Automatic adventitious respiratory sound analysis: A systematic review

Abstract

BackgroundAutomatic 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 studies, a standardised approach and comparison has not been well established.ObjectiveTo provide a review of existing algorithms for the detection or classification of adventitious respiratory sounds. This systematic review provides a complete summary of methods used in the literature to give a baseline for future works.Data sourcesA systematic review of English articles published between 1938 and 2016, searched using the Scopus (1938-2016) and IEEExplore (1984-2016) databases. Additional articles were further obtained by references listed in the articles found. Search terms included adventitious sound detection, adventitious sound classification, abnormal respiratory sound detection, abnormal respiratory sound classification, wheeze detection, wheeze classification, crackle detection, crackle classification, rhonchi detection, rhonchi classification, stridor detection, stridor classification, pleural rub detection, pleural rub classification, squawk detection, and squawk classification.Study selectionOnly articles were included that focused on adventitious sound detection or classification, based on respiratory sounds, with performance reported and sufficient information provided to be approximately repeated.Data extractionInvestigators extracted data about the adventitious sound type analysed, approach and level of analysis, instrumentation or data source, location of sensor, amount of data obtained, data management, features, methods, and performance achieved.Data synthesisA total of 77 reports from the literature were included in this review. 55 (71.43%) of the studies focused on wheeze, 40 (51.95%) on crackle, 9 (11.69%) on stridor, 9 (11.69%) on rhonchi, and 18 (23.38%) on other sounds such as pleural rub, squawk, as well as the pathology. Instrumentation used to collect data included microphones, stethoscopes, and accelerometers. Several references obtained data from online repositories or book audio CD companions. Detection or classification methods used varied from empirically determined thresholds to more complex machine learning techniques. Performance reported in the surveyed works were converted to accuracy measures for data synthesis.LimitationsDirect comparison of the performance of surveyed works cannot be performed as the input data used by each was different. A standard validation method has not been established, resulting in different works using different methods and performance measure definitions.ConclusionA review of the literature was performed to summarise different analysis approaches, features, and methods used for the analysis. The performance of recent studies showed a high agreement with conventiona...

The highs and lows of wheezing: A review of the most popular adventitious lung sound

“…The discussion of these studies would expand beyond the scope of this article, and interested readers are therefore directed to recent reviews of respiratory sound analysis. [42][43][44] For the clinician, Another observation that may relate to interregional airflows is the capture of an inspiratory wheeze that continues uninterrupted into expiration ( Figures 6 and 7). The detection of this phenomenon requires simultaneous recording of sound and airflow.…”

“…Over the past four decades, there have been numerous studies of computerized analyzes of wheezing, many with a focus on the engineering aspects of digital signal processing, and methods for pattern analysis and the automated detection of wheezes. The discussion of these studies would expand beyond the scope of this article, and interested readers are therefore directed to recent reviews of respiratory sound analysis . For the clinician, wheeze recording and analysis are of interest because they provide objective documentation and characterization of the adventitious sound, independent of perception and communication by observers.…”

WheezeD: Respiration Phase Based Wheeze Detection Using Acoustic Data From Pulmonary Patients Under Attack

“…Several works have been done to detect wheeze [15]. However, to the best of our knowledge, this work is the first to present a reliable model for respiratory phase based wheezing detection and its application towards assessment of severity of the pulmonary condition.…”

“…This method is non-invasive and simple, however it is heavily dependent on the physical presence of a physician, the experience of the physician, sensitivity and variability of human auditory system [14], presence of noise in the internal or external environment, technical specifications and response efficiency of stethoscopes [4]. The following survey paper summarizes some interesting previous works done on wheezing detection [15]. Few of them attempted at wheezing detection against other adventitious sounds.…”

An audio classification system for detecting pulmonary edema

“…Thus, there has been much research developed to detect DAS found in lung sounds. Recently, Pramono et al [13] presented a systematic review of automatic adventitious respiratory sound analysis. Regarding the analysis of crackles, they cited 36 papers that involve detection or classification and listed their data sources, amount of data, validation method, features used, classification method and performance.…”