Departamento de Ingeniería de Telecomunicación
URI permanente para esta comunidadhttps://hdl.handle.net/10953/39
En esta Comunidad se recogen los documentos generados por el Departamento de Ingeniería de Telecomunicación y que cumplen los requisitos de Copyright para su difusión en acceso abierto.
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Examinando Departamento de Ingeniería de Telecomunicación por Autor "Cañadas-Quesada, Francisco Jesús"
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Ítem A constrained tonal semi-supervised non-negative matrix factorization to classify presence/absence of wheezing in respiratory sounds(Elsevier, 2020-04-01) Torre-Cruz, Juan; Cañadas-Quesada, Francisco Jesús; García-Galán, Sebastián; Ruiz-Reyes, Nicolás; Vera-Candeas, Pedro; Carabias-Orti, Julio JoséFrom a clinical point of view, the detection of wheezing presence in respiratory sounds is a challenging task for early identification of pulmonary diseases since wheezing is the main manifestation associated to airway obstruction. In this article, we propose a novel method to detect the presence or absence of wheeze sounds in breath recordings in order to increase the reliability of the subjective diagnosis provided by the physician in the auscultation process. Specifically, it is assumed an unhealthy subject when wheeze sounds can be detected during breathing. The proposed method consists of three stages. The first stage attempts to estimate the spectral interval, band of interest (BOI), that shows the highest probability to find wheeze sounds. In the second stage, a constrained tonal semi-supervised non-negative matrix factorization (NMF) approach is applied to obtain spectral patterns that models the periodic or tonal nature typically shown by wheeze sounds. The third stage analyzes the estimated wheezing spectrogram based on the smoothness of the spectral trajectories from the most significant energy previously factorized in the BOI. Our system has been evaluated and compared to other state-of-the-art methods, yielding competitive results in the wheezing presence detection in respiratory sounds.Ítem A novel wheezing detection approach based on constrained non-negative matrix factorization(Elsevier, 2019-05-01) Torre-Cruz, Juan; Cañadas-Quesada, Francisco Jesús; Carabias-Orti, Julio José; Vera-Candeas, Pedro; Ruiz-Reyes, NicolásThe early wheezing detection is still a challenging task in biomedical signal processing because the presence of wheeze sounds often indicate respiratory diseases from airway obstructions. Currently, most of the first clinical examinations to detect any airway obstructions are carried out using auscultation. However, a high percentage of diagnoses are misdiagnosed since they are highly dependent on the physician’s training in the wheezing detection, especially in noisy environments in which weak wheeze sounds can be masked by louder respiratory sounds. In this work, we propose a novel wheezing detection approach, based on Constrained Non-negative Matrix Factorization, that uses two-stage cascade: separation and detection. The novelty of the separation stage is to model wheeze and respiratory sounds as reliably as possible that they can be observed in the nature incorporating constraints (sparseness and smoothness) into the NMF factorization. Once the estimated wheezing and respiratory signal are obtained from the separation stage, the detection contribution is based on the use of the Kullback-Leibler divergence to discriminate between wheezing and respiratory areas. The experiments have been conducted using three different datasets composed of healthy or unhealthy patients. First, an optimization process is applied to obtain the optimal parameters of the separation stage. Finally, the performance of the wheezing detection of the proposed method is evaluated taking into account other state-of-the-art methods. Experimental results report that i) the proposed method outperforms recent state-of-the-art wheezing detection approaches showing a robust wheezing detection performance even evaluating noisy environments and ii) the ability of the proposal to reliably detect healthy patients.Ítem Monitoring the internal quality of ornamental stone using impact-echo testing(Elsevier, 2019-12-01) Montiel-Zafra, María Violeta; Cañadas-Quesada, Francisco Jesús; Campos-Suñol, María José; Vera-Candeas, Pedro; Ruiz-Reyes, NicolásThe decay and durability of stone materials is a natural response to the progressive adjustment to different environmental and harsh conditions. Usually stone building elements with no apparent sign of decay are affected by the loss of cohesion. Non-invasive, early and low-cost identification of the internal damage of stone materials would be a great step forward. This paper presents an impact-echo (IE) method to analyse the internal quality of ornamental stone. The proposed method attempts to estimate the P-wave velocity in the material applying a frequency estimator that best explains the energy distribution of the possible modes of vibration from the captured IE signals. The velocity estimation will be analysed along a set of freeze-thawing cycles in order to establish a correlation with the internal damage caused in the material confirmed by its porosity. This value has been measured after several freezing-thawing cycles at each stone specimen. Experimental results show that the proposed method can be considered as a valid and effective tool for determining the internal damage of ornamental stone materials. Besides, the proposed method could be easily adapted to analyse specimens of different sizes, shapes and types of rocks.