{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:47:56Z","timestamp":1760150876815,"version":"build-2065373602"},"reference-count":36,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2022,2,1]],"date-time":"2022-02-01T00:00:00Z","timestamp":1643673600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004837","name":"Ministerio de Ciencia e Innovaci\u00f3n","doi-asserted-by":"publisher","award":["PID2020-113614RB-C22"],"award-info":[{"award-number":["PID2020-113614RB-C22"]}],"id":[{"id":"10.13039\/501100004837","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Spirometers are important devices for following up patients with respiratory diseases. These are mainly located only at hospitals, with all the disadvantages that this can entail. This limits their use and consequently, the supervision of patients. Research efforts focus on providing digital alternatives to spirometers. Although less accurate, the authors claim they are cheaper and usable by many more people worldwide at any given time and place. In order to further popularize the use of spirometers even more, we are interested in also providing user-friendly lung-capacity metrics instead of the traditional-spirometry ones. The main objective, which is also the main contribution of this research, is to obtain a person\u2019s lung age by analyzing the properties of their exhalation by means of a machine-learning method. To perform this study, 188 samples of blowing sounds were used. These were taken from 91 males (48.4%) and 97 females (51.6%) aged between 17 and 67. A total of 42 spirometer and frequency-like features, including gender, were used. Traditional machine-learning algorithms used in voice recognition applied to the most significant features were used. We found that the best classification algorithm was the Quadratic Linear Discriminant algorithm when no distinction was made between gender. By splitting the corpus into age groups of 5 consecutive years, accuracy, sensitivity and specificity of, respectively, 94.69%, 94.45% and 99.45% were found. Features in the audio of users\u2019 expiration that allowed them to be classified by their corresponding lung age group of 5 years were successfully detected. Our methodology can become a reliable tool for use with mobile devices to detect lung abnormalities or diseases.<\/jats:p>","DOI":"10.3390\/s22031106","type":"journal-article","created":{"date-parts":[[2022,2,1]],"date-time":"2022-02-01T22:16:18Z","timestamp":1643753778000},"page":"1106","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["A Machine-Learning Model for Lung Age Forecasting by Analyzing Exhalations"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0079-3675","authenticated-orcid":false,"given":"Marc","family":"Pifarr\u00e9","sequence":"first","affiliation":[{"name":"Department of Computer Science & INSPIRES, University of Lleida, Jaume II 69, 25001 Lleida, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3999-5549","authenticated-orcid":false,"given":"Alberto","family":"Tena","sequence":"additional","affiliation":[{"name":"CIMNE, Building C1, North Campus, UPC, Gran Capit\u00e0, 08034 Barcelona, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7586-0652","authenticated-orcid":false,"given":"Francisco","family":"Clari\u00e0","sequence":"additional","affiliation":[{"name":"Department of Computer Science & INSPIRES, University of Lleida, Jaume II 69, 25001 Lleida, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4830-9184","authenticated-orcid":false,"given":"Francesc","family":"Solsona","sequence":"additional","affiliation":[{"name":"Department of Computer Science & INSPIRES, University of Lleida, Jaume II 69, 25001 Lleida, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8188-4914","authenticated-orcid":false,"given":"Jordi","family":"Vilaplana","sequence":"additional","affiliation":[{"name":"Department of Computer Science & INSPIRES, University of Lleida, Jaume II 69, 25001 Lleida, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Arnau","family":"Benavides","sequence":"additional","affiliation":[{"name":"Department of Computer Science & INSPIRES, University of Lleida, Jaume II 69, 25001 Lleida, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9163-5364","authenticated-orcid":false,"given":"Lluis","family":"Mas","sequence":"additional","affiliation":[{"name":"Department of Computer Science & INSPIRES, University of Lleida, Jaume II 69, 25001 Lleida, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Francesc","family":"Abella","sequence":"additional","affiliation":[{"name":"IRBLleida, Avda Alcalde Rovira Roure 80, 25198 Lleida, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,2,1]]},"reference":[{"key":"ref_1","unstructured":"World Health Organization (WHO) (2020, December 09). 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