{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T15:17:43Z","timestamp":1785424663807,"version":"3.56.0"},"reference-count":13,"publisher":"ASME International","issue":"11","license":[{"start":{"date-parts":[[2024,7,1]],"date-time":"2024-07-01T00:00:00Z","timestamp":1719792000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.asme.org\/publications-submissions\/publishing-information\/legal-policies"}],"funder":[{"DOI":"10.13039\/100000090","name":"Congressionally Directed Medical Research Programs","doi-asserted-by":"publisher","award":["W81XWH2010884"],"award-info":[{"award-number":["W81XWH2010884"]}],"id":[{"id":"10.13039\/100000090","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000082","name":"Division of Graduate Education","doi-asserted-by":"publisher","award":["1747503"],"award-info":[{"award-number":["1747503"]}],"id":[{"id":"10.13039\/100000082","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["asmedigitalcollection.asme.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,11,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>This research introduces an adaptive control algorithm designed to determine gait phase in real-time using an inertial measurement unit (IMU) affixed to the shank. Focusing on detecting specific gait events, primarily initial contact (IC) and toe-off (TO), the algorithm utilizes dynamic thresholds and ratios that facilitate accurate event determination adaptively across a range of walking speeds. Built-in safety checks further ensure precision and minimize false detections. We validated the algorithm with eight participants walking at varying speeds. The algorithm demonstrated promising results in detecting IC and TO events with mean lead of 8.95\u2009ms and 4.42\u2009ms and detection success rate of 100% and 99.72%, respectively. These results are consistent with benchmarks from established algorithms (Hanlon and Anderson, 2009, \u201cReal-Time Gait Event Detection Using Wearable Sensors,\u201d Gait Posture, 30(4), pp. 523\u2013527; Maqbool et al., 2017, \u201cA Real-Time Gait Event Detection for Lower Limb Prosthesis Control and Evaluation,\u201d IEEE Trans. Neural Syst. Rehabil. Eng.: Publ. IEEE Eng. Med. Biol. Soc., 25(9), pp. 1500\u20131509). Moreover, the algorithm's self-adaptive nature ensures it can be used in scenarios of varying movement, offering a promising solution for real-time gait phase detection.<\/jats:p>","DOI":"10.1115\/1.4065842","type":"journal-article","created":{"date-parts":[[2024,7,1]],"date-time":"2024-07-01T11:54:16Z","timestamp":1719834856000},"update-policy":"https:\/\/doi.org\/10.1115\/crossmarkpolicy-asme","source":"Crossref","is-referenced-by-count":3,"title":["Detecting Toe-Off and Initial Contact in Real-Time With Self-Adapting Thresholds"],"prefix":"10.1115","volume":"146","author":[{"given":"Sofya M.","family":"Akhetova","sequence":"first","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of Wisconsin\u2013Madison , Engineering Hall, 2415, 1415 Engineering Drive, Madison, WI 53706"},{"id":[{"id":"https:\/\/ror.org\/01y2jtd41","id-type":"ROR","asserted-by":"publisher"}],"name":"University of Wisconsin-Madison"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rebecca","family":"Roembke","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, University of Wisconsin\u2013Madison , Mechanical Engineering Building, 2107, 1513 University Avenue, Madison, WI 53706"},{"id":[{"id":"https:\/\/ror.org\/01y2jtd41","id-type":"ROR","asserted-by":"publisher"}],"name":"University of Wisconsin-Madison"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peter","family":"Adamczyk","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of Wisconsin\u2013Madison , Engineering Hall, 2415, 1415 Engineering Drive, Madison, WI 53706 ; , Mechanical Engineering Building, 2107, 1513 University Avenue, Madison, WI 53706"},{"name":"Department of Mechanical Engineering, University of Wisconsin\u2013Madison , Engineering Hall, 2415, 1415 Engineering Drive, Madison, WI 53706 ; , Mechanical Engineering Building, 2107, 1513 University Avenue, Madison, WI 53706"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"33","published-online":{"date-parts":[[2024,7,16]]},"reference":[{"issue":"4","key":"2025071520023344600_bib1","doi-asserted-by":"crossref","first-page":"523","DOI":"10.1016\/j.gaitpost.2009.07.128","article-title":"Real-Time Gait Event Detection Using Wearable Sensors","volume":"30","year":"2009","journal-title":"Gait Posture"},{"issue":"1","key":"2025071520023344600_bib2","doi-asserted-by":"crossref","first-page":"66","DOI":"10.3390\/s16010066","article-title":"Gait Partitioning Methods: A Systematic Review","volume":"16","year":"2016","journal-title":"Sensors"},{"issue":"2","key":"2025071520023344600_bib3","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1016\/S1350-4533(99)00030-2","article-title":"A Practical Gait Analysis System Using Gyroscopes","volume":"21","year":"1999","journal-title":"Med. 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