Cristiano Jacques Miosso

Motor unit action potential conduction velocity estimated from surface electromyographic signals using image processing techniques

In surface electromyography (surface EMG, or S-EMG), conduction velocity (CV) refers to the velocity at which the motor unit action potentials (MUAPs) propagate along the muscle fibers, during contractions. The CV is related to the type and diameter of the muscle fibers, ion concentration, pH, and firing rate of the motor units (MUs). The CV can be used in the evaluation of contractile properties of MUs, and of muscle fatigue. The most popular methods for CV estimation are those based on maximum likelihood estimation (MLE). This work proposes an algorithm for estimating CV from S-EMG signals, using digital image processing techniques. The proposed approach is demonstrated and evaluated, using both simulated and experimentally-acquired multichannel S-EMG signals. We show that the proposed algorithm is as precise and accurate as the MLE method in typical conditions of noise and CV. The proposed method is not susceptible to errors associated with MUAP propagation direction or inadequate initialization parameters, which are common with the MLE algorithm. Image processing -based approaches may be useful in S-EMG analysis to extract different physiological parameters from multichannel S-EMG signals. Other new methods based on image processing could also be developed to help solving other tasks in EMG analysis, such as estimation of the CV for individual MUs, localization and tracking of innervation zones, and study of MU recruitment strategies.

Use of 3D-printers to create Intensity-Modulated Radiotherapy Compensator Blocks

Intensity-Modulated Radiotherapy (IMRT) is an important tool for cancer treatment. It concentrates high radiation doses in complex target volumes, while sparing the surrounding tissues. IMRT is traditionally performed using Multileaf Collimators (MLC) or Compensator Blocks. The conventional way used to manufacture IMRT compensator blocks, which uses milling machines, is an important drawback over the MLC method, due to high operational and production costs. In this research, we developed a simpler alternative method to manufacture an IMRT compensator block from a fluency map generated by a commercial treatment planning system (TPS). This map was converted into a mold, and then printed using a 3D printer. The final IMRT compensator block was achieved by filling the mold with cerrobend alloy. To validate this method a quality assurance was performed using dosimetric films to compare the measured dose distributions to those predicted by the TPS system. This comparison showed a good agreement among 8 dose profiles from each situation, with a maximum RMS error of 8.84 % for the tested profiles. This suggests that the 3D printers can be effectively used to manufacture IMRT compensator blocks. The main advantage to this approach is that it can be fully conducted inside a radiotherapy facility, which results in lower costs and production times.

Auxiliary System For Computer-Aided Evaluation of Breast Calcifications Based on Digital Image Processing and Artificial Neural Networks

Early diagnosis still represents the best approach in the prevention and control of breast cancer, the second most frequent form of cancer worldwide. In this context, mammography has been largely used as a major method for disease early detection, as it aids the early identification of calcification clusters that can be or can later become tumors. This paper discusses the use of Wavelet Transforms to help highlight calcification areas in combination with digital image morphological techniques for feature extraction from regions of interest in digital mammography. The results obtained in this work are being upgraded to a next step, which will use a MultiLayer Perceptron artificial neural network to classify calcifications according to the most applicable category in the Breast Imaging Reporting and Data System (BIRADS).

Morphological analysis for feature extraction and classification of breast calcifications

Calcifications (calcium build-ups) in breast regions are frequently found in breast screening examinations. It is estimated that 90% of nonpalpable intraductal breast cancers are detectable morphologically by the presence of calcifications. This work performs a morphological analysis of regions of interest related to breast calcifications by extraction of a set of features that help the health care provider in the automatic classification of these calcifications. The results are being validated in a controlled test that simulates calcifications in order to consider morphological information that characterizes the geometrical characteristics. This allows one to assign an object signature and hence to approximate the test conditions to real calcifications.

