Georgina Chi-Lem

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As respiratory sounds contain mechanical and clinical pulmonary information, technical efforts have been devoted during the past decades to analysing, processing and visualising them. The aim of this work was to evaluate deterministic interpolating functions to generate surface respiratory acoustic thoracic images (RATHIs), based on multiple acoustic(More)
This work proposes multichannel acquisition of lung sounds by a microphone array, feature extraction by a multivariate AR (MAR) model, dimensionality reduction of the feature vectors (FV) by SVD and PCA and, their classification by a supervised neural network. A microphone array of 25 sensors was attached on the thoracic surface of the subjects, who were(More)
In this study, a novel approach is proposed, the imaging of crackle sounds distribution on the thorax based on processing techniques that could contend with the detection and count of crackles; hence, the normalized fractal dimension (NFD), the univariate AR modeling combined with a supervised neural network (UAR-SNN), and the time-variant autoregressive(More)
Sound transmission has been of interest for many years in an attempt to study the structure of the lung and different researches have shown that artificial sounds produce a lateralization of sound information at the thoracic surface. Most of these studies have use non-simultaneous recording and input sounds introduced at the mouth or other thoracic points.(More)
RATHI was introduced as an attempt to further improve the association between anatomical zones and specific breathing activity, both spatially and temporally. This work compares RATHI with clinical pulmonary auscultation (PA) to assess the concordance between both procedures to detect asymmetries in lung sound (LS) intensities. Twelve healthy young males(More)
This work deals with the assessment of different parameterization techniques for lung sounds (LS) acquired on the whole posterior thoracic surface for normal versus abnormal LS classification. Besides the conventional technique of power spectral density (PSD), the eigenvalues of the covariance matrix and both the univariate autoregressive (UAR) and the(More)
Several techniques have been explored to detect automatically fine and coarse crackles; however, the solution for automatic detection of crackles remains insufficient. The purpose of this work was to explore the capacity of the time-variant autoregressive (TVAR) model to detect and to provide an estimate number of fine and coarse crackles in lung sounds.(More)
Respiratory sound analysis using stethoscope continues to be the mostly used method for the diagnosis of respiratory diseases. This technique depends on detection of symptomatic adventitious sounds present with normal vesicular sounds. However, some factors such as dependence on the practitioner doctor's experience, frequency distortion of the stethoscope(More)
Multichannel analysis of lung sounds (LSs) has enabled the generation of a functional image for the temporal and spatial study of LS intensities in healthy and diseased subjects; this method is known as respiratory acoustic thoracic imaging (RATHI). This acoustic imaging technique has been applied to diverse pulmonary conditions, but it is important to(More)