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Gait analysis is a critical step in the diagnosis and rehabilitation of these disorders. Specifically, step and stride lengths provide valuable insights into the gait quality and rehabilitation process. However, traditional approaches for estimating step length are not suitable for continuous daily monitoring since they rely on special mats and clinical environments. To address this limitation, this article presents a novel and practical step-length estimation technique using low-power wearable bend and inertial sensors. Experimental results show that the proposed model estimates step length with 5.49% mean absolute percentage error and provides accurate real-time feedback to the user.<\/jats:p>","DOI":"10.1145\/3485434","type":"journal-article","created":{"date-parts":[[2021,10,27]],"date-time":"2021-10-27T17:26:03Z","timestamp":1635355563000},"page":"1-24","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":20,"title":["<i>MGait<\/i>\n            : Model-Based Gait Analysis Using Wearable Bend and Inertial Sensors"],"prefix":"10.1145","volume":"3","author":[{"given":"Sizhe","family":"An","sequence":"first","affiliation":[{"name":"University of Wisconsin-Madison, Madison, Wisconsin, USA"}]},{"given":"Yigit","family":"Tuncel","sequence":"additional","affiliation":[{"name":"University of Wisconsin-Madison, Madison, Wisconsin, USA"}]},{"given":"Toygun","family":"Basaklar","sequence":"additional","affiliation":[{"name":"University of Wisconsin-Madison, Madison, Wisconsin, USA"}]},{"given":"Gokul K.","family":"Krishnakumar","sequence":"additional","affiliation":[{"name":"Arizona State University, Tempe, Arizona, USA"}]},{"given":"Ganapati","family":"Bhat","sequence":"additional","affiliation":[{"name":"Washington State University, Pullman, Washington, USA"}]},{"given":"Umit Y.","family":"Ogras","sequence":"additional","affiliation":[{"name":"University of Wisconsin-Madison, Madison, Wisconsin, USA"}]}],"member":"320","published-online":{"date-parts":[[2021,10,27]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"crossref","first-page":"188","DOI":"10.1109\/PERCOMW.2017.7917555","volume-title":"2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops\u201917)","author":"Alzantot Moustafa","year":"2017","unstructured":"Moustafa Alzantot, Supriyo Chakraborty, and Mani Srivastava. 2017. 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