70 resultados para Embs, WIllaim


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Considering the difficulty in the insulin dosage selection and the problem of hyper- and hypoglycaemia episodes in type 1 diabetes, dosage-aid systems appear as tremendously helpful for these patients. A model-based approach to this problem must unavoidably consider uncertainty sources such as the large intra-patient variability and food intake. This work addresses the prediction of glycaemia for a given insulin therapy face to parametric and input uncertainty, by means of modal interval analysis. As result, a band containing all possible glucose excursions suffered by the patient for the given uncertainty is obtained. From it, a safer prediction of possible hyper- and hypoglycaemia episodes can be calculated

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This paper examines the influence of a collaborative rehabilitation environment that encourages a long-distance collaborative "play" using two robot-mediated environments. This study presents a strategy for increasing motivation on able-bodied persons, applicable to impaired persons, to engage, sustain play and relate during a shared task. The study consisted of a series of eighteen single case studies, each involved in two distinct phases and assessed using a multidimensional measurement intended to assess participant' subjective experience. The results showed a clear positive trend in favour of the robot-mediated game environment. Subjects found the collaborative environment more valuable and more interesting and enjoyable. As a consequence, it appears subjects were willing to spend more time at a task.

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Theoretical models suggest that decisions about diet, weight and health status are endogenous within a utility maximization framework. In this article, we model these behavioural relationships in a fixed-effect panel setting using a simultaneous equation system, with a view to determining whether economic variables can explain the trends in calorie consumption, obesity and health in Organization for Economic Cooperation and Development (OECD) countries and the large differences among the countries. The empirical model shows that progress in medical treatment and health expenditure mitigates mortality from diet-related diseases, despite rising obesity rates. While the model accounts for endogeneity and serial correlation, results are affected by data limitations.

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This paper introduces the Hilbert Analysis (HA), which is a novel digital signal processing technique, for the investigation of tremor. The HA is formed by two complementary tools, i.e. the Empirical Mode Decomposition (EMD) and the Hilbert Spectrum (HS). In this work we show that the EMD can automatically detect and isolate tremulous and voluntary movements from experimental signals collected from 31 patients with different conditions. Our results also suggest that the tremor may be described by a new class of mathematical functions defined in the HA framework. In a further study, the HS was employed for visualization of the energy activities of signals. This tool introduces the concept of instantaneous frequency in the field of tremor. In addition, it could provide, in a time-frequency energy plot, a clear visualization of local activities of tremor energy over the time. The HA demonstrated to be very useful to perform objective measurements of any kind of tremor and can therefore be used to perform functional assessment.

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Anesthetic and analgesic agents act through a diverse range of pharmacological mechanisms. Existing empirical data clearly shows that such "microscopic" pharmacological diversity is reflected in their "macroscopic" effects on the human electroencephalogram (EEG). Based on a detailed mesoscopic neural field model we theoretically posit that anesthetic induced EEG activity is due to selective parametric changes in synaptic efficacy and dynamics. Specifically, on the basis of physiologically constrained modeling, it is speculated that the selective modification of inhibitory or excitatory synaptic activity may differentially effect the EEG spectrum. Such results emphasize the importance of neural field theories of brain electrical activity for elucidating the principles whereby pharmacological agents effect the EEG. Such insights will contribute to improved methods for monitoring depth of anesthesia using the EEG.

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By placing axons into polymeric micro-channels hosting embedded electrodes the extracellular amplitude of action potentials is greatly increased, allowing for robust recording and noise suppression. We are developing such an electrode interface to record electrical activity from bladder afferents to restore bladder control in patients suffering from spinal cord injury. Here we describe our microchannel electrode interface in terms of design, microfabrication and electrode characteristics and report on in vivo bladder function after implantation of teased dorsal rootlets within microchannels.

