{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T13:38:21Z","timestamp":1782394701115,"version":"3.54.5"},"reference-count":14,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2023,4,22]],"date-time":"2023-04-22T00:00:00Z","timestamp":1682121600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Quantitative information on how well a horse clears a jump has great potential to support the rider in improving the horse\u2019s jumping performance. This study investigated the validation of a GPS-based inertial measurement unit, namely Alogo Move Pro, compared with a traditional optical motion capture system. Accuracy and precision of the three jumping characteristics of maximum height (Zmax), stride\/jump length (lhorz), and mean horizontal speed (vhorz) were compared. Eleven horse\u2013rider pairs repeated two identical jumps (an upright and an oxer fence) several times (n = 6 to 10) at different heights in a 20 \u00d7 60 m tent arena. The ground was a fiber sand surface. The 24 OMC (Oqus 7+, Qualisys) cameras were rigged on aluminum rails suspended 3 m above the ground. The Alogo sensor was placed in a pocket on the protective plate of the saddle girth. Reflective markers placed on and around the Alogo sensor were used to define a rigid body for kinematic analysis. The Alogo sensor data were collected and processed using the Alogo proprietary software; stride-matched OMC data were collected using Qualisys Track Manager and post-processed in Python. Residual analysis and Bland\u2013Altman plots were performed in Python. The Alogo sensor provided measures with relative accuracy in the range of 10.5\u201320.7% for stride segments and 5.5\u201329.2% for jump segments. Regarding relative precision, we obtained values in the range of 6.3\u201314.5% for stride segments and 2.8\u201318.2% for jump segments. These accuracy differences were deemed good under field study conditions where GPS signal strength might have been suboptimal.<\/jats:p>","DOI":"10.3390\/s23094196","type":"journal-article","created":{"date-parts":[[2023,4,24]],"date-time":"2023-04-24T03:04:08Z","timestamp":1682305448000},"page":"4196","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Validation of Alogo Move Pro: A GPS-Based Inertial Measurement Unit for the Objective Examination of Gait and Jumping in Horses"],"prefix":"10.3390","volume":"23","author":[{"given":"K\u00e9vin C\u00e9dric","family":"Guyard","sequence":"first","affiliation":[{"name":"Information Science Institute GSEM\/CUI, University of Geneva, 1227 Carouge, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2511-4974","authenticated-orcid":false,"given":"St\u00e9phane","family":"Montavon","sequence":"additional","affiliation":[{"name":"Veterinary Department of the Swiss Armed Force, 3003 Berne, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jonathan","family":"Bertolaccini","sequence":"additional","affiliation":[{"name":"Information Science Institute GSEM\/CUI, University of Geneva, 1227 Carouge, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michel","family":"Deriaz","sequence":"additional","affiliation":[{"name":"HES-SO\/HEG Gen\u00e8ve, 1227 Carouge, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1111\/evj.12126","article-title":"Variation in Training Regimens in Professional Show jumping Yards","volume":"46","author":"Nostell","year":"2014","journal-title":"Equine Vet. 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J."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"372","DOI":"10.1111\/eve.13468","article-title":"The Ridden Horse Pain Ethogram","volume":"34","author":"Dyson","year":"2022","journal-title":"Equine Vet. Educ."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"103454","DOI":"10.1016\/j.jevs.2021.103454","article-title":"Detection of Equine Hoof Motion by Using a Hoof-Mounted Inertial Measurement Unit Sensor in Comparison to Examinations with an Optoelectronic Technique\u2014A Pilot Study","volume":"101","author":"Hagen","year":"2021","journal-title":"J Equine Vet. Sci."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Feuser, A.-K., Gesell-May, S., M\u00fcller, T., and May, A. (2022). Artificial Intelligence for Lameness Detection in Horses\u2014A Preliminary Study. Animals, 12.","DOI":"10.3390\/ani12202804"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Lawin, F.J., Bystr\u00f6m, A., Roepstorff, C., Rhodin, M., Alml\u00f6f, M., Silva, M., Andersen, P.H., Kjellstr\u00f6m, H., and Hernlund, E. (2023). Is Markerless More or Less? Comparing a Smartphone Computer Vision Method for Equine Lameness Assessment to Multi-Camera Motion Capture. Animals, 13.","DOI":"10.3390\/ani13030390"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Bosch, S., Serra Bragan\u00e7a, F., Marin-Perianu, M., Marin-Perianu, R., Van der Zwaag, B.J., Voskamp, J., Back, W., Van Weeren, R., and Havinga, P. (2018). EquiMoves: A Wireless Networked Inertial Measurement System for Objective Examination of Horse Gait. 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