Tratamiento endovascular de aneurismas de arterias viscerales. Experiencia de 10 años en un solo centro / Endovascular treatment of visceral artery aneurysms. A single center 10-year experience

RESUMEN Antecedentes : los aneurismas de arterias viscerales (AAV) tienen una frecuencia baja (0,1 a 2%). Hasta un 25% puede presentarse como rotura, con una alta mortalidad (hasta 70%). La terapia endovascular ha ganado terreno y se recomienda como primera opción según las últimas guías. Hoy en día, es posible adaptarse a casi cualquier anatomía utilizando tecnología cerebral. Objetivo : describir la experiencia y enfoque en el manejo endovascular de AAV, con resultados a corto, mediano y largo plazo. Material y métodos : llevamos a cabo una evaluación retrospectiva de pacientes tratados por AAV verdaderos por vía endovascular en un solo centro entre 2010 y 2020, con un seguimiento mínimo de 6 meses. Resultados : analizamos 19 procedimientos en 18 pacientes (9 hombres y 9 mujeres). La edad promedio fue 61,9 años; el promedio de tiempo de internación fue 1,94 días y el promedio de seguimiento de 40 meses. La arteria más involucrada fue la esplénica (n = 9, 50%). El tamaño aneurismático promedio fue 30,1 mm. La estrategia terapéutica más utilizada fue colocación de diversor de flujo (n = 8, 42,1%). Dos pacientes fueron reintervenidos (11,1%). Las tasas de exclusión completa fueron del 47,4%, 68,4% y 94,7% a los 3, 6 y 12 meses, respectivamente. No hubo casos de mortalidad a 30 días ni mortalidad relacionada con el aneurisma durante el seguimiento. Conclusión : el tratamiento endovascular de los AAV es seguro y eficaz. Sin embargo, se debe contar con la tecnología adecuada, para la planificación preoperatoria y el tratamiento.

ABSTRACT Background : the prevalence of visceral artery aneurysms (VAAs) is low (0.1 to 2%). Up to 25% may present as rupture which is associated with high mortality (up to 70%). Endovascular treatment has gained ground and is even considered the first option according to the most recent recommendations. Nowadays, almost any anatomy can be approached with endovascular techniques used to treat intracranial aneurysms. Objective : the aim of our study was to describe the experience and approach for the endovascular management of VAAs with short-, mid-, and long-term results. Material and methods : we conducted a retrospective evaluation of patients with true VAAs undergoing endovascular treatment in a single center between 2010 and 2020 who were followed up for a minimum of 6 months. Results : we analyzed 19 procedures in 18 patients (9 men and 9 women). Mean age was 61.9 years; mean length of hospital stay was 1.94 days and mean follow-up was 40 months. The splenic artery was the vessel most affected (n = 9, 50%). Mean aneurysm size was 30.1 mm. Flow diversion was the strategy most used (n = 8, 42.1%). Two patients required reintervention (11%). Complete exclusion rate was 38.4%, 47.4%, 68.4% and 94.7% at 3, 6 and 12 months, respectively. There were no cases of mortality within the first 30 days and no aneurysm-related mortality during the follow-up period. Conclusion : endovascular treatment of VAAs is a safe and efficient strategy but requires adequate technology for preoperative planning and treatment.

Validation of GWAS-Identified Variants for Anti-TNF Drug Response in Rheumatoid Arthritis: A Meta-Analysis of Two Large Cohorts.

