{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,25]],"date-time":"2025-12-25T05:16:34Z","timestamp":1766639794691,"version":"3.48.0"},"reference-count":38,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2025,12,19]],"date-time":"2025-12-19T00:00:00Z","timestamp":1766102400000},"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>This paper introduces a lightweight and accessible interaction system for treadmill-based video games, relying solely on facial tracking via a smartphone\u2019s front camera. The system enables real-time estimation of running cadence and directional control through natural head movements, providing an immersive and hands-free gaming experience. A key contribution is the implementation of a FFT-based cadence estimation method that achieves accuracy errors below 5% using only 128 frames, enabling real-time feedback. Preliminary evaluations with 11 participants demonstrate that the FFT-based approach outperforms traditional peak detection in both accuracy and robustness across multiple running speeds. These results position the system as a practical, efficient, and scalable solution for fitness-oriented human\u2013computer interaction, with promising implications for digital health and exergaming.<\/jats:p>","DOI":"10.3390\/s26010020","type":"journal-article","created":{"date-parts":[[2025,12,19]],"date-time":"2025-12-19T14:27:16Z","timestamp":1766154436000},"page":"20","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Optimizing the Interaction System for Treadmill Video Games Using a Smartphone\u2019s Front Camera"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6100-7538","authenticated-orcid":false,"given":"Micaela Yanet","family":"Martin","sequence":"first","affiliation":[{"name":"Institute of New Imaging Technologies, Universitat Jaume I, Av. Vicent Sos Baynat s\/n, 12071 Castell\u00f3n de la Plana, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1055-7657","authenticated-orcid":false,"given":"Carlos","family":"Mar\u00edn-Lora","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Systems Engineering, University of Zaragoza. Escuela Universitaria Polit\u00e9cnica de Teruel, C\/Ciudad Escolar, n\u00ba2, 44003 Teruel, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-8211-3736","authenticated-orcid":false,"given":"Mar\u00eda Beatriz","family":"Villar-L\u00f3pez","sequence":"additional","affiliation":[{"name":"Institute of New Imaging Technologies, Universitat Jaume I, Av. Vicent Sos Baynat s\/n, 12071 Castell\u00f3n de la Plana, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0525-7038","authenticated-orcid":false,"given":"Miguel","family":"Chover","sequence":"additional","affiliation":[{"name":"Institute of New Imaging Technologies, Universitat Jaume I, Av. Vicent Sos Baynat s\/n, 12071 Castell\u00f3n de la Plana, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,12,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Tahan, O., Hawchar, R., Matar, F., and Ghantous, M.M. (2017, January 6\u20138). iGym\u2014A RaspberryPi-smartphone hybrid system for better entertaining treadmill users. Proceedings of the IEEE EUROCON 2017\u201417th International Conference on Smart Technologies, Ohrid, Macedonia.","DOI":"10.1109\/EUROCON.2017.8011084"},{"key":"ref_2","unstructured":"Li, J., Zhang, X., and Zhou, Z. 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