{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T17:10:31Z","timestamp":1763226631480,"version":"build-2065373602"},"reference-count":23,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2018,11,3]],"date-time":"2018-11-03T00:00:00Z","timestamp":1541203200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key R&amp;D Program of China \u201cThe study on Load-bearing and Moving Support Exoskeleton Robot Key Technology and Typical Application\u201d","award":["2017YFB1300500"],"award-info":[{"award-number":["2017YFB1300500"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>A new approach is proposed to detect the real-time gait patterns adaptively through measuring the ground contact forces (GCFs) by force sensitive resistors (FSRs). Published threshold-based methods detect the gait patterns by means of setting a fixed threshold to divide the GCFs into on-ground and off-ground statuses. However, the threshold-based methods in the literature are neither an adaptive nor a real-time approach. To overcome these drawbacks, this study utilized the constant false alarm rate (CFAR) to analyze the characteristics of GCF signals. Specifically, a sliding window detector is built to record the lasting time of the curvature of the GCF signals and one complete gait cycle could be divided into three areas, such as continuous ascending area, continuous descending area and unstable area. Then, the GCF values in the unstable area are used to compute a threshold through the CFAR. Finally, the new gait pattern detection rules are proposed which include the results of the sliding window detector and the division results through the computed threshold. To verify this idea, a data acquisition board is designed to collect the GCF data from able-bodied subjects. Meanwhile, in order to test the reliability of the proposed method, five threshold-based methods in the literature are introduced as reference methods and the reliability is validated by comparing the detection results of the proposed method with those of the reference methods. Experimental results indicated that the proposed method could be used for real-time gait pattern detection, detect the gait patterns adaptively and obtain high reliabilities compared with the reference methods.<\/jats:p>","DOI":"10.3390\/s18113764","type":"journal-article","created":{"date-parts":[[2018,11,5]],"date-time":"2018-11-05T10:43:45Z","timestamp":1541414625000},"page":"3764","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Adjustable Method for Real-Time Gait Pattern Detection Based on Ground Reaction Forces Using Force Sensitive Resistors and Statistical Analysis of Constant False Alarm Rate"],"prefix":"10.3390","volume":"18","author":[{"given":"Fangli","family":"Yu","sequence":"first","affiliation":[{"name":"School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianbin","family":"Zheng","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lie","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Electronic and Electrical Engineering, Wuhan Textile University, Hongshan District, Wuhan 430073, China"},{"name":"Hubei Key Laboratory of Biomass Fibers and Eco-dyeing &amp; Finishing, Wuhan Textile University, Wuhan 430200, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rui","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hailin","family":"He","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhenbo","family":"Zhu","sequence":"additional","affiliation":[{"name":"AirForce Early Warning Academy, Wuhan 430000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0251-5959","authenticated-orcid":false,"given":"Yuanpeng","family":"Zhang","sequence":"additional","affiliation":[{"name":"AirForce Early Warning Academy, Wuhan 430000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,11,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"358","DOI":"10.1109\/TMECH.2008.2008803","article-title":"A Gait Monitoring System Based on Air Pressure Sensors Embedded in a Shoe","volume":"14","author":"Kong","year":"2009","journal-title":"IEEE\/ASME Trans. 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