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Predicting movement intention based on pattern recognition of biosignals are becoming increasingly important in many clinical and research applications. The main idea of these technologies is to use a human-in-the-loop system for controlling several hardware devices, in which the identification of the user intention is the most challenging aspect. Electromyography (EMG) provides biological signals...
The electronic and computational development has helped to create many new applications where the principal idea is obtaining better results in case of an emergency. Over time, we have investigated about new processes and strategies to analyze data, and how to use by audiovisual media to teach people to respond to emergency response, or any natural disaster as a seism.
Binaural hearing aids have been recognized as the most optimal strategy to improve hearing in people with hearing impairment in both ears. In this sense, to improve hearing in noisy environments, binaural methods outperform monaural methods with respect to noise reduction, speech intelligibility and sound quality. Among binaural noise-reduction methods, multichannel Wiener filters (MWF) have shown...
The electroencephalography is a technique used in brain mapping with applications in research and clinical practice. The current work aims to assess the reliability of quantitative electroencephalography and coherence measurements. Two electroencephalography sessions, obtained 4 to 6 weeks apart during resting state and memory condition, were recorded in 15 young healthy subject. For each subject...
Civil engineers use during tests various mechanisms and tools to estimate deformation of structures and materials such as the strain gage, which measures superficial deformation in cylindrical or block pieces, thus registering dimensional changes. Sometimes such experiments cause the destruction of the sensor element, increasing their cost and industrial liter, proportionally to the number of tests...
In this paper, a SVM-based method is implemented for the prediction of protein-protein interactions. This model is initially trained with a set of over 69.000 pairs of protein sequences based on documented positive interactions. Then, a cross-validation method is performed for estimating the accuracy of the system, showing acceptable performances in terms of sensitivity, specificity and geometric...
The design of a Structural Health Monitoring (SHM) systems is a requirement in the task of improving the safety and maintainability of the structures. Among the multiple techniques available for health monitoring, acousto-ultrasonics (AU) offers the possibility of inspecting large areas of structures from a piezoelectric active sensor network with a relatively small number of sensors. This paper proposes...
This paper presents a comparison of three strategies for managing the imbalance problem: undersampling, SMOTE and Weighted SVM. Undersampling is a strategy where the samples of the majority class are discarded; SMOTE (Synthetic Minority Over-sampling Technique) is a method in which synthetic samples of the minority class are added to the dataset; Weighted SVM keeps the number of samples of each class...
In this paper, we developed a method of simulation for intracerebral signals acquired during Deep Brain Stimulation - DBS surgery in one patient with Parkinson's disease. Based on our previous work, an auto-regressive (AR) parametric model with order 13 was used, because it generates one of the most accurate representations of basal ganglia signals in movement disorders. Then, the AR parameters were...
Within the context of epileptic sources localization from electroencephalographic signals, this work presents an exploratory study aimed at studying the effect of channel weighting on the estimation of the inverse problem solution. In this study, we consider two weighting approaches followed from a relevance feature analysis based on variance and energy criteria. Such approaches are compared by measuring...
This work consists in the design and construction of a line follower robot controlled by a camera connected to a Cyclone IV FPGA in a development board DE0-NANO from the company TERASIC. The camera is a TDRB-D5M. Using computer vision algorithms programmed into the FPGA we are able to guide the robot through a line of one of three possible colors. We follow the line by the use of techniques for masking...
One of the most common causes of traffic accidents is the driver's fatigue. So in this paper, a methodology for detection of eyestrain, in different lighting conditions, is presented by analyzing the blink rate using computer vision techniques. An algorithm that takes face recognition was used, then a technique based on edge detection and measurement of texture to segment the eye and to count the...
We present a comparative study about stereoscopic reconstruction process focused in modelling for parallel axis stereoscopic cameras. We used two classical models and one based on Artificial Neural Networks for modelling the parallel axis system. Then we used the root mean square of distances between the point coordinates calculated from images and measured from the calibration pattern to evaluate...
As a methodology for automatic detection of Parkinson's disease (PD), it is proposed the estimation of the different glottal flow features considering nonlinear behavior of the vocal folds. This paper evaluates the discrimination capability of set with eight different Nonlinear Dynamic (NLD) features. The experiment presented considering the five Spanish vowels uttered by 50 People with PD (PPD) and...
Dimensionality reduction (DR) methods represent a suitable alternative to visualizing data. Nonetheless, most of them still lack the properties of interactivity and controllability. In this work, we propose a data visualization interface that allows for user interaction within an interactive framework. Specifically, our interface is based on a mathematic geometric model, which combines DR methods...
The automatic detection of objects of interest from video sequences is a task of great importance for computer vision applications. Mostly, the detection of these objects is performed using supervised classification techniques, requiring a set of labeled training samples, known as ground truth data. These training samples are commonly labeled by a manual process using rectangular regions (bounding...
Computer vision systems allow identifying physical characteristics and product defects in a non-invasive and reliable form. Due to these advantages, computer vision systems have been widely accepted in the agricultural and food industries, since these industries require a high demand for objectivity, consistency and efficiency in the quality control of the product, requirements that can be met by...
Current technologies and methods for cutting pieces of a raw material, have a big limitation, and without despising its efficacy and precision, its scope and area of work limit the materials that are possible to manufacture in only process stage; This is a task of an area of research how to solve this disadvantage without losing the efficiency of the past technologies.
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