Germán Castellanos

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Heuristical algorithms can reduce the computational complexity. Such methods require of some stopping criteria (cost function). Some of these cost functions are based on statistics like univariate and multivariate methods of analysis. Dimensional reduction techniques such as principal component analysis (PCA) allow to find a lower dimension transformed(More)
The follow-up of some cardiac diseases may be achieved by ECG-holter record analysis. A heartbeat clustering method can be used to reduce the usually high computational cost of such holter analysis. This study describes a method aimed at cardiac arrhythmia recognition based on this approach, by means of unsupervised inspection of morphologically similar(More)
Adequate recognition of lips posture for speech articulation analysis requires of the measurement of several anthropometric mouth parameters. These are needed to estimate the position and contour of the lips and teeth and tongue positions, as well. Here, a method is proposed for lips contour detection under natural conditions without any extra hardware(More)
Here, an analysis of different acoustic features and their influence in automatic identification of hypernasality is shown. Effective feature selection method includes preprocessing of the initial feature space based on statistical independence analysis. Simultaneously, the synthesis of a specialized diagnostic feature is proposed based on analyzing the(More)
A system for feature extraction and recognition of lip postures is presented, by constructing a shape model of the inner and outer contours of the lips, whose parameters are controlled by a canonical genetic algorithm. Features of each posture are the model parameters which better fit to the analyzed image. A Bayesian classifier is used to classify, under(More)
Hidden Markov models have shown promising results for identification of spike sources in Parkinson's disease treatment, e.g., for deep brain stimulation. Usual classification criteria consist in maximum likelihood rule for the recognition of the correct class. In this paper, we present a different classification scheme based in proximity analysis. For this(More)
Importance of the resonance frequencIes of the vocal tract In estImatIng artIculatory posItIons Abstract — Acoustic-to-Articulatory inversion, which seeks to estimate an articulator position using the acoustic information in the speech signal, offers several potential applications in the field of speech processing. In this context, it is important to use(More)
Micropatterned adhesive surfaces may have potential in reconstructive surgery. The adhesion performance of mice ear skin to micropatterned poly(dimethylsiloxane) (PDMS) was investigated, under in vitro conditions, and compared to flat substrates. No significant difference in separation force F was observed between flat substrates and micropatterned surfaces(More)
HMMs are statistical models used in a very successful and effective form in speech recognition. However, HMM is a general model to describe the dynamic of stochastic processes; therefore it can be applied to a huge variety of biomedical signals. Usually, the HMM parameters are estimated by means of MLE (Maximum Likelihood Estimation) criterion.(More)