We aimed to validate the association of 28 GWAS-identified genetic variants for response to TNF inhibitors (TNFi) in a discovery cohort of 1361 rheumatoid arthritis (RA) patients monitored in routine care and ascertained through the REPAIR consortium and DANBIO registry. We genotyped selected markers and evaluated their association with response to TNFi after 6 months of treatment according to the change in disease activity score 28 (ΔDAS28). Next, we confirmed the most interesting results through meta-analysis of our data with those from the DREAM cohort that included 706 RA patients treated with TNFi. The meta-analysis of the discovery cohort and DREAM registry including 2067 RA patients revealed an overall association of the LINC02549rs7767069 SNP with a lower improvement in DAS28 that remained significant after correction for multiple testing (per-allele ORMeta=0.83, PMeta=0.000077; PHet=0.61). In addition, we found that each copy of the LRRC55rs717117G allele was significantly associated with lower improvement in DAS28 in rheumatoid factor (RF)-positive patients (per-allele ORMeta=0.67, P=0.00058; PHet=0.06) whereas an opposite but not significant effect was detected in RF-negative subjects (per-allele ORMeta=1.38, P=0.10; PHet=0.45; PInteraction=0.00028). Interestingly, although the identified associations did not survive multiple testing correction, the meta-analysis also showed overall and RF-specific associations for the MAFBrs6071980 and CNTN5rs1813443 SNPs with decreased changes in DAS28 (per-allele ORMeta_rs6071980 = 0.85, P=0.0059; PHet=0.63 and ORMeta_rs1813443_RF+=0.81, P=0.0059; PHet=0.69 and ORMeta_rs1813443_RF-=1.00, P=0.99; PHet=0.12; PInteraction=0.032). Mechanistically, we found that subjects carrying the LINC02549rs7767069T allele had significantly increased numbers of CD45RO+CD45RA+ T cells (P=0.000025) whereas carriers of the LINC02549rs7767069T/T genotype showed significantly increased levels of soluble scavengers CD5 and CD6 in serum (P=0.00037 and P=0.00041). In addition, carriers of the LRRC55rs717117G allele showed decreased production of IL6 after stimulation of PBMCs with B burgdorferi and E coli bacteria (P=0.00046 and P=0.00044), which suggested a reduced IL6-mediated anti-inflammatory effect of this marker to worsen the response to TNFi. In conclusion, this study confirmed the influence of the LINC02549 and LRRC55 loci to determine the response to TNFi in RA patients and suggested a weak effect of the MAFB and CNTN5 loci that need to be further investigated.

NFKB2 polymorphisms associate with the risk of developing rheumatoid arthritis and response to TNF inhibitors: Results from the REPAIR consortium.

This study sought to evaluate the association of 28 single nucleotide polymorphisms (SNPs) within NFKB and inflammasome pathway genes with the risk of rheumatoid arthritis (RA) and response to TNF inhibitors (TNFi). We conducted a case-control study in a European population of 1194 RA patients and 1328 healthy controls. The association of potentially interesting markers was validated with data from the DANBIO (695 RA patients and 978 healthy controls) and DREAM (882 RA patients) registries. The meta-analysis of our data with those from the DANBIO registry confirmed that anti-citrullinated protein antibodies (ACPA)-positive subjects carrying the NFKB2rs11574851T allele had a significantly increased risk of developing RA (PMeta_ACPA + = 0.0006) whereas no significant effect was found in ACPA-negative individuals (PMeta_ACPA- = 0.35). An ACPA-stratified haplotype analysis including both cohorts (n = 4210) confirmed that ACPA-positive subjects carrying the NFKB2TT haplotype had an increased risk of RA (OR = 1.39, P = 0.0042) whereas no effect was found in ACPA-negative subjects (OR = 1.04, P = 0.82). The meta-analysis of our data with those from the DANBIO and DREAM registries also revealed a suggestive association of the NFKB2rs1056890 SNP with larger changes in DAS28 (OR = 1.18, P = 0.007). Functional experiments showed that peripheral blood mononuclear cells from carriers of the NFKB2rs1005044C allele (in LD with the rs1056890, r2 = 1.00) showed increased production of IL10 after stimulation with LPS (P = 0.0026). These results provide first evidence of a role of the NFKB2 locus in modulating the risk of RA in an ACPA-dependent manner and suggest its implication in determining the response to TNFi. Additional studies are now warranted to further validate these findings.

iDeLog: Iterative Dual Spatial and Kinematic Extraction of Sigma-Lognormal Parameters.

