{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T09:55:27Z","timestamp":1791280527640,"version":"4.1.0"},"reference-count":31,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T00:00:00Z","timestamp":1791244800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001691","name":"JSPS","doi-asserted-by":"publisher","award":["JP26K15077"],"award-info":[{"award-number":["JP26K15077"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]},{"award":["JP26K15077"],"award-info":[{"award-number":["JP26K15077"]}],"id":[{"id":"https:\/\/ror.org\/00hhkn466","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Plantar load is an important biomechanical measure in gait analysis, rehabilitation assessment, and human movement evaluation. However, conventional measurement systems, including instrumented insoles and laboratory-based force measurement devices, rely on dedicated sensing hardware and may limit the accessibility of continuous gait monitoring. This study proposes a low-cost, monocular video-based framework for estimating bilateral plantar loads from pose-derived biomechanical features. As an initial application setting, we focused on treadmill walking, where a stationary camera can capture repeated body motion under consistent recording conditions, allowing the relationship between video-derived biomechanical features and plantar loading to be investigated before extending the framework to more variable environments. Video and reference plantar-load data from 14 healthy adults during treadmill walking at 3 km\/h were temporally aligned, yielding 50,464 frame-level observations. Body landmarks estimated using MediaPipe Pose were used to construct posture-related, motion-related, and short-term temporal features. Four machine-learning regressors were evaluated, with fold-specific Top-60 feature selection applied to the morphology-excluded feature configuration. ExtraTrees achieved the highest mean performance under blocked temporal five-fold cross-validation, with R2 values of 0.762 \u00b1 0.068 and 0.772 \u00b1 0.073 for the left- and right-foot loads, respectively. Feature-group ablation showed that removing three static morphology variables had only a small effect on blocked-validation performance. Under zero-shot leave-one-subject-out validation, the corresponding mean R2 values were \u22120.252 \u00b1 0.592 and \u22120.180 \u00b1 0.573, indicating limited generalization to previously unseen participants. Using the initial 30 s of reference-load data for subject-specific supervised calibration improved prediction performance on the matched post-calibration interval. Regularized temporal, scale, and offset calibration increased the mean R2 values from \u22120.233 to 0.358 for the left-foot target and from \u22120.141 to 0.444 for the right-foot target. These findings demonstrate the potential of monocular video-derived biomechanical features for bilateral plantar-load estimation during controlled treadmill walking. Short supervised calibration improved average prediction performance for unseen participants, enabling subsequent video-based estimation without continuous wearable-sensor measurements.<\/jats:p>","DOI":"10.3390\/s26196307","type":"journal-article","created":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T09:34:18Z","timestamp":1791279258000},"page":"6307","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Low-Cost Monocular Video-Based Framework for Bilateral Plantar Load Estimation During Treadmill Walking"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-2246-0264","authenticated-orcid":false,"given":"Yanmei","family":"Jiao","sequence":"first","affiliation":[{"name":"Department of Computer Science, Graduate School of Bionics, Computer and Media Sciences, Tokyo University of Technology, Hachioji 192-0982, Tokyo, Japan"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"},{"role":"data-curation","vocabulary":"credit"},{"role":"software","vocabulary":"credit"},{"role":"formal-analysis","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-0542-1094","authenticated-orcid":false,"given":"Gan","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Graduate School of Bionics, Computer and Media Sciences, Tokyo University of Technology, Hachioji 192-0982, Tokyo, Japan"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"},{"role":"data-curation","vocabulary":"credit"},{"role":"software","vocabulary":"credit"},{"role":"formal-analysis","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-9180-0937","authenticated-orcid":false,"given":"Xuan","family":"Huang","sequence":"additional","affiliation":[{"name":"Graduate School of Human Sciences, Waseda University, Tokorozawa 359-1192, Saitama, Japan"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"data-curation","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"}]},{"given":"Yuan","family":"Bian","sequence":"additional","affiliation":[{"name":"Graduate School of Human Sciences, Waseda University, Tokorozawa 359-1192, Saitama, Japan"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"investigation","vocabulary":"credit"},{"role":"data-curation","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1971-595X","authenticated-orcid":false,"given":"Bo","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Computer Science, Tokyo University of Technology, Hachioji 192-0982, Tokyo, Japan"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"resources","vocabulary":"credit"},{"role":"supervision","vocabulary":"credit"},{"role":"project-administration","vocabulary":"credit"},{"role":"funding-acquisition","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]}],"member":"1968","published-online":{"date-parts":[[2026,10,6]]},"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":"25","DOI":"10.1016\/j.fas.2018.12.005","article-title":"A state-of-the-art review of foot pressure","volume":"26","author":"Zulkifli","year":"2020","journal-title":"Foot Ankle Surg."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1016\/j.gaitpost.2024.12.022","article-title":"An overview of plantar pressure distribution measurements and its applications in health and medicine","volume":"117","author":"Arzehgar","year":"2025","journal-title":"Gait Posture"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"342","DOI":"10.1016\/j.bbe.2018.02.004","article-title":"Review on plantar data analysis for disease diagnosis","volume":"38","year":"2018","journal-title":"Biocybern. 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