{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,19]],"date-time":"2026-04-19T19:57:27Z","timestamp":1776628647497,"version":"3.51.2"},"reference-count":44,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2022,3,11]],"date-time":"2022-03-11T00:00:00Z","timestamp":1646956800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004070","name":"Khalifa University of Science and Technology","doi-asserted-by":"publisher","award":["8474000316\u2014CPRA\u2014Ventilator (Stefanini)"],"award-info":[{"award-number":["8474000316\u2014CPRA\u2014Ventilator (Stefanini)"]}],"id":[{"id":"10.13039\/501100004070","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This study aimed to explore novel inertial measurement unit (IMU)-based strategies to estimate respiratory parameters in healthy adults lying on a bed while breathing normally. During the experimental sessions, the kinematics of the chest wall were contemporaneously collected through both a network of 9 IMUs and a set of 45 uniformly distributed reflective markers. All inertial kinematics were analyzed to identify a minimum set of signals and IMUs whose linear combination best matched the tidal volume measured by optoelectronic plethysmography. The resulting models were finally tuned and validated through a leave-one-out cross-validation approach to assess the extent to which they could accurately estimate a set of respiratory parameters related to three trunk compartments. The adopted methodological approach allowed us to identify two different models. The first, referred to as Model 1, relies on the 3D acceleration measured by three IMUs located on the abdominal compartment and on the lower costal margin. The second, referred to as Model 2, relies on only one component of the acceleration measured by two IMUs located on the abdominal compartment. Both models can accurately estimate the respiratory rate (relative error &lt; 1.5%). Conversely, the duration of the respiratory phases and the tidal volume can be more accurately assessed by Model 2 (relative error &lt; 5%) and Model 1 (relative error &lt; 5%), respectively. We further discuss possible approaches to overcome limitations and improve the overall accuracy of the proposed approach.<\/jats:p>","DOI":"10.3390\/s22062185","type":"journal-article","created":{"date-parts":[[2022,3,13]],"date-time":"2022-03-13T21:44:17Z","timestamp":1647207857000},"page":"2185","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Assessing Respiratory Activity by Using IMUs: Modeling and Validation"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1210-7553","authenticated-orcid":false,"given":"Vito","family":"Monaco","sequence":"first","affiliation":[{"name":"The Biorobotics Institute and the Department of Excellence in Robotics and AI, Scuola Superiore Sant\u2019Anna, 56127 Pisa, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Carolina","family":"Giustinoni","sequence":"additional","affiliation":[{"name":"Scuola di Ingegneria, Universit\u00e0 di Pisa, 56126 Pisa, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7442-4426","authenticated-orcid":false,"given":"Tommaso","family":"Ciapetti","sequence":"additional","affiliation":[{"name":"IRCCS Fondazione Don Carlo Gnocchi, 20148 Milan, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4542-7385","authenticated-orcid":false,"given":"Alessandro","family":"Maselli","sequence":"additional","affiliation":[{"name":"IRCCS Fondazione Don Carlo Gnocchi, 20148 Milan, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cesare","family":"Stefanini","sequence":"additional","affiliation":[{"name":"The Biorobotics Institute and the Department of Excellence in Robotics and AI, Scuola Superiore Sant\u2019Anna, 56127 Pisa, Italy"},{"name":"Healthcare Engineering Innovation Center (HEIC), Khalifa University, Abu Dhabi P.O. Box 127788, United Arab Emirates"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,3,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"112460","DOI":"10.1016\/j.bios.2020.112460","article-title":"Stretchable respiration sensors: Advanced designs and multifunctional platforms for wearable physiological monitoring","volume":"166","author":"Dinh","year":"2020","journal-title":"Biosens. Bioelectron."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Liu, J., Liu, M., Bai, Y., Zhang, J., Liu, H., and Zhu, W. (2020). Recent Progress in Flexible Wearable Sensors for Vital Sign Monitoring. 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