The Kinematic Theory of rapid movements and its associated Sigma-Lognormal model have been extensively used in a large variety of applications. While the physical and biological meaning of the model have been widely tested and validated for rapid movements, some shortcomings have been detected when it is used with continuous long and complex movements. To alleviate such drawbacks, and inspired by the motor equivalence theory and a conceivable visual feedback, this paper proposes a novel framework to extract the Sigma-Lognormal parameters, namely iDeLog. Specifically, iDeLog consists of two steps. The first one, influenced by the motor equivalence model, separately derives an initial action plan defined by a set of virtual points and angles from the trajectory and a sequence of lognormals from the velocity. In the second step, based on a hypothetical visual feedback compatible with an open-loop motor control, the virtual target points of the action plan are iteratively moved to improve the matching between the observed and reconstructed trajectory and velocity. During experiments conducted with handwritten signatures, iDeLog obtained promising results as compared to the previous development of the Sigma-Lognormal.

Correction: Polymorphisms at phase I-metabolizing enzyme and hormone receptor loci influence the response to anti-TNF therapy in rheumatoid arthritis patients.

The original version of this Article contained an error in the spelling of the author Ana Rodríguez-Ramos, which was incorrectly given as Ana Rodríguez Ramos. This has now been corrected in both the PDF and HTML versions of the Article.

Polymorphisms at phase I-metabolizing enzyme and hormone receptor loci influence the response to anti-TNF therapy in rheumatoid arthritis patients.

The aim of this case-control study was to evaluate whether 47 single-nucleotide polymorphisms (SNPs) in steroid hormone-related genes are associated with the risk of RA and anti-TNF drug response. We conducted a case-control study in 3 European populations including 2936 RA patients and 2197 healthy controls. Of those, a total of 1985 RA patients were treated with anti-TNF blockers. The association of potentially interesting markers in the discovery population was validated through meta-analysis with data from DREAM and DANBIO registries. Although none of the selected variants had a relevant role in modulating RA risk, the meta-analysis of the linear regression data with those from the DREAM and DANBIO registries showed a significant correlation of the CYP3A4rs11773597 and CYP2C9rs1799853 variants with changes in DAS28 after the administration of anti-TNF drugs (P = 0.00074 and P = 0.006, respectively). An overall haplotype analysis also showed that the ESR2GGG haplotype significantly associated with a reduced chance of having poor response to anti-TNF drugs (P = 0.0009). Finally, a ROC curve analysis confirmed that a model built with eight steroid hormone-related variants significantly improved the ability to predict drug response compared with the reference model including demographic and clinical variables (AUC = 0.633 vs. AUC = 0.556; PLR_test = 1.52 × 10-6). These data together with those reporting that the CYP3A4 and ESR2 SNPs correlate with the expression of TRIM4 and ESR2 mRNAs in PBMCs (ranging from P = 1.98 × 10-6 to P = 2.0 × 10-35), and that the CYP2C9rs1799853 SNP modulates the efficiency of multiple drugs, suggest that steroid hormone-related genes may have a role in determining the response to anti-TNF drugs.KEY POINTS• Polymorphisms within the CYP3A4 and CYP2C9 loci correlate with changes in DAS28 after treatment with anti-TNF drugs.• A haplotype including eQTL SNPs within the ESR2 gene associates with better response to anti-TNF drugs.• A genetic model built with eight steroid hormone-related variants significantly improved the ability to predict drug response.

Anthropomorphic Features for On-Line Signatures.

Many features have been proposed in on-line signature verification. Generally, these features rely on the position of the on-line signature samples and their dynamic properties, as recorded by a tablet. This paper proposes a novel feature space to describe efficiently on-line signatures. Since producing a signature requires a skeletal arm system and its associated muscles, the new feature space is based on characterizing the movement of the shoulder, the elbow and the wrist joints when signing. As this motion is not directly obtained from a digital tablet, the new features are calculated by means of a virtual skeletal arm (VSA) model, which simulates the architecture of a real arm and forearm. Specifically, the VSA motion is described by its 3D joint position and its joint angles. These anthropomorphic features are worked out from both pen position and orientation through the VSA forward and direct kinematic model. The anthropomorphic features' robustness is proved by achieving state-of-the-art performance with several verifiers and multiple benchmarks on third party signature databases, which were collected with different devices and in different languages and scripts.

