Flavia Marrone, D. Fabris, M. Galli, H. Giberti, Mariano Di Martino, Giovanni Di Martino, M. Tarabini
{"title":"An automated system for the design of orthopaedic insoles","authors":"Flavia Marrone, D. Fabris, M. Galli, H. Giberti, Mariano Di Martino, Giovanni Di Martino, M. Tarabini","doi":"10.1109/MeMeA57477.2023.10171871","DOIUrl":null,"url":null,"abstract":"This work describes a complete system for the automated design of orthopaedic insoles. The system uses a commercial scanner to acquire the 3D scan of the plantar foot; a purposely designed optoelectronic system allows for acquiring the plantar point cloud when the knee and ankle are aligned perpendicularly to the scanning surface. We trained Artificial Neural Network to automatically create the orthopaedic insole starting from the scan and the pathology that must be corrected. We present the preliminary results based on 147 patients with different pathologies.","PeriodicalId":191927,"journal":{"name":"2023 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MeMeA57477.2023.10171871","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This work describes a complete system for the automated design of orthopaedic insoles. The system uses a commercial scanner to acquire the 3D scan of the plantar foot; a purposely designed optoelectronic system allows for acquiring the plantar point cloud when the knee and ankle are aligned perpendicularly to the scanning surface. We trained Artificial Neural Network to automatically create the orthopaedic insole starting from the scan and the pathology that must be corrected. We present the preliminary results based on 147 patients with different pathologies.