new filtering techniques. Then, a general method, based on graphical modelling, is proposed to derive filtering algorithms that involve a network of interconnected Bayesian filters. Finally, the proposed graphical approach is exploited to devise a new smoothing algorithm. Numerical results for dynamic systems evidence that our algorithms can achieve a better complexity-accuracy tradeoff and tracking capability than other techniques in the literature. Regarding radar imaging, various algorithms are developed for frequency modulated continuous wave radars; these algorithms rely on novel and efficient methods for the detection and estimation of multiple superimposed tones in noise. The accuracy achieved in the presence of multiple closely spaced targets is assessed on the basis of both synthetically generated data and of the measurements acquired through two commercial multiple-input multiple-output radars.

User scheduling for low earth orbit multi-user multiple-input-multiple-output non-terrestrial network systems

In rural and isolated areas without cellular coverage, Satellite Communication (SatCom) is the best candidate to complement terrestrial coverage. However, the main challenge for future generations of wireless networks will be to meet the growing demand for new services while dealing with the scarcity of frequency spectrum. As a result, it is critical to investigate more efficient methods of utilizing the limited bandwidth; and resource sharing is likely the only choice. The research community’s focus has recently shifted towards the interference management and exploitation paradigm to meet the increasing data traffic demands. In the Downlink (DL) and Feedspace (FS), LEO satellites with an on-board antenna array can offer service to numerous User Terminals (UTs) (VSAT or Handhelds) on-ground in FFR schemes by using cutting-edge digital beamforming techniques. Considering this setup, the adoption of an effective user scheduling approach is a critical aspect given the unusually high density of User terminals on the ground as compared to the on-board available satellite antennas. In this context, one possibility is that of exploiting clustering algorithms for scheduling in LEO MU-MIMO systems in which several users within the same group are simultaneously served by the satellite via Space Division Multiplexing (SDM), and then these different user groups are served in different time slots via Time Division Multiplexing (TDM). This thesis addresses this problem by defining a user scheduling problem as an optimization problem and discusses several algorithms to solve it. In particular, focusing on the FS and user service link (i.e., DL) of a single MB-LEO satellite operating below 6 GHz, the user scheduling problem in the Frequency Division Duplex (FDD) mode is addressed. The proposed State-of-the-Art scheduling approaches are based on graph theory. The proposed solution offers high performance in terms of per-user capacity, Sum-rate capacity, SINR, and Spectral Efficiency.

Proposal for underwater structural analysis using the techniques of ESPI and digital holography

The purpose of this article is to study the application of the holographic interferometry techniques in the structural analysis of submarine environment. These techniques are widely used today, with applications in many areas. Nevertheless, its application in submarine environments presents some challenges. The application of two techniques, electronic speckle pattern interferometry (ESPI) and digital holography, comparison of advantages and disadvantages of each of them is presented. A brief study is done on the influence of water properties and the optical effects due to suspended particles as well as possible solutions to minimize these problems. (C) 2009 Elsevier Ltd. All rights reserved.

Exploration of alpine orographic precipitation patterns with radar image processing and clustering techniques

A methodology of exploratory data analysis investigating the phenomenon of orographic precipitation enhancement is proposed. The precipitation observations obtained from three Swiss Doppler weather radars are analysed for the major precipitation event of August 2005 in the Alps. Image processing techniques are used to detect significant precipitation cells/pixels from radar images while filtering out spurious effects due to ground clutter. The contribution of topography to precipitation patterns is described by an extensive set of topographical descriptors computed from the digital elevation model at multiple spatial scales. Additionally, the motion vector field is derived from subsequent radar images and integrated into a set of topographic features to highlight the slopes exposed to main flows. Following the exploratory data analysis with a recent algorithm of spectral clustering, it is shown that orographic precipitation cells are generated under specific flow and topographic conditions. Repeatability of precipitation patterns in particular spatial locations is found to be linked to specific local terrain shapes, e.g. at the top of hills and on the upwind side of the mountains. This methodology and our empirical findings for the Alpine region provide a basis for building computational data-driven models of orographic enhancement and triggering of precipitation. Copyright (C) 2011 Royal Meteorological Society .

Negotiation Techniques in a Digital Library

The Andalusian eHealth Library (Biblioteca Virtual del Sistema Sanitario Público de Andalucía, BV-SSPA), created in June 2006 as a strategic action of the Andalusian Government with the aim of becoming the engine for the knowledge management of the health system in the region, has meant a radical change of mind in the way libraries can be managed: - As a regional library, it coordinates the 42 document library centers of the hospital network. - It is an organization in charge of its own budget and management. - It is the only intermediary for contracting health science resources. These factors have empowered the library in its dealings with other organizations such as stakeholders, suppliers, universities, etc. The centralization of the purchasing and the librarian network has made this library strong enough to deal with the economic recession and budgetary problems.

A Motion compensated filtering approach to remove sunlight flicker in shallow water images

A common problem in video surveys in very shallow waters is the presence of strong light fluctuations, due to sun light refraction. Refracted sunlight casts fast moving patterns, which can significantly degrade the quality of the acquired data. Motivated by the growing need to improve the quality of shallow water imagery, we propose a method to remove sunlight patterns in video sequences. The method exploits the fact that video sequences allow several observations of the same area of the sea floor, over time. It is based on computing the image difference between a given reference frame and the temporal median of a registered set of neighboring images. A key observation is that this difference will have two components with separable spectral content. One is related to the illumination field (lower spatial frequencies) and the other to the registration error (higher frequencies). The illumination field, recovered by lowpass filtering, is used to correct the reference image. In addition to removing the sunflickering patterns, an important advantage of the approach is the ability to preserve the sharpness in corrected image, even in the presence of registration inaccuracies. The effectiveness of the method is illustrated in image sets acquired under strong camera motion containing non-rigid benthic structures. The results testify the good performance and generality of the approach