{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T00:56:57Z","timestamp":1774313817529,"version":"3.50.1"},"reference-count":70,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2021,1,26]],"date-time":"2021-01-26T00:00:00Z","timestamp":1611619200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"EFRO OP-Oost","award":["Paardensprong"],"award-info":[{"award-number":["Paardensprong"]}]},{"name":"Swiss federal Office for Agriculture","award":["627001325"],"award-info":[{"award-number":["627001325"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Speed is an essential parameter in biomechanical analysis and general locomotion research. It is possible to estimate the speed using global positioning systems (GPS) or inertial measurement units (IMUs). However, GPS requires a consistent signal connection to satellites, and errors accumulate during IMU signals integration. In an attempt to overcome these issues, we have investigated the possibility of estimating the horse speed by developing machine learning (ML) models using the signals from seven body-mounted IMUs. Since motion patterns extracted from IMU signals are different between breeds and gaits, we trained the models based on data from 40 Icelandic and Franches-Montagnes horses during walk, trot, t\u00f6lt, pace, and canter. In addition, we studied the estimation accuracy between IMU locations on the body (sacrum, withers, head, and limbs). The models were evaluated per gait and were compared between ML algorithms and IMU location. The model yielded the highest estimation accuracy of speed (RMSE = 0.25 m\/s) within equine and most of human speed estimation literature. In conclusion, highly accurate horse speed estimation models, independent of IMU(s) location on-body and gait, were developed using ML.<\/jats:p>","DOI":"10.3390\/s21030798","type":"journal-article","created":{"date-parts":[[2021,1,25]],"date-time":"2021-01-25T21:47:52Z","timestamp":1611611272000},"page":"798","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Using Different Combinations of Body-Mounted IMU Sensors to Estimate Speed of Horses\u2014A Machine Learning Approach"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0898-2718","authenticated-orcid":false,"given":"Hamed","family":"Darbandi","sequence":"first","affiliation":[{"name":"Pervasive Systems Group, Department of Computer Science, University of Twente, 7522 NB Enschede, The Netherlands"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8514-7949","authenticated-orcid":false,"given":"Filipe","family":"Serra Bragan\u00e7a","sequence":"additional","affiliation":[{"name":"Department of Clinical Sciences, Faculty of Veterinary Medicine, Utrecht University, 3584 CM Utrecht, The Netherlands"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0884-5334","authenticated-orcid":false,"given":"Berend Jan","family":"van der Zwaag","sequence":"additional","affiliation":[{"name":"Pervasive Systems Group, Department of Computer Science, University of Twente, 7522 NB Enschede, The Netherlands"},{"name":"Inertia Technology B.V., 7521 AG Enschede, The Netherlands"}]},{"given":"John","family":"Voskamp","sequence":"additional","affiliation":[{"name":"Rosmark Consultancy, 6733 AA Wekerom, The Netherlands"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6259-2377","authenticated-orcid":false,"given":"Annik Imogen","family":"Gmel","sequence":"additional","affiliation":[{"name":"Equine Department, Vetsuisse Faculty, University of Zurich, 8057 Zurich, Switzerland"},{"name":"Agroscope\u2014Swiss National Stud Farm, Les Longs-Pr\u00e9s, 1580 Avenches, Switzerland"}]},{"given":"Eyr\u00fan Halla","family":"Haraldsd\u00f3ttir","sequence":"additional","affiliation":[{"name":"Equine Department, Vetsuisse Faculty, University of Zurich, 8057 Zurich, Switzerland"}]},{"given":"Paul","family":"Havinga","sequence":"additional","affiliation":[{"name":"Pervasive Systems Group, Department of Computer Science, University of Twente, 7522 NB Enschede, The Netherlands"}]}],"member":"1968","published-online":{"date-parts":[[2021,1,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1263","DOI":"10.1016\/j.jevs.2014.09.003","article-title":"Speed Index in the Racing Quarter Horse: A Genome-wide Association Study","volume":"34","author":"Meira","year":"2014","journal-title":"J. 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