Automatic Classification of Adventitious Respiratory Sounds: A (Un)Solved Problem?
نویسندگان
چکیده
منابع مشابه
Detection of Adventitious Respiratory Sounds Using Empirical Mode Decomposition
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 and frequency response of the human ear...
متن کاملAutomatic adventitious respiratory sound analysis: A systematic review
BACKGROUND Automatic detection or classification of adventitious sounds is useful to assist physicians in diagnosing or monitoring diseases such as asthma, Chronic Obstructive Pulmonary Disease (COPD), and pneumonia. While computerised respiratory sound analysis, specifically for the detection or classification of adventitious sounds, has recently been the focus of an increasing number of studi...
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INTRODUCTION There is a need to develop simple, noninvasive, and sensitive outcome measures for respiratory therapy. Adventitious respiratory sounds (ie, crackles and wheezes) can be objectively characterized with computerized respiratory sound analysis (CORSA) and have been shown to contribute for diagnosis purposes; however, their potential for use as outcome measures is unknown. Thus, this s...
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Convenient searching of multimedia databases requires well annotated data. Labeling sound data with information like pitch or timbre must be done through sound analysis. In this paper, we deal with the problem of automatic classification of musical instrument on the basis of its sound. Although there are algorithms for basic sound descriptors extraction, correct identification of instrument sti...
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In this paper, a classification scheme has been proposed to classify crackles based on waveform features and frequency domain features. This purpose is very important in the analysis of respiratory disorders. In fact, morphological characters of crackles can be well represented by time amplitude distribution. Thus, they convey significant diagnostic information, for their precise timing in the ...
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ژورنال
عنوان ژورنال: Sensors
سال: 2020
ISSN: 1424-8220
DOI: 10.3390/s21010057