{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T23:26:22Z","timestamp":1768519582160,"version":"3.49.0"},"reference-count":34,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2023,1,3]],"date-time":"2023-01-03T00:00:00Z","timestamp":1672704000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Icelandic directorate of labour"},{"name":"the University of Iceland"},{"name":"Horseday ehf"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Animals"],"abstract":"<jats:p>Automated gait classification has traditionally been studied using horse-mounted sensors. However, smartphone-based sensors are more accessible, but the performance of gait classification models using data from such sensors has not been widely known or accessible. In this study, we performed horse gait classification using deep learning models and data from mobile phone sensors located in the rider\u2019s pocket. We gathered data from 17 horses and 14 riders. The data were gathered simultaneously from movement sensors in a mobile phone located in the rider\u2019s pocket and a gait classification system based on four wearable sensors attached to the horse\u2019s limbs. With this efficient approach to acquire labelled data, we trained a Bi-LSTM model for gait classification. The only input to the model was a 50 Hz signal from the phone\u2019s accelerometer and gyroscope that was rotated to the horse\u2019s frame of reference. We demonstrate that sensor data from mobile phones can be used to classify the five gaits of the Icelandic horse with up to 94.4% accuracy. The result suggests that horse riding activities can be studied at a large scale using mobile phones to gather data on gaits. While our study showed that mobile phone sensors could be effective for gait classification, there are still some limitations that need to be addressed in future research. For example, further studies could explore the effects of different riding styles or equipment on gait classification accuracy or investigate ways to minimize the influence of factors such as phone placement. By addressing these questions, we can continue to improve our understanding of horse gait and its role in horse riding activities.<\/jats:p>","DOI":"10.3390\/ani13010183","type":"journal-article","created":{"date-parts":[[2023,1,4]],"date-time":"2023-01-04T01:42:44Z","timestamp":1672796564000},"page":"183","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Efficient Development of Gait Classification Models for Five-Gaited Horses Based on Mobile Phone Sensors"],"prefix":"10.3390","volume":"13","author":[{"given":"Haraldur B.","family":"Dav\u00ed\u00f0sson","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of Iceland, 101 Reykjav\u00edk, Iceland"},{"name":"Horseday ehf., 102 Reykjav\u00edk, Iceland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Torben","family":"Rees","sequence":"additional","affiliation":[{"name":"T\u00f6ltSense Ltd., Newton Abbot TQ12 5ND, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marta Rut","family":"\u00d3lafsd\u00f3ttir","sequence":"additional","affiliation":[{"name":"Horseday ehf., 102 Reykjav\u00edk, Iceland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hafsteinn","family":"Einarsson","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Iceland, 101 Reykjav\u00edk, Iceland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,1,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"701","DOI":"10.1126\/science.150.3697.701","article-title":"Symmetrical Gaits of Horses","volume":"150","author":"Hildebrand","year":"1965","journal-title":"Science"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"8145","DOI":"10.3390\/s120608145","article-title":"Accuracy and Precision of Equine Gait Event Detection during Walking with Limb and Trunk Mounted Inertial Sensors","volume":"12","author":"Olsen","year":"2012","journal-title":"Sensors"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"688","DOI":"10.1111\/evj.12669","article-title":"A simple method for equine kinematic gait event detection","volume":"49","author":"Holt","year":"2017","journal-title":"Equine Vet. 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