Static and Dynamic Synthesis of Bengali and Devanagari Signatures.

Developing an automatic signature verification system is challenging and demands a large number of training samples. This is why synthetic handwriting generation is an emerging topic in document image analysis. Some handwriting synthesizers use the motor equivalence model, the well-established hypothesis from neuroscience, which analyses how a human being accomplishes movement. Specifically, a motor equivalence model divides human actions into two steps: 1) the effector independent step at cognitive level and 2) the effector dependent step at motor level. In fact, recent work reports the successful application to Western scripts of a handwriting synthesizer, based on this theory. This paper aims to adapt this scheme for the generation of synthetic signatures in two Indic scripts, Bengali (Bangla), and Devanagari (Hindi). For this purpose, we use two different online and offline databases for both Bengali and Devanagari signatures. This paper reports an effective synthesizer for static and dynamic signatures written in Devanagari or Bengali scripts. We obtain promising results with artificially generated signatures in terms of appearance and performance when we compare the results with those for real signatures.

Dynamic Signature Verification System Based on One Real Signature.

The dynamic signature is a biometric trait widely used and accepted for verifying a person's identity. Current automatic signature-based biometric systems typically require five, ten, or even more specimens of a person's signature to learn intrapersonal variability sufficient to provide an accurate verification of the individual's identity. To mitigate this drawback, this paper proposes a procedure for training with only a single reference signature. Our strategy consists of duplicating the given signature a number of times and training an automatic signature verifier with each of the resulting signatures. The duplication scheme is based on a sigma lognormal decomposition of the reference signature. Two methods are presented to create human-like duplicated signatures: the first varies the strokes' lognormal parameters (stroke-wise) whereas the second modifies their virtual target points (target-wise). A challenging benchmark, assessed with multiple state-of-the-art automatic signature verifiers and multiple databases, proves the robustness of the system. Experimental results suggest that our system, with a single reference signature, is capable of achieving a similar performance to standard verifiers trained with up to five signature specimens.

Myoelectronic signal-based methodology for the analysis of handwritten signatures.

With the overall aim of improving the synthesis of handwritten signatures, we have studied how muscle activation depends on handwriting style for both text and flourish. Surface electromyographic (EMG) signals from a set of twelve arm and trunk muscles were recorded in synchronization with handwriting produced on a digital Tablet. Correlations between these EMG signals and handwritten trajectory signals were analyzed so as to define the sequence of muscles activated during the different parts of the signature. Our results establish a correlation between the speed of the movement, stroke size, handwriting style and muscle activation. Muscle activity appeared to be clustered as a function of movement speed and handwriting style, a finding which may be used for filter design in a signature synthesizer.

Generation of Duplicated Off-Line Signature Images for Verification Systems.

Biometric researchers have historically seen signature duplication as a procedure relevant to improving the performance of automatic signature verifiers. Different approaches have been proposed to duplicate dynamic signatures based on the heuristic affine transformation, nonlinear distortion and the kinematic model of the motor system. The literature on static signature duplication is limited and as far as we know based on heuristic affine transforms and does not seem to consider the recent advances in human behavior modeling of neuroscience. This paper tries to fill this gap by proposing a cognitive inspired algorithm to duplicate off-line signatures. The algorithm is based on a set of nonlinear and linear transformations which simulate the human spatial cognitive map and motor system intra-personal variability during the signing process. The duplicator is evaluated by increasing artificially a training sequence and verifying that the performance of four state-of-the-art off-line signature classifiers using two publicly databases have been improved on average as if we had collected three more real signatures.

