{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T04:34:30Z","timestamp":1777523670424,"version":"3.51.4"},"reference-count":39,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2019,12,3]],"date-time":"2019-12-03T00:00:00Z","timestamp":1575331200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000038","name":"Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"publisher","award":["Natural Sciences and Engineering Research Council"],"award-info":[{"award-number":["Natural Sciences and Engineering Research Council"]}],"id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000024","name":"Canadian Institutes of Health Research","doi-asserted-by":"publisher","award":["Canadian Institutes of Health Research"],"award-info":[{"award-number":["Canadian Institutes of Health Research"]}],"id":[{"id":"10.13039\/501100000024","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001804","name":"Canada Research Chairs","doi-asserted-by":"publisher","award":["Canada Research Chairs Program"],"award-info":[{"award-number":["Canada Research Chairs Program"]}],"id":[{"id":"10.13039\/501100001804","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Continuous kinematic monitoring of runners is crucial to inform runners of inappropriate running habits. Motion capture systems are the gold standard for gait analysis, but they are spatially limited to laboratories. Recently, wearable sensors have gained attention as an unobtrusive method to analyze performance metrics and the health conditions of runners. In this study, we developed a system capable of estimating joint angles in sagittal, frontal, and transverse planes during running. A prototype with fiber strain sensors was fabricated. The positions of the sensors on the pelvis were optimized using a genetic algorithm. A cohort of ten people completed 15 min of running at five different speeds for gait analysis by our prototype device. The joint angles were estimated by a deep convolutional neural network in inter- and intra-participant scenarios. In intra-participant tests, root mean square error (RMSE) and normalized root mean square error (NRMSE) of less than 2.2\u00b0 and 5.3%, respectively, were obtained for hip, knee, and ankle joints in sagittal, frontal, and transverse planes. The RMSE and NRMSE in inter-participant tests were less than 6.4\u00b0 and 10%, respectively, in the sagittal plane. The accuracy of this device and methodology could yield potential applications as a soft wearable device for gait monitoring of runners.<\/jats:p>","DOI":"10.3390\/s19235325","type":"journal-article","created":{"date-parts":[[2019,12,4]],"date-time":"2019-12-04T04:30:35Z","timestamp":1575433835000},"page":"5325","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":47,"title":["Lower Body Kinematics Monitoring in Running Using Fabric-Based Wearable Sensors and Deep Convolutional Neural Networks"],"prefix":"10.3390","volume":"19","author":[{"given":"Mohsen","family":"Gholami","sequence":"first","affiliation":[{"name":"Menrva Research Group, Schools of Mechatronic Systems Engineering &amp; Engineering Science, Simon Fraser University, Metro Vancouver, BC V5A 1S6, Canada"}]},{"given":"Ahmad","family":"Rezaei","sequence":"additional","affiliation":[{"name":"Menrva Research Group, Schools of Mechatronic Systems Engineering &amp; Engineering Science, Simon Fraser University, Metro Vancouver, BC V5A 1S6, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0313-3557","authenticated-orcid":false,"given":"Tyler J.","family":"Cuthbert","sequence":"additional","affiliation":[{"name":"Menrva Research Group, Schools of Mechatronic Systems Engineering &amp; Engineering Science, Simon Fraser University, Metro Vancouver, BC V5A 1S6, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1454-3546","authenticated-orcid":false,"given":"Christopher","family":"Napier","sequence":"additional","affiliation":[{"name":"Menrva Research Group, Schools of Mechatronic Systems Engineering &amp; Engineering Science, Simon Fraser University, Metro Vancouver, BC V5A 1S6, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2309-9977","authenticated-orcid":false,"given":"Carlo","family":"Menon","sequence":"additional","affiliation":[{"name":"Menrva Research Group, Schools of Mechatronic Systems Engineering &amp; Engineering Science, Simon Fraser University, Metro Vancouver, BC V5A 1S6, Canada"}]}],"member":"1968","published-online":{"date-parts":[[2019,12,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1412","DOI":"10.1249\/MSS.0000000000001245","article-title":"Running Technique is an Important Component of Running Economy and Performance","volume":"49","author":"Folland","year":"2017","journal-title":"Med. 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