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This study designs a low\u2010cost gait detection system with high accuracy and reliability that is an alternative method\/equipment in the gait detection field to the most widely used commercial system, the virtual user concept (Vicon) system. The proposed system integrates mass\u2010produced low\u2010cost sensors\/chips in a compact size to collect kinematic data. Furthermore, an x86 mini personal computer (PC) running at 100\u2009Hz classifies motion data in real\u2010time. To guarantee gait detection accuracy, the embedded gait detection algorithm adopts a multilayer perceptron (MLP) model and a rule\u2010based calibration filter to classify kinematic data into five distinct gait events: heel\u2010strike, foot\u2010flat, heel\u2010off, toe\u2010off, and initial\u2010swing. To evaluate performance, volunteers are requested to walk on the treadmill at a regular walking speed of 4.2\u2009km\/h while kinematic data are recorded by a low\u2010cost system and a Vicon system simultaneously. The gait detection accuracy and relative time error are estimated by comparing the classified gait events in the study with the Vicon system as a reference. The results show that the proposed system obtains a high accuracy of 99.66% with a smaller time error (32\u2009ms), demonstrating that it performs similarly to the Vicon system in the gait detection field.<\/jats:p>","DOI":"10.1155\/2021\/6378514","type":"journal-article","created":{"date-parts":[[2021,8,14]],"date-time":"2021-08-14T17:35:19Z","timestamp":1628962519000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Low\u2010Cost Multisensor Integrated System for Online Walking Gait Detection"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9986-2182","authenticated-orcid":false,"given":"Lingyun","family":"Yan","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2613-902X","authenticated-orcid":false,"given":"Guowu","family":"Wei","sequence":"additional","affiliation":[]},{"given":"Zheqi","family":"Hu","sequence":"additional","affiliation":[]},{"given":"Haohua","family":"Xiu","sequence":"additional","affiliation":[]},{"given":"Yuyang","family":"Wei","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3222-2102","authenticated-orcid":false,"given":"Lei","family":"Ren","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2021,8,14]]},"reference":[{"key":"e_1_2_10_1_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuropsychologia.2010.05.022"},{"key":"e_1_2_10_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.gaitpost.2018.07.165"},{"key":"e_1_2_10_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2017.04.006"},{"key":"e_1_2_10_4_2","doi-asserted-by":"publisher","DOI":"10.1109\/JSEN.2018.2866802"},{"key":"e_1_2_10_5_2","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2019.2900121"},{"key":"e_1_2_10_6_2","doi-asserted-by":"publisher","DOI":"10.1109\/tmech.2019.2961567"},{"key":"e_1_2_10_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.gaitpost.2011.02.012"},{"key":"e_1_2_10_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.gaitpost.2004.12.002"},{"key":"e_1_2_10_9_2","doi-asserted-by":"publisher","DOI":"10.1093\/tse\/tdz007"},{"key":"e_1_2_10_10_2","unstructured":"OttE. 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