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- A scalable and open source linear positioning system controllerPublication . Medeiros, M. C.; Fernandes, A. J. A.; Teixeira, C. A.; Ruano, M. GraçaThis paper is on the implementation of a dual axis positioning system controller. The system was designed to be used for space-dependent ultrasound signal acquisition problems, such as pressure field mapping. The work developed can be grouped in two main subjects: hardware and software. Each axis includes one stepper motor connected to a driver circuit, which is then connected to a processing unit. The graphical user interface is simple and clear for the user. The system resolution was computed as 127 mu m with an accuracy of 2.44 mu m. Although the target application is ultrasound signal acquisition, the controller can be applied to other devices that has up to four stepper motors. The application was developed as an open source software, thus it can be used or changed to fit different purposes.
- Time-variable blood flow averaged waveformsPublication . Leiria, A.; da Cruz Silva Andrade Madeira e Carvalho de Moura, Maria Margarida; Evans, D. H.; Ruano, M. GraçaThe computation of the average of random signals is addressed in this article. These averaging techniques are particularly relevant for Doppler blood flow clinical evaluation and research that usually accesses clinical indicators related to maximum and mean frequency, bandwidth and power variation over time. A novel technique is presented and compared to one previously described in the literature (Kitney and Giddens, "Analysis of blood velocity waveforms by phase shift averaging and autoregressive spectral estimation'', J. Biomech. Eng., 105, 398 - 404, 1983.). While the latter method is an iterative one, which sometimes does not converge, the former is a sequential technique, guaranteeing convergence. Clinical Doppler blood flow signals were averaged using both methods and the resulting waveforms were evaluated against the original signals, emphasising the impact on the relevant spectral parameters. The results obtained showed that, except for the maximum error in the computation of power variation over time, the errors produced are reduced by the proposed new algorithm.
- Métodos de soft computing para la estimación no invasiva de la temperatura en medios multicapa empleando ultrasonido retrodispersoPublication . Teixeira, C. A.; Pereira, W. C. A.; Ruano, M. Graça; Ruano, AntonioLa seguridad y eficacia de las terapias térmicas están ligadas con la determinación exacta de la temperatura, es por ello que la retroalimentacón de la temperatura en los métodos computacionales es de vital importancia.
- A framework for blood flow analysis and researchPublication . Ruano, Maria; Da Cruz Silva Andrade Madeira E Carvalho De Moura, Maria Margarida; Leiria, A.; Garcia, F.; Moreno, E.A framework to support research and clinical applications on ultrasound Doppler blood flow signals' analysis was created by integration of several subsystems into a portable computer application. Several alternatives of the different subsystems were integrated allowing the comparison amongst them. Aiming initially the study of carotid artery blood flow signals, the framework is being extended to encompass different vases -such as the mean cerebral artery - and some cardiac valves -such as the aortic and mitral valves. Developed upon Debian Linux distribution, but portable to other operating systems, the application components considered were built from open source software.
- Adaptive system for blood flow estimationPublication . da Cruz Silva Andrade Madeira e Carvalho de Moura, Maria Margarida; Leiria, A.; Ruano, M. GraçaAdaptive estimation of blood flow signals is performed resorting to a framework developed to support research on Doppler blood flow signals' analysis. Real time spectral estimation methods, real time performance evaluation and run-time adjustment of the estimation methods parameters are bound together allowing the system to adapt itself to varying signal characteristic that are caused by physiological reasons.
- A hybrid autonomous robot navigation method based on artificial intelligence and soft computing techniquesPublication . Kiss, L.; Varkonyi-koczy, A. R.; Ruano, M. GraçaThe main problem to be solved for autonomous indoor robots is that the environment where they have to move safety is only partially known and possibly dynamically changing. In this paper a hybrid navigation method is proposed, using two techniques that deal with a priori information and sensory data separately, thus blending the intelligence and optimality of global navigation methods with the reactivity and low complexity of local ones. The first, global navigation module, based on a priori information, chooses intermediary goals for the local navigation module, for which the so called A* algorithm is used. The second part, carrying out the (local) navigation relying on sensory data, applies a fuzzy-neural representation of an improved potential field based guiding navigation tool. Vision based obstacle detection is implemented by difference detection based on a combination of RGB and HSV representations of the pixels. Copyright (C) 2003 IFAC.
