Lung sounds classification using convolutional neural networks.

Lung sounds convey relevant information related to pulmonary disorders, and to evaluate patients with pulmonary conditions, the physician or the doctor uses the traditional auscultation technique. However, this technique suffers from limitations. For example, if the physician is not well trained, this may lead to a wrong diagnosis. Moreover, lung sounds are non-stationary, complicating the tasks of analysis, recognition, and distinction. This is why developing automatic recognition systems can help to deal with these limitations. In this paper, we compare three machine learning approaches for lung sounds classification. The first two approaches are based on the extraction of a set of handcrafted features trained by three different classifiers (support vector machines, k-nearest neighbor, and Gaussian mixture models) while the third approach is based on the design of convolutional neural networks (CNN). In the first approach, we extracted the 12 MFCC coefficients from the audio files then calculated six MFCCs statistics. We also experimented normalization using zero mean and unity variance to enhance accuracy. In the second approach, the local binary pattern (LBP) features are extracted from the visual representation of the audio files (spectrograms). The features are normalized using whitening. The dataset used in this work consists of seven classes (normal, coarse crackle, fine crackle, monophonic wheeze, polyphonic wheeze, squawk, and stridor). We have also experimentally tested dataset augmentation techniques on the spectrograms to enhance the ultimate accuracy of the CNN. The results show that CNN outperformed the handcrafted feature based classifiers.

A physical approach to the automated classification of clinical percussion sounds.

Chest percussion is a traditional technique used for the physical examination of pulmonary injuries and diseases. It is a method of tapping body parts with fingers or small instruments to evaluate the size, consistency, borders, and presence of fluid/air in the lungs and abdomen. Percussion has been successfully used for the diagnosis of such potentially lethal conditions as traumatic and tension pneumothorax. This technique, however, has certain shortcomings, including limitations of the human ear and the subjectivity of the administrator, that lead to overall low sensitivity. Automation of the method by using a standardized percussion source and computerized classification of digitized signals would remove the subjective factor and other limitations of the technique. It would also enable rapid on-site diagnostics of pulmonary traumas when thorough clinical examination is impossible. This paper lays the groundwork for an objective signal classification approach based on a general physical model of a damped harmonic oscillator. Using this concept, critical parameters that effectively subdivide percussion signals into three main groups, historically known as "tympanic," "resonant," and "dull," are identified, opening the possibility for automated diagnostics of air/liquid inclusions in the thorax and abdomen. The key role of damping in forming the character of the percussion signal is investigated using a 3D thorax phantom. The contribution of the abdominal component into the complex multimode spectrum of chest percussion signals is demonstrated.

Two-stage classification of respiratory sound patterns.

The classification problem of respiratory sound signals has been addressed by taking into account their cyclic nature, and a novel hierarchical decision fusion scheme based on the cooperation of classifiers has been developed. Respiratory signals from three different classes are partitioned into segments, which are later joined to form six different phases of the respiration cycle. Multilayer perceptron classifiers classify the parameterized segments from each phase and decision vectors obtained from different phases are combined using a nonlinear decision combination function to form a final decision on each subject. Furthermore a new regularization scheme is applied to the data to stabilize training and consultation.

Organizacao e avaliacao de um software para ensino de ausculta respiratoria / Organization and evaluation of a software for teaching respiratory auscultation

O objetivo deste trabalho foi elaborar um software multimidia para o desenvolvimento de um programa de ensino de ausculta pulmonar e avaliar o aprendizado do conteudo apos a utilizacao desta forma de ensino. Metodo : O software foi...

Variabilidade dos termos utilizados em ausculta pulmonar alterada no HCPA / Variability of terms utilized in abnormal pulmonary auscultation at HCPA

Alguns equivocos de traducao e o uso inadequado de novos termos descrevendo os ruidos adventicios na ausculta pulmonar sao responsaveis pela falta de padronizacao desta nomenclatura, dificultando a comunicacao na pratica e ensino medicos. Em 382 prontuarios revisados quanto ao registro de ruidos adventicios no momento da internacao no HCPA, foram tabulados 18 termos didtintos utilizados, independentemente da sua frequencia de aparecimento. Em apenas 8 dos 165 prontuarios com registro de ausculta alterada, houve caracterizacao correta dos ruidos quanto ao tempo no ciclo respiratorio. A variabilidade de termos encontrada sugere a falta de padronizacao da nomenclatura da ausculta em nosso meio, bem como a nao utilizacao da terminologia internacional de sons respiratorios existente. Os autores discutem a importancia da uniformizacao destes termos e apresentam a classificacao atualmente proposta

The arts of percussion and auscultation of the chest re-examined.

Clinical teaching of percussion and auscultation is examined critically, and it is suggested that there is confusion on the subject both in textbooks and in the minds of clinicians and students. Percussion should be viewed more in terms of 'feel' than 'sound', and thus a classification of 'hard', 'intermediate' and 'soft' dullness is introduced. As regards auscultation, a plea is made for differentiation between obstructed and non-obstructed consolidation of lobes, a point recognized by some clinicians, but not enunciated with clarity by teachers. The differences between the clinical findings in obstructive consolidation of the upper and lower lobes are discussed. The importance of distinguishing between tracheal and bronchial breathing is emphasized.