Existing challenges, open issues and future trends will be discussed as well. A summary of the main surveyed methods together with the classification parameters and used features for the sake of comparison is given. The analysis includes detection and/or classification of the sound events. The methods are shortly described and the analyzing algorithms are explained. Relevant sounds related to abnormal respiratory activities are considered as well. Such adventitious sounds include cough, wheeze, crackle and, snore. In this paper, the smartphone-based systems for automatic detection and classification of the adventitious lung sounds are surveyed. It’s a crunchy, scratchy sound, and it happens in time. Ubiquity of smartphones and widespread use of the corresponding applications make such a device an attractive platform for hosting the detection and classification systems for adventitious lung sounds. This sound, also called Hamman’s sign, tells your doctor that air is trapped in the space between your lungs (called the mediastinum). For claims with a date of service on or after October 1, 2015, use an equivalent ICD-10-CM code (or codes). These may be easily audible or identified through auscultation of the respiratory system through the lung fields with a stethoscope as well as from the spectral characteristics of lung sounds. ICD-9-CM 786.9 is a billable medical code that can be used to indicate a diagnosis on a reimbursement claim, however, 786.9 should only be used for claims with a date of service on or before September 30, 2015. Such systems can be presented as different platforms like medical devices, standalone software or smartphone application. Respiratory sounds, also known as lung sounds or breath sounds, refer to the specific sounds generated by the movement of air through the respiratory system. Detection and classification of adventitious acoustic lung sounds plays an important role in diagnosing, monitoring, controlling and, caring the patients with lung diseases.
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