Análisis cinemático y síntesis de un sistema de palancas para la sub-actuación de un dedo artificial con 3 articulaciones

Se presenta el análisis y síntesis de un conjunto de palancas mecánicas como un sistema óptimo y con capacidad de extensión, para el desarrollo de las funciones biomecánicas humanas de la apertura y cierre de un dedo artificial multi-articulado, cuyo movimiento es descrito por el principio articular de sub-actuación, disminuyendo de esta manera los grados de libertad en un dedo de tres articulaciones. Proponemos una relación funcional para un grado de libertad, mediante la incorporación comoelemento motriz de entrada a un actuador lineal. Planteamos la extensión del diseño del sistema de palancas correspondientes para la actuación de cada uno de los dedos secundarios en una mano robótica.Palabra(s) Clave(s): análisis, dedo, multi-articulado, palancas, síntesis, sub-actuación

A Novel Truncating Mutation in HOMER2 Causes Nonsyndromic Progressive DFNA68 Hearing Loss in a Spanish Family

Nonsyndromic hereditary hearing loss is a common sensory defect in humans that is clinically and genetically highly heterogeneous. So far, 122 genes have been associated with this disorder and 50 of them have been linked to autosomal dominant (DFNA) forms like DFNA68, a rare subtype of hearing impairment caused by disruption of a stereociliary scaffolding protein (HOMER2) that is essential for normal hearing in humans and mice. In this study, we report a novel HOMER2 variant (c.832_836delCCTCA) identified in a Spanish family by using a custom NGS targeted gene panel (OTO-NGS-v2). This frameshift mutation produces a premature stop codon that may lead in the absence of NMD to a shorter variant (p.Pro278Alafs*10) that truncates HOMER2 at the CDC42 binding domain (CBD) of the coiled-coil structure, a region that is essential for protein multimerization and HOMER2-CDC42 interaction. c.832_836delCCTCA mutation is placed close to the previously identified c.840_840dup mutation found in a Chinese family that truncates the protein (p.Met281Hisfs*9) at the CBD. Functional assessment of the Chinese mutant revealed decreased protein stability, reduced ability to multimerize, and altered distribution pattern in transfected cells when compared with wild-type HOMER2. Interestingly, the Spanish and Chinese frameshift mutations might exert a similar effect at the protein level, leading to truncated mutants with the same Ct aberrant protein tail, thus suggesting that they can share a common mechanism of pathogenesis. Indeed, age-matched patients in both families display quite similar hearing loss phenotypes consisting of early-onset, moderate-to-profound progressive hearing loss. In summary, we have identified the third variant in HOMER2, which is the first one identified in the Spanish population, thus contributing to expanding the mutational spectrum of this gene in other populations, and also to clarifying the genotype–phenotype correlations of DFNA68 hearing loss

Analysis of Dipolar Sources in the Solution of the Electroencephalographic Inverse Problem

In this work, we propose a solution to the problem of identification of sources in the brain from measurements of the electrical potential, recorded on the scalp EEG (electroencephalogram), where boundary problems are used to model the skull, brain region, and scalp, solving the inverse problem from the EEG measurements, the so-called Electroencephalographic Inverse Problem (EIP), which is ill-posed in the Hadamard sense since the problem has numerical instability. We focus on the identification of volumetric dipolar sources of the EEG by constructing and modeling a simplification to reduce the multilayer conductive medium (two layers or regions Ω1 and Ω2) to a problem of a single layer of a homogeneous medium with a null Neumann condition on the boundary. For this simplification purpose, we consider the Cauchy problem to be solved at each time. We compare the results we obtained solving the multiple layers problem with those obtained by our simplification proposal. In both cases, we solve the direct and inverse problems for two different sources, as synthetic results for dipolar sources resembling epileptic foci, and a similar case with an external stimulus (intense light, skin stimuli, sleep problems, etc). For the inverse problem, we use the Tikhonov regularization method to handle its numerical instability. Additionally, we build an algorithm to solve both models (multiple layers problem and our simplification) in time, showing optimization of the problem when considering 128 divisions in the time interval [0,1] s, solving the inverse problem at each time (interval division) and comparing the recovered source with the initial one in the algorithm. We observed a significant decrease in the computation times when simplifying the numerical calculations, resulting in a decrease up to 50% in the execution times, between the EIP multilayer model and our simplification proposal, to a single layer homogeneous problem of a homogeneous medium, which translates into a numerical efficiency in this type of problem

Identificación de los parámetros de una fuente dipolar, usando mínimos cuadrados

Los problemas de identificación también conocidos como problemas inversos, se presentan en diferentes campos de la investigación y consisten en determinar el origen de cierto fenómeno a partir de las causas que este produce. En particular en la medicina es de gran interés determinar el daño cerebral en el interior del cerebro, a partir de mediciones del potencial sobre el cuero cabelludo. Esta medición es conocida como Electroencefalograma. En este trabajo, se utiliza un modelo de medio conductor para establecer correlaciones entre la fuente interior y el potencial medido a través del electroencefalograma. A partir de esta relación, se plantean los problemas directo e inverso electroencefalográfico. El problema inverso presenta generalmente inestabilidad en el sentido de que dadas dos mediciones cercanas pueden identificar fuentes muy alejadas. Además se propone una expresión matemática para encontrar el potencial producido por una fuente dipolar. En la parte experimental se construyó un sistema físico, el cual consiste en colocar un dipolo eléctrico dentro de una esfera conductora, con lo cual se representa a la fuente dipolar dentro de la cabeza. Esta permitirá tener los potenciales experimentales que se usarán para la recuperación de la fuente