An experimental evaluation of the incidence of fitness-function/search-algorithm combinations on the classification performance of myoelectric control systems with iPCA tuning

BackgroundThe information of electromyographic signals can be used by Myoelectric Control Systems (MCSs) to actuate prostheses. These devices allow the performing of movements that cannot be carried out by persons with amputated limbs. The state of the art in the development of MCSs is based on the use of individual principal component analysis (iPCA) as a stage of pre-processing of the classifiers. The iPCA pre-processing implies an optimization stage which has not yet been deeply explored.MethodsThe present study considers two factors in the iPCA stage: namely A (the fitness function), and B (the search algorithm). The A factor comprises two levels, namely A1 (the classification error) and A2 (the correlation factor). Otherwise, the B factor has four levels, specifically B1 (the Sequential Forward Selection, SFS), B2 (the Sequential Floating Forward Selection, SFFS), B3 (Artificial Bee Colony, ABC), and B4 (Particle Swarm Optimization, PSO). This work evaluates the incidence of each one of the eight possible combinations between A and B factors over the classification error of the MCS.ResultsA two factor ANOVA was performed on the computed classification errors and determined that: (1) the interactive effects over the classification error are not significative (F0.01,3,72 = 4.0659 > fAB = 0.09), (2) the levels of factor A have significative effects on the classification error (F0.02,1,72 = 5.0162 < fA = 6.56), and (3) the levels of factor B over the classification error are not significative (F0.01,3,72 = 4.0659 > fB = 0.08).ConclusionsConsidering the classification performance we found a superiority of using the factor A2 in combination with any of the levels of factor B. With respect to the time performance the analysis suggests that the PSO algorithm is at least 14 percent better than its best competitor. The latter behavior has been observed for a particular configuration set of parameters in the search algorithms. Future works will investigate the effect of these parameters in the classification performance, such as length of the reduced size vector, number of particles and bees used during optimal search, the cognitive parameters in the PSO algorithm as well as the limit of cycles to improve a solution in the ABC algorithm.

Envisioning Ecosystems - Biodiversity, Infirmity and Affectivity

Earth’s biosphere, climate biodiversity crises and environmental issues are raising a profound level of awareness concerning the collective responsibility toward Earth’s life and demanding the responsibility for promoting a healthy ecosystem. A new transdisciplinar group of Brazilian researchers at the University of Brasilia at Gama (FGA), working on the Biomedical Engineering Graduate Program, shares with the international community of Art and TechnoScience several themes related to the ecosystem biodiversity and the extremophile condition (Bec, 2007). We consider our responsibility and the urgent attention to life in our country’s huge territory, while facing the effects of an endemic infection of tropical climates and working for the preservation of the Biomes in Amazon Forest, the lung of the planet. Our collaborative projects are concerned with infirmity of the territory and the human invasion and destruction of the ecosystem self-organizing defence. Consequently, we work on health care and affective geographies, in the sense postulated by the geographer/philosopher Milton Santos (Santos, 2008 & Santos, 2009) renewed by geolocated and ubiquitous condition and sentient technologies. Interventions in social networks allow people to exist in the sense of being here and there, consisting of a largely sense of place, to be co-located, being connected everywhere, with an awareness of place amplified by the power to take care of the ecosystem. Our project leads with landscapes as a living organism in a given geography, being socially engineered, from the conceptual subjective use of space to the advanced mobile telematic computing and ubiquitous data processing and data information visualization by applying the perspective of acting everywhere – and specially in extreme and hostile space.

Module for the acquisition and processing of biological signals related to the emotional state

Medical, artistic and social applications of biomedical signals benefit from the possibility of measuring a persons emotional state, and of creating, through biofeedback techniques, a personal dynamic interaction with the environment. This paper describes a wearable microsensor module used to acquire and preprocess biological signals that are directly related to ones emotional state in daily activities. The main circuit includes a skin galvanic sensor, a breathing sensor, and an electrocardiograph with three electrodes. The acquired signals are treated by independent instrumentation amplifiers and digitized by a dedicated microcontroller at an acquisition/preprocessing board. The module and the enhanced application for Networked Communications in Biomedical Engineering and ubiquitous computing reinvent the sense of presence in the physical world when wearing a BWAS — Biocybrid Wearable Art System. Ontological levels of creative reality and phenomenological framework using embedded systems and the ways of using hardware and software are discussed. The results intend future industry developments of devices to enhance and to supplement the human perceptive and affective human condition. The identification and interpretation of appropriate models for art, communication, aesthetic, design, fashion, health, personal security or other applications are challenges for insightful discussions of the role of engineers, physiologists, artists, educators, social scientists, as well as of ethnographic methods and practices.

