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INTRODUCTION: The cycling activity has increased in recent years, either as a means of leisure or physical activity or as means of transport. Discomfort is one of the main complaints for cyclists, especially when related to the type o pavement they use while riding. This work presents a study of measurement and evaluation of human exposure to hand-arm vibration in the leisure cyclist activity in different pavements in order to classify according to vibration discomfort and to vibration injury risk. METHODS: Vibration measurements are performed for three pavement types, asphalt (AS), precast concrete slab (PC), and interlocking concrete blocks (BI), using two bicycle models (time trial speed racing bike, S and mountain bike, MB), and cyclists with different physical characteristics. It is performed a quantitative analysis of each configuration - pavement type × bike model × cyclist - where the daily vibration exposure A(8) is evaluated, as defined in ISO 5349-1 Standard, for 2h daily exposure. It is also evaluated the maximum daily exposure in order to reach limit values, as defined by Directive 2002/44/EC. RESULTS: Based on a subjective analysis (survey), it is evaluated the comfort degree for vibration exposure for each tested pavement, according to a survey within cyclists. Finally, the results are compared using both quantitative and subjective analysis. CONCLUSIONS: Not surprisingly, it has been noticed that the most comfortable pavement type is the asphalt pavement (AS), followed by the precast concrete pavement (PC) and by the interlocking concrete blocks pavement (BI), confirming the opinion pool within cyclists. As a new finding, for some pavement types, bikes and daily journey activities, the vibration levels may reach health limit levels which justify the originality of the work and the importance as guidance for healthy public decisions for new cycle paths.

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INTRODUCTION: Face recognition, one of the most explored themes in biometry, is used in a wide range of applications: access control, forensic detection, surveillance and monitoring systems, and robotic and human machine interactions. In this paper, a new classifier is proposed for face recognition: the novelty classifier. METHODS: The performance of a novelty classifier is compared with the performance of the nearest neighbor classifier. The ORL face image database was used. Three methods were employed for characteristic extraction: principal component analysis, bi-dimensional principal component analysis with dimension reduction in one dimension and bi-dimensional principal component analysis with dimension reduction in two directions. RESULTS: In identification mode, the best recognition rate with the leave-one-out strategy is equal to 100%. In the verification mode, the best recognition rate was also 100%. For the half-half strategy, the best recognition rate in the identification mode is equal to 98.5%, and in the verification mode, 88%. CONCLUSION: For face recognition, the novelty classifier performs comparable to the best results already published in the literature, which further confirms the novelty classifier as an important pattern recognition method in biometry.

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INTRODUCTION: In the study of human biomechanics, it is often desirable to evaluate fatigue in the muscles that are involved in performing a particular task. Identifying the phenomena responsible for this condition is a problem that in most cases is complex and requires appropriate research mechanisms. Isokinetic dynamometry (ID) and surface electromyography (SEMG) are two techniques widely used in studies on strength and muscle fatigue. Their effectiveness is conditioned upon a good understanding of their limitations and the adoption of procedures to fully exploit the potential of each one. The main goal of the present study is to verify whether the electromyographic parameters, especially the conduction velocity (CV), are sensitive to the fatigue instauration process within sets of maximal isokinetic contractions. CV is a basic physiological parameter directly related to muscle activity and still little explored in experiments combining ID and SEMG. METHODS: Instrumentation architecture that combines ID and SEMG was used to estimate electromyographic and biomechanical parameters in protocols of maximum intensity isokinetic knee extension exercises. This architecture allows for limiting the parameter estimates to a specific region of isokinetic exercise, called the isokinetic load range (ILR), where one can consider that the angular velocity is constant and the SEMG signals are cyclo-stationary. Electromyographic signals were acquired using an array of electrodes. CONCLUSION: The results suggest that CV and the other SEMG parameters, including amplitude and frequency descriptors, are sensitive to detect a fatigue process only in protocols that restrict the analysis to ILR and that also bring the subject to a state of fatigue quickly.

