{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T04:23:08Z","timestamp":1782274988952,"version":"3.54.5"},"reference-count":52,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2020,8,11]],"date-time":"2020-08-11T00:00:00Z","timestamp":1597104000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["2018R1D1A1A02086093"],"award-info":[{"award-number":["2018R1D1A1A02086093"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The human foot is easily deformed owing to the innate form of the foot or an incorrect walking posture. Foot deformations not only pose a threat to foot health but also cause fatigue and pain when walking; therefore, accurate diagnoses of foot deformations are required. However, the measurement of foot deformities requires specialized personnel, and the objectivity of the diagnosis may be insufficient for professional medical personnel to assess foot deformations. Thus, it is necessary to develop an objective foot deformation classification model. In this study, a model for classifying foot types is developed using image and numerical foot pressure data. Such heterogeneous data are used to generate a fine-tuned visual geometry group-16 (VGG16) and K\u2212nearest neighbor (k-NN) models, respectively, and a stacking ensemble model is finally generated to improve accuracy and robustness by combining the two models. Through k-fold cross-validation, the accuracy and robustness of the proposed method have been verified by the mean and standard deviation of the f1 scores (0.9255 and 0.0042), which has superior performance compared to single models generated using only numerical or image data. Thus, the proposed model provides the objectivity of diagnosis for foot deformation, and can be used for analysis and design of foot healthcare products.<\/jats:p>","DOI":"10.3390\/s20164481","type":"journal-article","created":{"date-parts":[[2020,8,11]],"date-time":"2020-08-11T09:28:57Z","timestamp":1597138137000},"page":"4481","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":34,"title":["A Deep-Learning Approach for Foot-Type Classification Using Heterogeneous Pressure Data"],"prefix":"10.3390","volume":"20","author":[{"given":"Jonghyeok","family":"Chae","sequence":"first","affiliation":[{"name":"School of Mechanical Engineering, Pusan National University (PNU), Busan 46290, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9492-8963","authenticated-orcid":false,"given":"Young-Jin","family":"Kang","sequence":"additional","affiliation":[{"name":"Research Institute of Mechanical Technology, Pusan National University (PNU), Busan 46290, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0342-5189","authenticated-orcid":false,"given":"Yoojeong","family":"Noh","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Pusan National University (PNU), Busan 46290, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,8,11]]},"reference":[{"key":"ref_1","unstructured":"Michaud, T.C. 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