{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T20:40:14Z","timestamp":1773693614571,"version":"3.50.1"},"reference-count":57,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2020,12,24]],"date-time":"2020-12-24T00:00:00Z","timestamp":1608768000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001871","name":"Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia","doi-asserted-by":"publisher","award":["SFRH\/BD\/135686\/2018"],"award-info":[{"award-number":["SFRH\/BD\/135686\/2018"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008530","name":"European Regional Development Fund","doi-asserted-by":"publisher","award":["UID\/BIM\/04501\/2013"],"award-info":[{"award-number":["UID\/BIM\/04501\/2013"]}],"id":[{"id":"10.13039\/501100008530","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008530","name":"European Regional Development Fund","doi-asserted-by":"publisher","award":["POCI-01-0145-FEDER-007628\u2014iBiMED"],"award-info":[{"award-number":["POCI-01-0145-FEDER-007628\u2014iBiMED"]}],"id":[{"id":"10.13039\/501100008530","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100010661","name":"Horizon 2020 Framework Programme","doi-asserted-by":"publisher","award":["825572"],"award-info":[{"award-number":["825572"]}],"id":[{"id":"10.13039\/100010661","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>(1) Background: Patients with respiratory conditions typically exhibit adventitious respiratory sounds (ARS), such as wheezes and crackles. ARS events have variable duration. In this work we studied the influence of event duration on automatic ARS classification, namely, how the creation of the Other class (negative class) affected the classifiers\u2019 performance. (2) Methods: We conducted a set of experiments where we varied the durations of the other events on three tasks: crackle vs. wheeze vs. other (3 Class); crackle vs. other (2 Class Crackles); and wheeze vs. other (2 Class Wheezes). Four classifiers (linear discriminant analysis, support vector machines, boosted trees, and convolutional neural networks) were evaluated on those tasks using an open access respiratory sound database. (3) Results: While on the 3 Class task with fixed durations, the best classifier achieved an accuracy of 96.9%, the same classifier reached an accuracy of 81.8% on the more realistic 3 Class task with variable durations. (4) Conclusion: These results demonstrate the importance of experimental design on the assessment of the performance of automatic ARS classification algorithms. Furthermore, they also indicate, unlike what is stated in the literature, that the automatic classification of ARS is not a solved problem, as the algorithms\u2019 performance decreases substantially under complex evaluation scenarios.<\/jats:p>","DOI":"10.3390\/s21010057","type":"journal-article","created":{"date-parts":[[2020,12,24]],"date-time":"2020-12-24T09:02:44Z","timestamp":1608800564000},"page":"57","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":66,"title":["Automatic Classification of Adventitious Respiratory Sounds: A (Un)Solved Problem?"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1643-667X","authenticated-orcid":false,"given":"Bruno Machado","family":"Rocha","sequence":"first","affiliation":[{"name":"University of Coimbra, Centre for Informatics and Systems of the University of Coimbra, Department of Informatics Engineering, 3030-290 Coimbra, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7783-7488","authenticated-orcid":false,"given":"Diogo","family":"Pessoa","sequence":"additional","affiliation":[{"name":"University of Coimbra, Centre for Informatics and Systems of the University of Coimbra, Department of Informatics Engineering, 3030-290 Coimbra, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4980-6200","authenticated-orcid":false,"given":"Alda","family":"Marques","sequence":"additional","affiliation":[{"name":"Lab3R\u2014Respiratory Research and Rehabilitation Laboratory, School of Health Sciences (ESSUA), University of Aveiro, 3810-193 Aveiro, Portugal"},{"name":"Institute of Biomedicine (iBiMED), University of Aveiro, 3810-193 Aveiro, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9847-0590","authenticated-orcid":false,"given":"Paulo","family":"Carvalho","sequence":"additional","affiliation":[{"name":"University of Coimbra, Centre for Informatics and Systems of the University of Coimbra, Department of Informatics Engineering, 3030-290 Coimbra, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3215-3960","authenticated-orcid":false,"given":"Rui Pedro","family":"Paiva","sequence":"additional","affiliation":[{"name":"University of Coimbra, Centre for Informatics and Systems of the University of Coimbra, Department of Informatics Engineering, 3030-290 Coimbra, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2020,12,24]]},"reference":[{"key":"ref_1","unstructured":"(2020, December 10). 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