RESUMO
The classification of surface myoelectric signals (sEMG) remains a great challenge when focused on its implementation in an electromechanical hand prosthesis, due to its nonlinear and stochastic nature, as well as the great difference between models applied offline and online. In this work, the selection of the set of the features that allowed us to obtain the best results for the classification of this type of signals is presented. In order to compare the results obtained, the Nina PRO DB2 and DB3 databases were used, which contain information on 50 different movements of 40 healthy subjects and 11 amputated subjects, respectively. The sEMG of each subject was acquired through 12 channels in a bipolar configuration. To carry out the classification, a convolutional neural network (CNN) was used and a comparison of four sets of features extracted in the time domain was made, three of which have shown good performance in previous works and one more that was used for the first time to train this type of network. Set one is composed of six features in the time domain (TD1), Set two has 10 features also in the time domain (TD2) including the autoregression model (AR), the third set has two features in the time domain derived from spectral moments (TD-PSD1), and finally, a set of five features also has information on the power spectrum of the signal obtained in the time domain (TD-PSD2). The selected features in each set were organized in four different ways for the formation of the training images. The results obtained show that the set of features TD-PSD2 obtained the best performance for all cases. With the set of features and the formation of images proposed, an increase in the accuracies of the models of 8.16% and 8.56% was obtained for the DB2 and DB3 databases, respectively, compared to the current state of the art that has used these databases.
Assuntos
Amputados , Gestos , Algoritmos , Eletromiografia/métodos , Mãos , Humanos , Movimento , Redes Neurais de ComputaçãoRESUMO
Different coalescence processes on 1D silver nanostructures synthesized by a PVP assisted reaction in ethylene glycol at 160 °C were studied experimentally and theoretically. Analysis by TEM and HRTEM shows different defects found on the body of these materials, suggesting that they were induced by previous coalescence processes in the synthesis stage. TEM observations showed that irradiation with the electron beam eliminates the boundaries formed near the edges of the structures, suggesting that this process can be carried out by the application of other means of energy (i.e. thermal). These results were also confirmed by theoretical calculations by Monte Carlo simulations using a Sutton-Chen potential. A theoretical study by molecular dynamics simulation of the different coalescence processes on 1D silver nanostructures is presented, showing a surface energy driven sequence followed to form the final coalesced structure. Calculations were made at 1000-1300 K, which is near the melting temperature of silver (1234 K). Based on these results, it is proposed that 1D nanostructures can grow through a secondary mechanism based on coalescence, without losing their dimensionality.
RESUMO
The implications of delta-aminolevulinic acid dehydratase (ALAD) polymorphism for lead kinetics and toxicity have been mainly studied in occupationally exposed adults. Therefore, our purpose was to evaluate the distribution of ALAD genotype and its association with biomarkers of exposure (PbB levels) and effect (Blood ZPP) among children living in a smelter community in Mexico. We recruited 569 children from nine elementary schools close to a smelter site. PbB was determined by electrothermal atomic absorption spectrometry. A polymerase chain reaction (PCR)-based protocol was used for ALAD genotyping. Zinc protoporphyrin (ZPP) in blood was measured by direct fluorometry. Most children (93.15%) were homozygous for ALAD (1-1), 6.67% were heterozygous for ALAD for (1-2), and one child was homozygous for ALAD (2-2). There was an increased proportion of ALAD (1-2/2-2) genotype with respect to PbB levels. The ZPP geometric mean was slightly higher in ALAD (1-1) genotype children (63.48 mu mol ZPP/mol Hb) than in those having the ALAD-2 genotype (58.22 mu mol ZPP/mol Hb; p = 0.051). Linear and quadratic models showed significant relationships between ZPP and PbB. A significant increase in the odds ratio (OR) for the effect of lead exposure on ZPP levels was observed for ALAD (1-1) children having PbB values above 20 mu g/dL, as compared to those having PbB levels below 10 mu g/dL (OR = 2.95, 95% CI = 1.45-5.97; p = 0.003), whereas no significant increases were observed for the ALAD (1-2/2-2) children. In summary, our results suggest that heme biosynthesis was less affected in ALAD (1-2/2-2) lead-exposed children than in those carrying the ALAD (1-1) genotype.