{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,16]],"date-time":"2026-10-16T16:43:33Z","timestamp":1792169013646,"version":"4.4.0"},"reference-count":56,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2023,2,10]],"date-time":"2023-02-10T00:00:00Z","timestamp":1675987200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Fonds de recherche du Qu\u00e9bec, programme bilat\u00e9ral de coop\u00e9ration de recherche Qu\u00e9bec-Flandre","award":["#G0E4521N"],"award-info":[{"award-number":["#G0E4521N"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJERPH"],"abstract":"<jats:p>Inertial measurement units (IMUs) have shown promising outcomes for estimating gait event detection (GED) and ground reaction force (GRF). This study aims to determine the best sensor location for GED and GRF prediction in gait using data from IMUs for healthy and medial knee osteoarthritis (MKOA) individuals. In this study, 27 healthy and 18 MKOA individuals participated. Participants walked at different speeds on an instrumented treadmill. Five synchronized IMUs (Physilog\u00ae, 200 Hz) were placed on the lower limb (top of the shoe, heel, above medial malleolus, middle and front of tibia, and on medial of shank close to knee joint). To predict GRF and GED, an artificial neural network known as reservoir computing was trained using combinations of acceleration signals retrieved from each IMU. For GRF prediction, the best sensor location was top of the shoe for 72.2% and 41.7% of individuals in the healthy and MKOA populations, respectively, based on the minimum value of the mean absolute error (MAE). For GED, the minimum MAE value for both groups was for middle and front of tibia, then top of the shoe. This study demonstrates that top of the shoe is the best sensor location for GED and GRF prediction.<\/jats:p>","DOI":"10.3390\/ijerph20043120","type":"journal-article","created":{"date-parts":[[2023,2,10]],"date-time":"2023-02-10T05:18:35Z","timestamp":1676006315000},"page":"3120","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Inertial Sensor Location for Ground Reaction Force and Gait Event Detection Using Reservoir Computing in Gait"],"prefix":"10.3390","volume":"20","author":[{"given":"Sara","family":"Havashinezhadian","sequence":"first","affiliation":[{"name":"Interdisciplinary Center for Research in Rehabilitation and Social Integration (CIRRIS), Department of Kinesiology, Faculty of Medicine, Universit\u00e9 Laval, Quebec, QC G1V 0A6, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Laurent","family":"Chiasson-Poirier","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, Interdisciplinary Institute for Technological Innovation, Universit\u00e9 de Sherbrooke, Sherbrooke, QC J1K 2R1, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9390-7052","authenticated-orcid":false,"given":"Julien","family":"Sylvestre","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, Interdisciplinary Institute for Technological Innovation, Universit\u00e9 de Sherbrooke, Sherbrooke, QC J1K 2R1, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2649-3459","authenticated-orcid":false,"given":"Katia","family":"Turcot","sequence":"additional","affiliation":[{"name":"Interdisciplinary Center for Research in Rehabilitation and Social Integration (CIRRIS), Department of Kinesiology, Faculty of Medicine, Universit\u00e9 Laval, Quebec, QC G1V 0A6, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,2,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"9884","DOI":"10.3390\/s120709884","article-title":"Foot plantar pressure measurement system: A review","volume":"12","author":"Razak","year":"2012","journal-title":"Sensors"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Ancillao, A., Tedesco, S., Barton, J., and O\u2019Flynn, B. 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