{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,2]],"date-time":"2025-11-02T16:44:30Z","timestamp":1762101870008,"version":"build-2065373602"},"reference-count":38,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2016,5,10]],"date-time":"2016-05-10T00:00:00Z","timestamp":1462838400000},"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>In this study, we classify four horse gaits (walk, sitting trot, rising trot, canter) of three breeds of horse (Jeju, Warmblood, and Thoroughbred) using a neuro-fuzzy classifier (NFC) of the Takagi-Sugeno-Kang (TSK) type from data information transformed by a wavelet packet (WP). The design of the NFC is accomplished by using a fuzzy c-means (FCM) clustering algorithm that can solve the problem of dimensionality increase due to the flexible scatter partitioning. For this purpose, we use the rider\u2019s hip motion from the sensor information collected by inertial sensors as feature data for the classification of a horse\u2019s gaits. Furthermore, we develop a coaching system under both real horse riding and simulator environments and propose a method for analyzing the rider\u2019s motion. Using the results of the analysis, the rider can be coached in the correct motion corresponding to the classified gait. To construct a motion database, the data collected from 16 inertial sensors attached to a motion capture suit worn by one of the country\u2019s top-level horse riding experts were used. Experiments using the original motion data and the transformed motion data were conducted to evaluate the classification performance using various classifiers. The experimental results revealed that the presented FCM-NFC showed a better accuracy performance (97.5%) than a neural network classifier (NNC), naive Bayesian classifier (NBC), and radial basis function network classifier (RBFNC) for the transformed motion data.<\/jats:p>","DOI":"10.3390\/s16050664","type":"journal-article","created":{"date-parts":[[2016,5,10]],"date-time":"2016-05-10T10:00:31Z","timestamp":1462874431000},"page":"664","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Classification of Horse Gaits Using FCM-Based Neuro-Fuzzy Classifier from the Transformed Data Information of Inertial Sensor"],"prefix":"10.3390","volume":"16","author":[{"given":"Jae-Neung","family":"Lee","sequence":"first","affiliation":[{"name":"Department of Control and Instrumentation Engineering, Chosun University, 375 Seosuk-dong, Gwangju 501-759, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Myung-Won","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Control and Instrumentation Engineering, Chosun University, 375 Seosuk-dong, Gwangju 501-759, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yeong-Hyeon","family":"Byeon","sequence":"additional","affiliation":[{"name":"Department of Control and Instrumentation Engineering, Chosun University, 375 Seosuk-dong, Gwangju 501-759, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Won-Sik","family":"Lee","sequence":"additional","affiliation":[{"name":"Yudo-Star Co., ltd. 415, Cheongneung-Daero, Namdong-Gu, Incheon 405-817, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3821-0711","authenticated-orcid":false,"given":"Keun-Chang","family":"Kwak","sequence":"additional","affiliation":[{"name":"Department of Control and Instrumentation Engineering, Chosun University, 375 Seosuk-dong, Gwangju 501-759, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2016,5,10]]},"reference":[{"key":"ref_1","first-page":"235","article-title":"The Effect of Indoor Horseback-Riding Machine on the Balance of the Elderly with Dementia","volume":"3","author":"Kim","year":"2008","journal-title":"J. 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