Non-speech sounds (cough, wheeze) are typically known to perform better than speech
sounds for asthmatic and healthy subject classification. In this work, we use sustained …

In this work, we consider the task of automatic classification of asthmatic patients and
healthy subjects using voice stimuli. Cough and wheeze have been used as voice stimuli for …

There are several diseases (eg asthma, pneumonia etc.) affecting the human respiratory
apparatus altering its airway path substantially, thus characterising its acoustic properties …

Featured Application The automated classification of respiratory sound has gained
increasing attention in recent years and has been the subject of a growing number of …

Deep learning algorithms have been incorporated into conventional auscultation
procedures, advancing the area of respiratory sound analysis. Convolutional Neural …

Objective This study aimed to investigate and classify wheeze sound characteristics
according to asthma severity levels (mild, moderate and severe) using integrated power (IP) …

We propose a robust and efficient lung sound classification system using a snapshot
ensemble of convolutional neural networks (CNNs). A robust CNN architecture is used to …

Respiratory sound (RS) attributes and their analyses structure a fundamental piece of
pneumonic pathology, and it gives symptomatic data regarding a patient's lung. A couple of …

Respiratory diseases constitute one of the leading causes of death worldwide and directly
affect the patient's quality of life. Early diagnosis and patient monitoring, which …

Globally, respiratory diseases are the leading cause of death, making it essential to develop
an automatic respiratory sounds software to speed up diagnosis and reduce physician …