Biocybrid systems and the re-engineering of life

The reengineering of life expanded by perceptual experiences in the sense of presence in Virtual Reality and Augmented Reality is the theme of our investigation in collaborative practices confirming the artists´ creativity close to the inventivity of scientists and mutual capacity for the generation of biocybrid systems. We consider the enactive bodily interfaces for human existence being co-located in the continuum and symbiotic zone between body and flesh - cyberspace and data - and the hybrid properties of physical world. That continuum generates a biocybrid zone (Bio+cyber+hybrid) and the life is reinvented. Results reaffirm the creative reality of coupled body and mutual influences with environment information, enhancing James Gibsons ecological perception theory. The ecosystem life in its dynamical relations between human, animal, plants, landscapes, urban life and objects, bring questions and challenges for artworks and the reengineering of life discussed in our artworks in technoscience. Finally, we describe an implementation in which the immersion experience is enhanced by the datavisualization of biological audio signals and by using wearable miniaturized devices for biofeedback.

Compressive sensing using the log-barrier algorithm with complex-valued measurements

Compressive sensing constitutes a series of theories and algorithms that, under certain conditions, allow one to reconstruct a signal from limited linear measurements, based on knowledge about a domain where the signal is sparse. The ℓ0-minimization represents the ideal approach for reconstruction, as it searches for the sparsest representation that explains the measurements, but it is an NP-hard procedure. Fortunately, the ℓ1-minimization can frequently be used as an approximation to the ℓ0 approach, and the problem can be solved by some algorithms in polynomial time. One of the optimization problems formulated in this context corresponds to finding the sparsest solution subject to a quadratic constraint, such as in the log-barrier algorithm provided in the well- known ℓ1-Magic package. However, in this particular problem, real-valued signals are reconstructed from real- valued data. In this paper, we show how we can reconstruct sparse real-valued signals from noisy complex-valued measurements. The problem is still posed as a second-order cone program by means of the log barrier method. However, new modifications in the Newton’s step equations and in the ℓ1-Magic codes are necessary to fit the complex-valued data. In addition, in order to evaluate the reconstructions using complex data, we present the results of numerical experimentation and evaluate the performance of the signal reconstruction in terms of signal-to-error ratios. The provided method is well-suited for real applications involving the acquisition of complex-valued data, such as magnetic resonance imaging and computed tomography.

Effects of Biofeedback in Preventing Urinary Incontinence and Erectile Dysfunction after Radical Prostatectomy

In this study, we present a biofeedback method for the strengthening of perineal muscles during the preoperative procedures for radical prostatectomy, and we evaluate this technique as a prevention measure against complications such as urinary incontinence (UI) and erectile dysfunction (ED), which affect prostatectomy patients after surgery. In the experimental protocol, the patients performed specific exercises with the help of a device that provided the patient with visual biofeedback, based on a plot of the anal pressure. For the experimental protocol, we selected 20 male patients, with an average age of 64.0 years, and submitted them to ten therapeutic sessions each. A control group consisting of 32 men with an average age of 66.3 years, who were treated with the same surgical procedure but not with the preoperative procedures, also took part in the experiment. To evaluate UI and ED after the surgery in both control and experimental groups, we used two validated questionnaires—to assess UI, we used the King’s Health Questionnaire (KHQ) and, for ED, we used the International Index of Erectile Function (IIEF-5) Questionnaire. We compared the variables associated with UI and ED after the surgery for the control and experimental groups. The occurrence of UI after radical prostatectomy in the control group (100% of the patients) was higher than that for the experimental group (5% of the patients), with p < 0.0001. Likewise, the occurrence of erectile dysfunction after prostatectomy in the control group (48.6% of the patients) was higher than that for the experimental group (5% of the patients), with p < 0.0001. The number of nocturia events also decreased as a consequence of the intervention (p < 0.0001), as did the number of disposable underwear units for urinary incontinence (p < 0.0001). Furthermore, we compared, only for the experimental group, the anal pressure before the biofeedback intervention and after the surgery, and we verified that the anal pressure after surgery was significantly higher (p < 0.0001). The results strongly suggest that the preoperative biofeedback procedure was effective in decreasing urinary incontinence and erectile dysfunction after radical prostatectomy. As future work, we intend to extend this analysis for larger samples and considering a broader age range.