A Behavioral Handwriting Model for Static and Dynamic Signature Synthesis.

The synthetic generation of static handwritten signatures based on motor equivalence theory has been recently proposed for biometric applications. Motor equivalence divides the human handwriting action into an effector dependent cognitive level and an effector independent motor level. The first level has been suggested by others as an engram, generated through a spatial grid, and the second has been emulated with kinematic filters. Our paper proposes a development of this methodology in which we generate dynamic information and provide a unified comprehensive synthesizer for both static and dynamic signature synthesis. The dynamics are calculated by lognormal sampling of the 8-connected continuous signature trajectory, which includes, as a novelty, the pen-ups. The forgery generation imitates a signature by extracting the most perceptually relevant points of the given genuine signature and interpolating them. The capacity to synthesize both static and dynamic signatures using a unique model is evaluated according to its ability to adapt to the static and dynamic signature inter- and intra-personal variability. Our highly promising results suggest the possibility of using the synthesizer in different areas beyond the generation of unlimited databases for biometric training.

Static Signature Synthesis: A Neuromotor Inspired Approach for Biometrics.

In this paper we propose a new method for generating synthetic handwritten signature images for biometric applications. The procedures we introduce imitate the mechanism of motor equivalence which divides human handwriting into two steps: the working out of an effector independent action plan and its execution via the corresponding neuromuscular path. The action plan is represented as a trajectory on a spatial grid. This contains both the signature text and its flourish, if there is one. The neuromuscular path is simulated by applying a kinematic Kaiser filter to the trajectory plan. The length of the filter depends on the pen speed which is generated using a scalar version of the sigma lognormal model. An ink deposition model, applied pixel by pixel to the pen trajectory, provides realistic static signature images. The lexical and morphological properties of the synthesized signatures as well as the range of the synthesis parameters have been estimated from real databases of real signatures such as the MCYT Off-line and the GPDS960GraySignature corpuses. The performance experiments show that by tuning only four parameters it is possible to generate synthetic identities with different stability and forgers with different skills. Therefore it is possible to create datasets of synthetic signatures with a performance similar to databases of real signatures. Moreover, we can customize the created dataset to produce skilled forgeries or simple forgeries which are easier to detect, depending on what the researcher needs. Perceptual evaluation gives an average confusion of 44.06 percent between real and synthetic signatures which shows the realism of the synthetic ones. The utility of the synthesized signatures is demonstrated by studying the influence of the pen type and number of users on an automatic signature verifier.

Genetic variants within immune-modulating genes influence the risk of developing rheumatoid arthritis and anti-TNF drug response: a two-stage case-control study.

BACKGROUND: Rheumatoid arthritis (RA) is a chronic autoimmune disease that arises as a result of the interaction between genetic and environmental factors. A growing body of research suggests that genetic variants within immune-related genes can influence the risk of developing the disease and affect drug response. MATERIALS AND METHODS: To test this hypothesis, we carried out a comprehensive two-stage case-control study in a White population of 1239 White RA patients and 1229 healthy controls to investigate whether 49 single nucleotide polymorphisms within or near 17 immune-related genes modulate the risk of developing RA and antitumor necrosis factor (anti-TNF) drug response. RESULTS: Logistic regression analyses showed that carriers of the IL4rs2070874T and IL4rs2243250T and IL8RBrs1126580A alleles or the IL8RBrs2230054C/C genotype had a significantly increased risk of developing RA [odds ratio (OR)=1.37, 95% confidence interval (CI) 1.13-1.67, P=0.0016; OR=1.24, 95% CI 1.03-1.49, P=0.020; OR=1.23, 95% CI 1.08-1.41, P=0.002 and OR=1.19, 95% CI 1.04-1.36, P=0.01, respectively]. The association of the IL4 variants was further supported by a meta-analysis including 7150 individuals (P =0.0010), whereas the involvement of the IL8RB locus in determining the susceptibility to RA was also supported by gene-gene interaction analyses that identified significant two-locus and three-locus interaction models including IL8RB variants that act synergistically to increase the risk of the disease (P=0.014 and 0.018). Interestingly, we also found that patients harbouring the IFNGrs2069705C allele showed a significantly better response to anti-TNF drugs than those patients carrying the wild-type allele (P=0.0075). CONCLUSIONS: Our data suggest that IL4 and IL8RB loci may have a small-effect genetic impact on the risk of developing RA, whereas IFNG might be involved in modulating the response to anti-TNF drugs.