Simulated LCSLM with Inducible Diffractive Theory to Display Super-Gaussian Arrays Applying the Transport-of-Intensity Equation

We simulate a liquid crystal spatial light modulator (LCSLM), previously validated by Fraunhofer diffraction to observe super-Gaussian periodic profiles and analyze the wavefront of optical surfaces applying the transport-of-intensity equation (TIE). The LCSLM represents an alternative to the Ronchi Rulings, allowing to avoid all the related issues regarding diffractive and refractive properties, and noise. To this aim, we developed and numerically simulated a LCSLM resembling a fractal from a generating base. Such a base is constituted by an active square (values equal to one) and surrounded by eight switched-off pixels (zero-valued). We replicate the base in order to form 1 ×N-pixels and the successive rows to build the 1024×1024 LCSLM of active pixels. We visually test the LCSLM with calibration images as a diffractive object that is mathematically inducible, using mathematical induction over the N×N-shape (1×1, 2×2, 3×3, …, n×n pixels for the generalization). Finally, we experimentally generate periodic super-Gaussian profiles to be visualized in the LCSLM (transmission SLM, 1024×768-pixels LC 2012 Translucent SLM), modifying the TIE as an optical test in order to analyze the optical elements by comparing the results with ZYGO/APEX

Stable Numerical Identification of Sources in Non-Homogeneous Media

In this work, we present a numerical algorithm to solve the inverse problem of volumetric sources from measurements on the boundary of a non-homogeneous conductive medium, which is made of conductive layers with constant conductivity in each layer. This inverse problem is ill-posed since there is more than one source that can generate the same measurement. Furthermore, the ill-posedness is due to the fact that small variations (or errors) in the measurement (input data) can produce substantial variations in the identified source location. We propose two steps to solve this inverse problem in some classes of sources: we first recover the harmonic part of the volumetric source, and, in a second step, we compute the non-harmonic part of the source. For the reconstruction of the harmonic part of the source, we follow a variational approach based on the reformulation of the inverse problem as a distributed control problem, for which the cost function incorporates a penalized term with the input data on the boundary. This cost function is minimized by a conjugate gradient algorithm in combination with a finite element discretization. We recover the non-harmonic component of the source using a priori information and an iterative algorithm for some particular classes of sources. To validate the numerical methodology, we develop synthetic examples both in circular (simple) and irregular (complex) regions. The numerical results show that the proposed methodology allows to recover the complete source and produce stable and accurate numerical solutions

FPGA-Based Hardware Implementation of a Stable Inverse Source Problem Algorithm in a Non-Homogeneous Circular Region

Objective: This work presents an implementation of a stable algorithm that recovers sources located at the boundary separating two homogeneous media in field-programmable gate arrays. Two loop unrolling architectures were developed and analyzed for this purpose. This inverse source problem is ill-posed due to numerical instability, i.e., small errors in the measurement can produce significant changes in the source location. Methodology: To handle the numerical instability when recovering these sources, the Tikhonov regularization method in combination with the Fourier series truncation method are applied in the stable algorithm. This stable algorithm is implemented in two different architectures developed in this work: The first architecture (Mode 1) allows for different operating speeds, which is an advantage depending on whether we work with fast or slow signals. The second one (Mode 2) reduces resource consumption by exploiting the characteristics of the source identification algorithm, which is an advantage for multichannel problems such as inverse electrocardiography or electroencephalography. Results: The architectures were tested on four devices of the 7 Series of Xilinx: Spartan-7 xc7s100fgga484, Virtex-7 xc7v585tffg1157, Kintex-7 xc7k70tfbg484, and Artix-7 xc7a35tcpg236. The two hardware implementations of the stable algorithm were validated using synthetic examples implemented in MATLAB, which shows the advantages of each architecture. Contributions: We developed two efficient architectures based on a loop unrolling design for source identification problems. These are effective strategies to divide and assign tasks to the configurable hardware, and they appear as an appropriate technique for implementing the algorithm. The first one is simple and allows for different operating speeds. The second one uses a control system based on multiplexors that reduce resource consumption and complexity of the design and can be used for multichannel problems. From the numerical test, we found the regularization parameters. The synthetic examples developed here can be considered for similar problems and can be extended to concentric spheres

Stable Identification of Sources Located on Interface of Nonhomogeneous Media

This paper presents a stable method for the identification of sources located on the separation interface of two homogeneous media (where one of them is contained by the other one), from measurement yielded by those sources on the exterior boundary of the media. This is an ill-posed problem because numerical instability is presented, i.e., minimal errors in the measurement can result in significant changes in the solution. To obtain the proposed stable method the identification problem is categorized into three subproblems, two of which present numerical instability and regularization methods must be applied to obtain their solution in a stable form. To manage the numerical instability due to the ill-posedness of these subproblems, the Tikhonov regularization and sequential smoothing methods are used. We illustrate this methodology in a circular and irregular region to demonstrate the feasibility of the proposed method, which yields convergent and stable solutions for input data with and without noise