- Non-invasive temperature prediction of in vitro therapeutic ultrasound signals using neural networksPublication . Teixeira, C. A.; Ruano, Antonio; Ruano, M. Graça; Pereira, W. C. A.; Negreira, C.In this paper, a novel black-box modelling scheme applied to non-invasive temperature prediction in a homogeneous medium subjected to therapeutic ultrasound is presented. It is assumed that the temperature in a point of the medium is non-linearly related to some spectral features and one temporal feature, extracted from the collected RF-lines. The black-box models used are radial basis functions neural networks (RBFNNs), where the best-fitted models were selected from the space of model structures using a genetic multiobjective strategy. The best-fitted predictive model presents a maximum absolute error less than 0.4 C in a prediction horizon of approximately 2 h, in an unseen data sequence. This work demonstrates that this type of black-box model is well-suited for punctual and noninvasive temperature estimation, achieving, for a single point estimation, better results than the ones presented in the literature, encouraging research on multi-point non-invasive temperature estimation.
- Adaptive system for blood flow estimationPublication . da Cruz Silva Andrade Madeira e Carvalho de Moura, Maria Margarida; Leiria, A.; Ruano, M. GraçaAdaptive estimation of blood flow signals is performed resorting to a framework developed to support research on Doppler blood flow signals' analysis. Real time spectral estimation methods, real time performance evaluation and run-time adjustment of the estimation methods parameters are bound together allowing the system to adapt itself to varying signal characteristics that are caused by physiological reasons.
- Soft-computing-based car body deformation and EES determination for car crash analysis systemsPublication . Varkonyi-Koczy, A. R.; Rovisco, Ana; Ruano, M. GraçaCar body deformation modeling plays a very important role in crash accident analyses, as well as in safe car body design. The determination of the energy absorbed by the deformation and the corresponding energy equivalent speed can be of key importance; however, their precise determination is a very difficult task. Starting from the results of crash tests, intelligent and soft methods offer a way to model the crash process itself, as well as to determine the absorbed energy, the before-crash speed of the car, etc. In this paper, a modeling technique and an intelligent expert system are introduced, which, together, are able to follow the deformation process of car bodies in car crashes and analyze the strength of the different parts, which can significantly contribute to the improvement of the safety of car bodies.
- Numerical techniques for modeling Doppler ultrasound spectra systemsPublication . Ruano, M. GraçaEvaluation of blood-flow Doppler ultrasound spectral content is currently performed on clinical diagnosis. Since mean frequency and bandwidth spectral parameters are determinants on the quantification of stenotic degree, more precise estimators than the conventional Fourier transform should be seek. This paper summarizes studies led by the author in this field, as well as the strategies used to implement the methods in real-time. Regarding stationary and nonstationary characteristics of the blood-flow signal, different models were assessed. When autoregressive and autoregressive moving average models were compared with the traditional Fourier based methods in terms of their statistical performance while estimating both spectral parameters, the Modified Covariance model was identified by the cost/benefit criterion as the estimator presenting better performance. The performance of three time-frequency distributions and the Short Time Fourier Transform was also compared. The Choi-Williams distribution proved to be more accurate than the other methods. The identified spectral estimators were developed and optimized using high performance techniques. Homogeneous and heterogeneous architectures supporting multiple instruction multiple data parallel processing were essayed. Results obtained proved that real-time implementation of the blood-flow estimators is feasible, enhancing the usage of more complex spectral models on other ultrasonic systems.