{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,22]],"date-time":"2026-01-22T17:45:41Z","timestamp":1769103941921,"version":"3.49.0"},"reference-count":45,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2018,12,27]],"date-time":"2018-12-27T00:00:00Z","timestamp":1545868800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Breathing frequency (fB) is an important vital sign that\u2014if appropriately monitored\u2014may help to predict clinical adverse events. Inertial sensors open the door to the development of low-cost, wearable, and easy-to-use breathing-monitoring systems. The present paper proposes a new posture-independent processing algorithm for breath-by-breath extraction of breathing temporal parameters from chest-wall inclination change signals measured using inertial measurement units. An important step of the processing algorithm is dimension reduction (DR) that allows the extraction of a single respiratory signal starting from 4-component quaternion data. Three different DR methods are proposed and compared in terms of accuracy of breathing temporal parameter estimation, in a group of healthy subjects, considering different breathing patterns and different postures; optoelectronic plethysmography was used as reference system. In this study, we found that the method based on PCA-fusion of the four quaternion components provided the best fB estimation performance in terms of mean absolute errors (&lt;2 breaths\/min), correlation (r &gt; 0.963) and Bland\u2013Altman Analysis, outperforming the other two methods, based on the selection of a single quaternion component, identified on the basis of spectral analysis; particularly, in supine position, results provided by PCA-based method were even better than those obtained with the ideal quaternion component, determined a posteriori as the one providing the minimum estimation error. The proposed algorithm and system were able to successfully reconstruct the respiration-induced movement, and to accurately determine the respiratory rate in an automatic, position-independent manner.<\/jats:p>","DOI":"10.3390\/s19010088","type":"journal-article","created":{"date-parts":[[2018,12,27]],"date-time":"2018-12-27T11:29:43Z","timestamp":1545910183000},"page":"88","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":54,"title":["Assessment of Breathing Parameters Using an Inertial Measurement Unit (IMU)-Based System"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4334-7488","authenticated-orcid":false,"given":"Ambra","family":"Cesareo","sequence":"first","affiliation":[{"name":"Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milan, Italy"}]},{"given":"Ylenia","family":"Previtali","sequence":"additional","affiliation":[{"name":"Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milan, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2568-9735","authenticated-orcid":false,"given":"Emilia","family":"Biffi","sequence":"additional","affiliation":[{"name":"Scientific Institute, IRCCS E. Medea, Bioengineering Lab, 23842 Bosisio Parini, Lecco, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2950-0231","authenticated-orcid":false,"given":"Andrea","family":"Aliverti","sequence":"additional","affiliation":[{"name":"Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milan, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2018,12,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"797","DOI":"10.1046\/j.1365-2044.2003.03258.x","article-title":"Effect of Introducing the Modified Early Warning Score on Clinical Outcomes, cardio-pulmonary Arrests and Intensive Care Utilisation in Acute Medical Admissions","volume":"58","author":"Subbe","year":"2003","journal-title":"Anaesthesia"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"657","DOI":"10.5694\/j.1326-5377.2008.tb01825.x","article-title":"Respiratory Rate: The Neglected Vital Sign","volume":"188","author":"Cretikos","year":"2008","journal-title":"Med. 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