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INTRODUCTION: Sleepiness is responsible for a considerable proportion of traffic accidents. It is thus an important traffic safety issue to find a robust, objective and practical way to estimate the amount of time a person has been awake. To attempt to meet this goal, we investigated the relationship between sleepiness and posture control. METHODS: Subjects were kept awake for 36 hours and posturographic data during quiet standing were collected every two hours by means of a force platform. The standing surface (rigid surface or foam surface) and visual (eyes open or eyes closed) conditions were manipulated. RESULTS: In the more challenging conditions (with foam surface and/or eyes closed), the body sway variables derived from the center of the pressure measurement increased significantly when time since awakening became greater than 21 h in almost all subjects. CONCLUSION: Based on this result, we propose a practical protocol that could robustly assess whether time since awakening was greater than 21 h.

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INTRODUCTION: The objective of this paper is to verify the influence of the source geometry on Geiger Müller (GM) exposure rate data. This paper presents a validation of an application based on Monte Carlo (MC) data simulated using Geant4, based on a comparison of the exposure rates calculated via MC and Deterministic Calculations (DC) to experimental (measured) exposure rates. METHODS: Experimental data that were collected through measurements of standard sources were used for MC and DC validation. In addition, the best method of analyzing the impact of the real source geometry on calculations of a descarpack box of radioactive waste was verified. Furthermore, were estimated the exposure rates from a homogeneous solid waste box (used at clinical sites) and from a point source. These results were compared to confirm possible discrepancies related to source geometry in exposure rates collected using a GM detector. RESULTS: The investigated estimation methods were statistically compared; the MC presented higher agreement with the experimental data than did the deterministic calculations. The impact of considering a point source instead of the real geometry (descarpack box) was an underestimation of between 20% and 70%, depending on the source - detector distance and the isotope evaluated. CONCLUSION: The DC always presented a higher difference with respect to the experimental data than did the MC calculation. The use of realistic geometry proved to exert a significant impact on the exposure rate data for solid radioactive waste compared with the exposure rate induced by a point source; the exposure rate estimation obtained using the real geometry was always at least 16% higher than the estimation obtained for a point source, and some differences greater than 50% were found.

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INTRODUCTION: Automatic detection of blood components is an important topic in the field of hematology. Segmentation is an important step because it allows components to be grouped into common areas and processed separately. This paper proposes a method for the automatic segmentation and classification of blood components in microscopic images using a general and automatic fuzzy approach. METHODS: During pre-processing, the supports of the fuzzy sets are automatically calculated based on the histogram peaks in the green channel of the RGB image and the Euclidean distance between the leukocyte nuclei centroids and the remaining pixels. During processing, fuzzification associates the degree of pertinence of the gray level of each pixel in the regions defined in the histogram with the proximity of the leukocyte nucleus centroid closest to the pixel. The fuzzy rules are then applied, and the image is defuzzified, resulting in the classification of four regions: leukocyte nuclei, leukocyte cytoplasm, erythrocytes and blood plasma. In post-processing, false positives are reduced and the leukocytes (including the nucleus and cytoplasm), erythrocytes and blood plasma are segmented. RESULTS: A total of 530 microscopic images of blood smears were processed, and the results were compared with the results of manual segmentation by experts and the accuracy rates of other approaches. CONCLUSION: The method demonstrated average accuracy rates of 97.31% for leukocytes, 95.39% for erythrocytes and 95.06% for blood plasma, avoiding the limitations found in the literature and contributing to the practice of the segmentation of blood components.

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INTRODUCTION: One of the challenges in developing Computer-Aided Diagnosis (CAD) systems is their accurate and comprehensive assessment. This paper presents the conduction and results of a systematic review (SR) that aims to verify the state of the art regarding the assessment of CAD systems. This survey provides a general analysis of the current status of the design, development and assessment of such systems and includes discussions on the most used metrics and approaches that could be utilized to obtain more objective evaluation methods. METHODS: The SR was conducted using the scientific databases, ACM Digital Library, IEEE Xplore Digital Library, ScienceDirect and Web of Science. Inclusion and exclusion criteria were defined and applied to each retrieved work to select those of interest. From 156 studies retrieved, 100 studies were included. Results: There is a number of abnormalities that have been used for the development of CAD systems. Images from computed tomographies and mammographies are the most encountered types of medical images. Additionally, a number of studies used public databases for CAD evaluations. The main evaluation metrics and methods applied to CAD systems include sensitivity, accuracy, specificity and receiver operating characteristic (ROC) analyses. In the assessed CAD systems that used the segmentation method, 30.0% applied the overlap measure. DISCUSSION: There remain several topics to explore for the assessment of CAD schemes. While some evaluation metrics are traditionally used, they require a prior knowledge of case characteristics to test CAD systems. We were not able to identify articles that use software testing to evaluate CAD systems. Thus, we realize that there is a gap between CAD assessments and traditional practices of software engineering. However, the scope of this research is limited to scientific and academic works and excludes commercial interests. Finally, we discuss potential research studies within this scope to create a more objective and efficient evaluation of CAD systems.