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This communication examines the suitability of a photo-patternable polydimethylsiloxane (PP-PDMS) elastomer as an insulating material for implantable microelectrodes. PP-PDMS is produced by mixing a photoinitiator (2-hydroxy-2-methylpropiophenone) with the PDMS base and curing agent. Subsequent exposure to UV radiation and development of the elastomeric “photo-resist” allows for the definition of well-defined openings within the PP-PDMS film. The dielectric constants of PP-PDMS and PDMS are similar (ε ≈ 2.6, f <;1MHz). Gold film microelectrodes patterned on glass or a PDMS substrate are encapsulated with PP-PDMS, while recording sites as small as 104 μm2 can be obtained in the PP-PDMS layer. The cytotoxicity of the PP-PDMS was preliminary tested in vitro by culturing 3T3 fibroblasts in PP-PDMS extracts. No adverse effects were observed in cultures exposed to PP-PDMS films initially leached in isopropanol solvent for 48h.

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We are reporting on the fabrication and electrical characterization of a novel elastomer based micro-cuff neural interface. Electrodes are gold (Au) tracks of sub-100nm thickness and are thermally evaporated on a 0.5 mm thick polydimethylsiloxane (PDMS) substrate. We investigate how electrode area and immersion in phosphate buffered saline (PBS) at 37°C influence electrode impedance. A microfluidic channel is bonded to the electrode array to form the cuff. In an acute, in-vivo, proof-of-principle recording, the device is capable of detecting light stroking and pinch of a hind leg of an anaesthetized rat.

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Virtual Reality (VR) can provide visual stimuli for EEG studies that can be altered in real time and can produce effects that are difficult or impossible to reproduce in a non-virtual experimental platform. As part of this experiment the Oculus Rift, a commercial-grade, low-cost, Head Mounted Display (HMD) was assessed as a visual stimuli platform for experiments recording EEG. Following, the device was used to investigate the effect of congruent visual stimuli on Event Related Desynchronisation (ERD) due to motion imagery.

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Exercise based rehabilitation plays a vital role in the recovery of various conditions, such as stroke, Parkinson’s disease (PD), chronic pain, and so on. Recently, telerehabilitation has become increasingly popular quantitative nature in assessments particularly for systematic monitoring of progress as well as cost saving for the patients as well as for the health care sector at large. However, challenges do exist in implementing a distributed bio-feedback in a cost-effective and efficient way. In this paper, we present the associated conceptual framework of cloud-based tele-rehabilitation system employing affordable non-invasive Microsoft Kinect® allowing patients to perform rehabilitation exercises in non-clinical setting such as home environments without loosing the quality of patients care. More importantly, different from existing tele-rehabilitation systems, our system not only measures whether patients can perform rehabilitation tasks, but also how well they can finish the tasks. Preliminary experiments validate its potential in training healthy subject to perform exercise motions emulating the physical rehabilitation process.

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The spermatogenesis is crucial to the species reproduction, and its monitoring may shed light over some important information of such process. Thus, the germ cells quantification can provide useful tools to improve the reproduction cycle. In this paper, we present the first work that address this problem in fishes with machine learning techniques. We show here how to obtain high recognition accuracies in order to identify fish germ cells with several state-of-the-art supervised pattern recognition techniques. © 2011 IEEE.

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Parkinson's disease (PD) automatic identification has been actively pursued over several works in the literature. In this paper, we deal with this problem by applying evolutionary-based techniques in order to find the subset of features that maximize the accuracy of the Optimum-Path Forest (OPF) classifier. The reason for the choice of this classifier relies on its fast training phase, given that each possible solution to be optimized is guided by the OPF accuracy. We also show results that improved other ones recently obtained in the context of PD automatic identification. © 2011 IEEE.

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The anticancer drug paclitaxel was encapsulated into a bio-nanocomposite formed by magnetic nanoparticles, chitosan and apatite. The aim of this drug carrier is to provide a new perspective against breast cancer. The dynamics of the pure and encapsulated drug were investigated in order to verify possible molecular changes caused by the encapsulation, as well as to follow which interactions may occur between paclitaxel and the composite. Fourier transformed infrared spectroscopy, thermal analysis, inelastic and quasi-elastic neutron scattering experiments were performed. These very preliminary results suggest the successful encapsulation of the drug.