{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T00:04:47Z","timestamp":1776297887270,"version":"3.50.1"},"reference-count":45,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2021,4,19]],"date-time":"2021-04-19T00:00:00Z","timestamp":1618790400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100010665","name":"H2020 Marie Sk\u0142odowska-Curie Actions","doi-asserted-by":"publisher","award":["764977"],"award-info":[{"award-number":["764977"]}],"id":[{"id":"10.13039\/100010665","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The deterioration of gait can be used as a biomarker for ageing and neurological diseases. Continuous gait monitoring and analysis are essential for early deficit detection and personalized rehabilitation. The use of mobile and wearable inertial sensor systems for gait monitoring and analysis have been well explored with promising results in the literature. However, most of these studies focus on technologies for the assessment of gait characteristics, few of them have considered the data acquisition bandwidth of the sensing system. Inadequate sampling frequency will sacrifice signal fidelity, thus leading to an inaccurate estimation especially for spatial gait parameters. In this work, we developed an inertial sensor based in-shoe gait analysis system for real-time gait monitoring and investigated the optimal sampling frequency to capture all the information on walking patterns. An exploratory validation study was performed using an optical motion capture system on four healthy adult subjects, where each person underwent five walking sessions, giving a total of 20 sessions. Percentage mean absolute errors (MAE%) obtained in stride time, stride length, stride velocity, and cadence while walking were 1.19%, 1.68%, 2.08%, and 1.23%, respectively. In addition, an eigenanalysis based graphical descriptor from raw gait cycle signals was proposed as a new gait metric that can be quantified by principal component analysis to differentiate gait patterns, which has great potential to be used as a powerful analytical tool for gait disorder diagnostics.<\/jats:p>","DOI":"10.3390\/s21082869","type":"journal-article","created":{"date-parts":[[2021,4,19]],"date-time":"2021-04-19T21:59:49Z","timestamp":1618869589000},"page":"2869","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["An Intelligent In-Shoe System for Gait Monitoring and Analysis with Optimized Sampling and Real-Time Visualization Capabilities"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5020-873X","authenticated-orcid":false,"given":"Jiaen","family":"Wu","sequence":"first","affiliation":[{"name":"Institute of Robotics and Intelligent Systems, ETH Zurich, 8092 Zurich, Switzerland"},{"name":"Magnes AG, Selnaustrasse 5, 8001 Zurich, Switzerland"}]},{"given":"Kiran","family":"Kuruvithadam","sequence":"additional","affiliation":[{"name":"Institute of Robotics and Intelligent Systems, ETH Zurich, 8092 Zurich, Switzerland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9865-9185","authenticated-orcid":false,"given":"Alessandro","family":"Schaer","sequence":"additional","affiliation":[{"name":"Magnes AG, Selnaustrasse 5, 8001 Zurich, Switzerland"}]},{"given":"Richie","family":"Stoneham","sequence":"additional","affiliation":[{"name":"Department of Sport, Exercise and Rehabilitation, Northumbria University, Newcastle upon Tyne NE1 8ST, UK"}]},{"given":"George","family":"Chatzipirpiridis","sequence":"additional","affiliation":[{"name":"Magnes AG, Selnaustrasse 5, 8001 Zurich, Switzerland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3602-7841","authenticated-orcid":false,"given":"Chris Awai","family":"Easthope","sequence":"additional","affiliation":[{"name":"Cereneo Foundation, Center for Interdisciplinary Research (CEFIR), 6354 Vitznau, Switzerland"}]},{"given":"Gill","family":"Barry","sequence":"additional","affiliation":[{"name":"Department of Sport, Exercise and Rehabilitation, Northumbria University, Newcastle upon Tyne NE1 8ST, UK"}]},{"given":"James","family":"Martin","sequence":"additional","affiliation":[{"name":"Department of Mechanical and Construction Engineering, Northumbria University, Newcastle upon Tyne NE1 8ST, UK"}]},{"given":"Salvador","family":"Pan\u00e9","sequence":"additional","affiliation":[{"name":"Institute of Robotics and Intelligent Systems, ETH Zurich, 8092 Zurich, Switzerland"}]},{"given":"Bradley J.","family":"Nelson","sequence":"additional","affiliation":[{"name":"Institute of Robotics and Intelligent Systems, ETH Zurich, 8092 Zurich, Switzerland"}]},{"given":"Olga\u00e7","family":"Ergeneman","sequence":"additional","affiliation":[{"name":"Magnes AG, Selnaustrasse 5, 8001 Zurich, Switzerland"}]},{"given":"Hamdi","family":"Torun","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Physics and Electrical Engineering, Northumbria University, Newcastle upon Tyne NE1 8ST, UK"}]}],"member":"1968","published-online":{"date-parts":[[2021,4,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"443","DOI":"10.3390\/s140100443","article-title":"Gait and Foot Clearance Parameters Obtained Using Shoe-Worn Inertial Sensors in a Large-Population Sample of Older Adults","volume":"14","author":"Dadashi","year":"2014","journal-title":"Sensors"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Abu-Faraj, Z.O., Harris, G.F., Smith, P.A., and Hassani, S. 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