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INTRODUCTION: The evaluation of muscular tissue condition can be accomplished with mechanomyography (MMG), a technique that registers intramuscular mechanical waves produced during a fiber's contraction and stretching that are sensed or interfaced on the skin surface. OBJECTIVE: Considering the scope of MMG measurements and recent advances involving the technique, the goal of this paper is to discuss mechanomyography updates and discuss its applications and potential future applications. METHODS: Forty-three MMG studies were published between the years of 1987 and 2013. RESULTS: MMG sensors are developed with different technologies such as condenser microphones, accelerometers, laser-based instruments, etc. Experimental protocols that are described in scientific publications typically investigated the condition of the vastus lateralis muscle and used sensors built with accelerometers, third and fourth order Butterworth filters, 5-100Hz frequency bandpass, signal analysis using Root Mean Square (RMS) (temporal), Median Frequency (MDF) and Mean Power Frequency (MPF) (spectral) features, with epochs of 1 s. CONCLUSION: Mechanomyographic responses obtained in isometric contractions differ from those observed during dynamic contractions in both passive and functional electrical stimulation evoked movements. In the near future, MMG features applied to biofeedback closed-loop systems will help people with disabilities, such as spinal cord injury or limb amputation because they may improve both neural and myoelectric prosthetic control. Muscular tissue assessment is a new application area enabled by MMG; it can be useful in evaluating the muscular tonus in anesthetic blockade or in pathologies such as myotonic dystrophy, chronic obstructive pulmonary disease, and disorders including dysphagia, myalgia and spastic hypertonia. New research becomes necessary to improve the efficiency of MMG systems and increase their application in rehabilitation, clinical and other health areas.

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INTRODUCTION: The quality control (QC) of biomedical equipment is a very important process for the quality assurance of the instruments used in diagnoses and treatments. Ultrasound diagnostic imaging is one of the most widely used techniques for diagnostic imaging in hospitals and medical clinics. However, the time required to complete several B-mode imaging QC tests in ultrasound equipment is very critical for a hospital with a high number of exams. Here, we present a computational tool to assist in the acquisition and storage of data from multiple QC tests in B-mode ultrasound diagnostic equipment to promote an efficient alternative for QC in clinical routines. METHODS: The project was planned and implemented in C++ programming language and compiled for two computing platforms: Windows and Linux. The most common QC routine tests for B-mode ultrasound were combined in a simple graphical user interface. RESULTS: After entering all of the correct QC information in the graphical user interface, a final report in PDF format was created. CONCLUSION: The proposed program has been helpful for students and diagnostic professionals and is a quick and easy application for several QC tests for B-mode ultrasound diagnostic equipment. Our program seeks to help in the dissemination and application of QC tests for B-mode ultrasound equipment in hospitals and clinics and for the technical training of ultrasound professionals.

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INTRODUCTION: The human body may interact with the structures and these interactions are developed through the application of contact forces, for instance due to walking movement. A structure may undergo changes in the dynamic behaviour when subjected to loads and human bodies. The aim of this paper is to propose a methodology using Artificial Neural Networks (ANN) to calibrate a force platform in order to reduce uncertainties in the vertical Ground Reaction Force measurements and positioning of the applied force for the human gait. METHODS: Force platforms have been used to evaluate the pattern of applied human forces and to fit models for the interaction between pedestrians and structures. The designed force platform consists in two force plates placed side by side in the direction of walking. The reference voltages applied to the Wheatstone bridge were used for calibration as the input data to the ANN, while the output data were the estimated values of the standard weights applied to the force platform. RESULTS: It was presented a framework to enhance traditional calibration methods for force platforms (vertical component) using an ANN. The use of ANN shows significant improvements for the measured variables, leading to better results with lower uncertain values that are smaller than those using a simple traditional calibration. CONCLUSION: The results suggest that the calibration with the ANN method may be useful in obtaining more accurate vertical Ground Reaction Forces and positioning measurements in a force platform for human gait analysis.