{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T06:47:25Z","timestamp":1787726845189,"version":"build-2784847793"},"reference-count":44,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2025,2,28]],"date-time":"2025-02-28T00:00:00Z","timestamp":1740700800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"SensorSportLab III"},{"name":"SensorSportLab IV"},{"name":"Consejo Superior de Deportes (Ministerio de Cultura y Deporte)"},{"name":"project IJC2020-043307-I"},{"name":"European Union NextGenerationEU\/PRTR"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This work presents a comparative study of low cost and low invasiveness sensors (plantar pressure and inertial measurement units) for classifying cross-country skiing techniques. A dataset was created for symmetrical comparative analysis, with data collected from skiers using instrumented insoles that measured plantar pressure, foot angles, and acceleration. A deep learning model based on CNN and LSTM was trained on various sensor combinations, ranging from two specific pressure sensors to a full multisensory array per foot incorporating 4 pressure sensors and an inertial measurement unit with accelerometer, magnetometer, and gyroscope. Results demonstrate an encouraging performance with plantar pressure sensors and classification accuracy closer to inertial sensing. The proposed approach achieves a global average accuracy of 94% to 99% with a minimal sensor setup, highlighting its potential for low-cost and precise technique classification in cross-country skiing and future applications in sports performance analysis.<\/jats:p>","DOI":"10.3390\/s25051500","type":"journal-article","created":{"date-parts":[[2025,2,28]],"date-time":"2025-02-28T10:12:33Z","timestamp":1740737553000},"page":"1500","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["A Comparative Study of Plantar Pressure and Inertial Sensors for Cross-Country Ski Classification Using Deep Learning"],"prefix":"10.3390","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8344-7101","authenticated-orcid":false,"given":"Aurora","family":"Polo-Rodr\u00edguez","sequence":"first","affiliation":[{"name":"Department of Computer Engineering, Automatics and Robotics, Research Centre for Information and Communications Technologies (CITIC-UGR), University of Granada, 18014 Granada, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1701-8878","authenticated-orcid":false,"given":"Pablo","family":"Escobedo","sequence":"additional","affiliation":[{"name":"ECsens, Sport and Health University Research Institute (iMUDS), Department of Electronics and Computer Technology, School of Technology and Telecommunications Engineering (ETSIIT), University of Granada, 18014 Granada, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fernando","family":"Mart\u00ednez-Mart\u00ed","sequence":"additional","affiliation":[{"name":"HCTLab Research Group, Universidad Aut\u00f3noma de Madrid, 28049 Madrid, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2840-9882","authenticated-orcid":false,"given":"Noel","family":"Marcen-Cinca","sequence":"additional","affiliation":[{"name":"Department of Health Sciences, University of San Jorge, Villanueva de G\u00e1llego, 50003 Zaragoza, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0234-4758","authenticated-orcid":false,"given":"Miguel A.","family":"Carvajal","sequence":"additional","affiliation":[{"name":"ECsens, Sport and Health University Research Institute (iMUDS), Department of Electronics and Computer Technology, School of Technology and Telecommunications Engineering (ETSIIT), University of Granada, 18014 Granada, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Javier","family":"Medina-Quero","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Automatics and Robotics, Research Centre for Information and Communications Technologies (CITIC-UGR), University of Granada, 18014 Granada, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6733-2283","authenticated-orcid":false,"given":"Mar\u00eda Sof\u00eda","family":"Mart\u00ednez-Garc\u00eda","sequence":"additional","affiliation":[{"name":"HCTLab Research Group, Universidad Aut\u00f3noma de Madrid, 28049 Madrid, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,2,28]]},"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":"Zayegh","year":"2012","journal-title":"Sensors"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1007\/s12283-017-0252-z","article-title":"A Multi-Sensor System for Automatic Analysis of Classical Cross-Country Skiing Techniques","volume":"20","author":"Seeberg","year":"2017","journal-title":"Sports Eng."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"3284","DOI":"10.1109\/TBME.2013.2250972","article-title":"Kinetic Gait Analysis Using a Low-Cost Insole","volume":"60","author":"Howell","year":"2013","journal-title":"IEEE Trans. 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