{"title":"Cover Image, Volume 5, Number 3, September 2025","authors":"","doi":"10.1002/msd2.70050","DOIUrl":null,"url":null,"abstract":"<p><b>Cover Caption:</b> Scoliosis Rehabilitation with a Robotic Brace Powered by RL-based Impedance Control and Digital Twin: Adolescent Idiopathic Scoliosis (AIS) is commonly treated with traditional braces that rely solely on passive strap tensioning, lacking intelligent control strategies. This study proposes a reinforcement learning-based position-based impedance control (RLPIC) method for robotic braces to enable active human–robot interaction. To safely simulate and train the control system, a novel five-dimensional, three-layer digital twin (DT) model is developed, integrating physical modeling, digital modeling, bidirectional interaction, and optimization, enhanced by a neural network-based parameter estimator. Both numerical simulations and real-time experiments validate the DT and RLPIC framework, demonstrating improved tracking and interaction performance in AIS treatment.\n\n <figure>\n <div><picture>\n <source></source></picture><p></p>\n </div>\n </figure></p>","PeriodicalId":60486,"journal":{"name":"国际机械系统动力学学报(英文)","volume":"5 3","pages":""},"PeriodicalIF":3.6000,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/msd2.70050","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"国际机械系统动力学学报(英文)","FirstCategoryId":"1087","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/msd2.70050","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
引用次数: 0
Abstract
Cover Caption: Scoliosis Rehabilitation with a Robotic Brace Powered by RL-based Impedance Control and Digital Twin: Adolescent Idiopathic Scoliosis (AIS) is commonly treated with traditional braces that rely solely on passive strap tensioning, lacking intelligent control strategies. This study proposes a reinforcement learning-based position-based impedance control (RLPIC) method for robotic braces to enable active human–robot interaction. To safely simulate and train the control system, a novel five-dimensional, three-layer digital twin (DT) model is developed, integrating physical modeling, digital modeling, bidirectional interaction, and optimization, enhanced by a neural network-based parameter estimator. Both numerical simulations and real-time experiments validate the DT and RLPIC framework, demonstrating improved tracking and interaction performance in AIS treatment.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
