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The objective of this exploratory study was to develop signal processing methods for assisting in the diagnosis of arteriovenous fistula stenosis on patients suffering from endstage renal disease and undergoing haemodialysis treatments. The proposed method is based on the classification of vessels sounds utilizing parameter extraction from wavelets transform coefficients. The coefficients energy of selected scales (frequency bands) were fed to a support vector machine based system for classification. Results suggested that this technique can be useful for diagnosis purposes to physicians during the auscultation procedure.

The simulation approach is an important tool used for the design and implementation of mobile radio systems with an emphasis on the propagation modeling for wireless channel. In this paper. we carried out simulations for three different street positions scenarios o f the receiver, (mobile station). using the Geometrical-Based Single Bounce Elliptical Channel model. as might be appropriate for microcellular applications and mobile-to-mobile communication. From the simulation results we use the parameters time-of-arrival (TOA) and angle-of-arrival (AOA), (delay and angular domain. respectively), to estimate the higher order channel statistics, such as the delay spread (DS) and the angle spread (AS). respectively.

In this paper we present analytical expressions for the angle-of-arrival (AOA) power density function (PDF) and its application in geometrically based channel models for urban environments. In order to evaluate the theoretical clusters PDF in angle domain proposed, we make computer simulations and comparisons with experimental results for wideband channel models, published in the open literature. The comparison with experimental results shows good agreement. The generalized clusters PDF derived in this paper can be used to simulate a power-delay-angle profile and to quantify second order statistics, i.e., angle spread for a given elliptical shape of the cluster.

In this paper, a feature extraction method based on principal component analysis was developed for classification of the vascular access's condition in hemodialysis patients. The assessment of the method was carried out by discriminating between before and after angioplasty sound recordings as well as before angioplasty and reference recordings. The results showed that when before and after angioplasty recordings were compared by patient, the classification agreed with the result of angioplasty procedure. When all the available before and after angioplasty recordings were compared, it was still possible to discriminate them at a good rate. On the other hand, when the reference recordings substituted the after angioplasty recordings, almost a perfect discrimination was achieved.