Modified classification of normal lung sounds applying Quantile vectors.

In this paper a novel Lung Sound Automatic Verification (LSAV) system and front-end Quantile based acoustic models to classify Lung Sounds (LS) are proposed. The utilization of Quantiles allowed an easier and objective assessment with smaller computational demand. Moreover, less-complex Gaussian Mixture Models (GMM) were computed than those previously reported. The LSAV system allowed us to reach practically negligible error in healthy (normal) LS verification. LASV system efficiency and the optimal GMM's were evaluated by using Equal Error Rate (EER) and Bayesian Information Criterion (BIC) techniques respectively. These approaches could provide a tool for broader medical evaluation which does not rely, as it is often the case, on a qualitative and subjective description of LS.

Acoustics based assessment of respiratory diseases using GMM classification.

The focus of this paper is to present a method utilizing lung sounds for a quantitative assessment of patient health as it relates to respiratory disorders. In order to accomplish this, applicable traditional techniques within the speech processing domain were utilized to evaluate lung sounds obtained with a digital stethoscope. Traditional methods utilized in the evaluation of asthma involve auscultation and spirometry, but utilization of more sensitive electronic stethoscopes, which are currently available, and application of quantitative signal analysis methods offer opportunities of improved diagnosis. In particular we propose an acoustic evaluation methodology based on the Gaussian Mixed Models (GMM) which should assist in broader analysis, identification, and diagnosis of asthma based on the frequency domain analysis of wheezing and crackles.

Effect of the extrusion on functional properties and mineral dialyzability from Phaseolus vulgaris bean flour.

The effects of extrusion conditions on cooking degree, flour dispersion viscosity and mineral potential availability of extruded bean flour were studied. Phaseolus vulgaris beans of the agronomic cultivar "Flor de mayo" were ground and dehulled to obtain grits and then extruded at different temperatures (140, 160 and 180 degrees C) and moisture contents (17, 20 and 23%), according to a bifactorial experimental design. Degree of cooking was estimated by water solubility (WS) and specific mechanical energy (SME). The effect of variables on WS and SME were analysed by surface response methodology. Flour dispersion viscosity and mineral availability (estimated by in vitro dialyzability), were also evaluated on selected samples. Results showed that, within the ranges of the variables used for this study, only the effect of temperature was significant on the degree of cooking. No direct correlation was observed between water solubility and SME, although a maximum value of WS corresponded to a range of SME values of 400-500 J/g was observed. Dispersion viscosity decreases as WS increases, so if high calorie density is desired, for instance in order to produce a cream soup formula, bean grits should be extruded at high temperature and as low moisture as possible, in our case 180 degrees C and 17% moisture. On the other hand, the effects of extrusion variables on iron and zinc dialyzability were not much affected.