Herramienta para la evaluación acústica de la voz en entornos hospitalarios: EVALUA / A tool for the acoustic assessment of the voice in clinical environments: EVALUA

En el ámbito de la evaluación acústica del sistema fonador, las diferentes herramientas conocidas no están exentas de la necesidad de interpretar sus resultados y de un conocimiento amplio de las características de la señal de voz en los diferentes dominios de representación. En este trabajo se presenta una simple y robusta herramienta de software que tiene como objetivo documentar la calidad de voz a partir de una grabación de una vocal sostenida, cuantificando objetivamente y de forma automática 4 fenómenos físicos que permiten realizar una medición de la calidad de la voz. Estos 4 fenómenos físicos se han denominado: estabilidad de la voz, riqueza espectral, presencia de ruido e irregularidades en las masas. Se ha desarrollado un software que de manera automática identifica las variaciones de la normalidad de los 4 fenómenos físicos y, por tanto, permite diferenciar de forma objetiva las voces normales de las patológicas. Para el análisis de las prestaciones del sistema que se presenta se han evaluado 86 locutores de control y 155 locutores con patologías laríngeas variadas con diferentes grados de disfonía. En el estudio realizado se ha obtenido una sensibilidad del 89% y una especificidad de 89,5% en la discriminación entre voces normales y patológicas. Con el estudio clínico realizado hemos demostrado que la herramienta es clínicamente relevante en la evaluación y documentación de pacientes con trastornos de la voz (AU)

In the field of acoustic evaluation of the phonatory system, the distinct available tools are not exempt from the need to interpret their results and for extensive knowledge of the characteristics of the speech signal in the different domains of representation. This article presents a simple and robust software tool that aims to document voice quality from a recording of a sustained vowel. This tool measures four physical phenomena that define voice quality objectively and automatically. These four physical phenomena are referred to as: voice stability, spectral richness, the presence of noise, and mass irregularities. We have developed a software tool that automatically identifies variations in the four physical phenomena with respect to their normal ranges, and therefore allows normal voice to be differentiated from pathological voices. To analyze the performance of this system, we evaluated 86 speakers in a control group and 155 speakers with various laryngeal disorders and distinct degrees of dysphonia. A sensitivity of 89% and a specificity of 89.5% were obtained in discriminating between normal and pathological voices. This clinical study shows that the tool is clinically relevant in the assessment and documentation of patients with voice disorders (AU)

Modeling the lexical morphology of Western handwritten signatures.

A handwritten signature is the final response to a complex cognitive and neuromuscular process which is the result of the learning process. Because of the many factors involved in signing, it is possible to study the signature from many points of view: graphologists, forensic experts, neurologists and computer vision experts have all examined them. Researchers study written signatures for psychiatric, penal, health and automatic verification purposes. As a potentially useful, multi-purpose study, this paper is focused on the lexical morphology of handwritten signatures. This we understand to mean the identification, analysis, and description of the signature structures of a given signer. In this work we analyze different public datasets involving 1533 signers from different Western geographical areas. Some relevant characteristics of signature lexical morphology have been selected, examined in terms of their probability distribution functions and modeled through a General Extreme Value distribution. This study suggests some useful models for multi-disciplinary sciences which depend on handwriting signatures.

Genetic variants within the TNFRSF1B gene and susceptibility to rheumatoid arthritis and response to anti-TNF drugs: a multicenter study.

