{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T20:17:58Z","timestamp":1778876278045,"version":"3.51.4"},"reference-count":48,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2014,7,30]],"date-time":"2014-07-30T00:00:00Z","timestamp":1406678400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Tracheal sounds have received a lot of attention for estimating ventilation parameters in a non-invasive way. The aim of this work was to examine the feasibility of extracting accurate airflow, and automating the detection of breath-phase onset and respiratory rates all directly from tracheal sounds acquired from an acoustic microphone connected to a smartphone. We employed the Samsung Galaxy S4 and iPhone 4s smartphones to acquire tracheal sounds from N = 9 healthy volunteers at airflows ranging from 0.5 to 2.5 L\/s. We found that the amplitude of the smartphone-acquired sounds was highly correlated with the airflow from a spirometer, and similar to previously-published studies, we found that the increasing tracheal sounds\u2019 amplitude as flow increases follows a power law relationship. Acquired tracheal sounds were used for breath-phase onset detection and their onsets differed by only 52 \u00b1 51 ms (mean \u00b1 SD) for Galaxy S4, and  51 \u00b1 48 ms for iPhone 4s, when compared to those detected from the reference signal via the spirometer. Moreover, it was found that accurate respiratory rates (RR) can be obtained from tracheal sounds. The correlation index, bias and limits of agreement were r2 = 0.9693, 0.11 (\u22121.41 to 1.63) breaths-per-minute (bpm) for Galaxy S4, and r2 = 0.9672,  0.097 (\u20131.38 to 1.57) bpm for iPhone 4s, when compared to RR estimated from spirometry. Both smartphone devices performed similarly, as no statistically-significant differences were found.<\/jats:p>","DOI":"10.3390\/s140813830","type":"journal-article","created":{"date-parts":[[2014,7,30]],"date-time":"2014-07-30T09:19:07Z","timestamp":1406711947000},"page":"13830-13850","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":41,"title":["Tracheal Sounds Acquisition Using Smartphones"],"prefix":"10.3390","volume":"14","author":[{"given":"Bersain","family":"Reyes","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering, Worcester Polytechnic Institute, 100 Institute Road, Worcester, MA 01609, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Natasa","family":"Reljin","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, Worcester Polytechnic Institute, 100 Institute Road, Worcester, MA 01609, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ki","family":"Chon","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, Worcester Polytechnic Institute, 100 Institute Road, Worcester, MA 01609, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2014,7,30]]},"reference":[{"key":"ref_1","first-page":"597","article-title":"Definition of terms for applications of respiratory sounds","volume":"10","author":"Sovijarvi","year":"2000","journal-title":"Eur. 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