BACKGROUND: Recent research suggests that genetic variants in the tumor necrosis factor receptor 2 (TNFRSF1B) gene may have an impact on susceptibility to rheumatoid arthritis (RA) and drug response. The present population-based case-control study was carried out to evaluate whether 5 tagging single-nucleotide polymorphisms (SNPs) within the TNFRSF1B gene are associated with the risk of RA and response to antitumor necrosis factor (TNF) drugs. METHODS: The study population included 1412 RA patients and 1225 healthy controls. A subset of 596 anti-TNF-naive RA patients was selected to assess the association of TNFRSF1B SNPs and drug response according to the EULAR response criteria. RESULTS: We found that carriers of the TNFRSF1Brs3397C allele had a significantly increased risk of developing RA (P=0.0006). Importantly, this association remained significant after correction for multiple testing. We also confirmed the lack of association of the TNFRSF1Brs1061622 SNP with the risk of RA in the single-SNP analysis (P=0.89), but also through well-powered meta-analyses (PDOM=0.67 and PREC=0.37, respectively). In addition, our study showed that carriers of the TNFRSF1Brs3397C/C, TNFRSF1Brs1061622G/G, and TNFRSF1Brs1061631A/A genotypes had an increased risk of having a worse response to anti-TNF drugs at the level of P less than 0.05 (P=0.014, 0.0085 and 0.028, respectively). We also observed that, according to a log-additive model, carriers of the TNFRSF1Brs3397C or TNFRSF1Brs1061622G alleles showed an increased risk of having worse response to anti-TNF medications (P=0.018 and 0.0059). However, the association of the TNFRSF1Brs1061622 SNP only reached marginal significance after correction for multiple testing according to a log-additive model (P=0.0059) and it was not confirmed through a meta-analysis (PDOM=0.12). CONCLUSION: Our results suggest that the TNFRSF1Brs3397 variant may play a role in modulating the risk of RA, but does not provide strong evidence of an impact of TNFRSF1B variants in determining response to anti-TNF drugs.

Application of the Teager-Kaiser energy operator in bearing fault diagnosis.

Condition monitoring of rotating machines is important in the prevention of failures. As most machine malfunctions are related to bearing failures, several bearing diagnosis techniques have been developed. Some of them feature the bearing vibration signal with statistical measures and others extract the bearing fault characteristic frequency from the AM component of the vibration signal. In this paper, we propose to transform the vibration signal to the Teager-Kaiser domain and feature it with statistical and energy-based measures. A bearing database with normal and faulty bearings is used. The diagnosis is performed with two classifiers: a neural network classifier and a LS-SVM classifier. Experiments show that the Teager domain features outperform those based on the temporal or AM signal.

On the feasibility of interoperable schemes in hand biometrics.

Personal recognition through hand-based biometrics has attracted the interest of many researchers in the last twenty years. A significant number of proposals based on different procedures and acquisition devices have been published in the literature. However, comparisons between devices and their interoperability have not been thoroughly studied. This paper tries to fill this gap by proposing procedures to improve the interoperability among different hand biometric schemes. The experiments were conducted on a database made up of 8,320 hand images acquired from six different hand biometric schemes, including a flat scanner, webcams at different wavelengths, high quality cameras, and contactless devices. Acquisitions on both sides of the hand were included. Our experiment includes four feature extraction methods which determine the best performance among the different scenarios for two of the most popular hand biometrics: hand shape and palm print. We propose smoothing techniques at the image and feature levels to reduce interdevice variability. Results suggest that comparative hand shape offers better performance in terms of interoperability than palm prints, but palm prints can be more effective when using similar sensors.

Offline geometric parameters for automatic signature verification using fixed-point arithmetic.

This paper presents a set of geometric signature features for offline automatic signature verification based on the description of the signature envelope and the interior stroke distribution in polar and Cartesian coordinates. The features have been calculated using 16 bits fixed-point arithmetic and tested with different classifiers, such as hidden Markov models, support vector machines, and Euclidean distance classifier. The experiments have shown promising results in the task of discriminating random and simple forgeries.