Siyu Yang, Kangjie Zheng, Cenwei Li, Nanxin Li, Fred Han
{"title":"Multimodal adaptive mirror therapy through gait adaptation on a split-belt treadmill for gait training.","authors":"Siyu Yang, Kangjie Zheng, Cenwei Li, Nanxin Li, Fred Han","doi":"10.1177/09287329261496166","DOIUrl":null,"url":null,"abstract":"<p><p>BackgroundTraditional mirror therapy relies on fixed kinematic symmetry, often neglecting the trade-offs between movement accuracy, stability, and muscular effort. This study developed a Multimodal Adaptive Mirror Therapy system featuring a multi-objective controller for personalized gait rehabilitation.ObjectiveTo develop and evaluate a multimodal adaptive mirror therapy system that integrates gait kinematics, postural stability, and muscular activation into a unified multi-objective optimization framework for personalized gait rehabilitation.MethodsTwenty-six subjects underwent asymmetric gait training with unilateral limb restraint to simulate asymmetric gait patterns. The proposed system integrated camera-based gait data, inertial measurement unit (IMU)-based stability metrics, and electromyography (EMG) activation into a unified objective function. Optimization was dynamically adjusted via a weighted harmonic mean of multimodal scores. Normalized mutual information (NMI) was used to quantify dependencies, while interquartile range (IQR) analysis evaluated controller stability.ResultsNMI analysis revealed significant dependencies between all modalities (p < 0.05), with the training parameter showing the strongest correlation with stability (NMI = 0.342). The multimodal controller achieved balanced, near-optimal performance, yielding median scores of 97.81% for stability and 92.44% for gait. Notably, it exhibited the lowest inter-participant variability among all strategies in the stability domain (IQR: 24.80%), compared to substantially wider dispersions observed under unimodal controllers.ConclusionThis study demonstrated that a multimodal, closed-loop control scheme can effectively resolve performance trade-offs in gait training. By transitioning from rigid imitation to dynamic multi-objective optimization, the system provided a robust, intelligent closed-loop platform, establishing a practical foundation for patient-centered robotic rehabilitation.</p>","PeriodicalId":48978,"journal":{"name":"Technology and Health Care","volume":" ","pages":"9287329261496166"},"PeriodicalIF":1.3000,"publicationDate":"2026-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Technology and Health Care","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1177/09287329261496166","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}
引用次数: 0
Abstract
BackgroundTraditional mirror therapy relies on fixed kinematic symmetry, often neglecting the trade-offs between movement accuracy, stability, and muscular effort. This study developed a Multimodal Adaptive Mirror Therapy system featuring a multi-objective controller for personalized gait rehabilitation.ObjectiveTo develop and evaluate a multimodal adaptive mirror therapy system that integrates gait kinematics, postural stability, and muscular activation into a unified multi-objective optimization framework for personalized gait rehabilitation.MethodsTwenty-six subjects underwent asymmetric gait training with unilateral limb restraint to simulate asymmetric gait patterns. The proposed system integrated camera-based gait data, inertial measurement unit (IMU)-based stability metrics, and electromyography (EMG) activation into a unified objective function. Optimization was dynamically adjusted via a weighted harmonic mean of multimodal scores. Normalized mutual information (NMI) was used to quantify dependencies, while interquartile range (IQR) analysis evaluated controller stability.ResultsNMI analysis revealed significant dependencies between all modalities (p < 0.05), with the training parameter showing the strongest correlation with stability (NMI = 0.342). The multimodal controller achieved balanced, near-optimal performance, yielding median scores of 97.81% for stability and 92.44% for gait. Notably, it exhibited the lowest inter-participant variability among all strategies in the stability domain (IQR: 24.80%), compared to substantially wider dispersions observed under unimodal controllers.ConclusionThis study demonstrated that a multimodal, closed-loop control scheme can effectively resolve performance trade-offs in gait training. By transitioning from rigid imitation to dynamic multi-objective optimization, the system provided a robust, intelligent closed-loop platform, establishing a practical foundation for patient-centered robotic rehabilitation.
期刊介绍:
Technology and Health Care is intended to serve as a forum for the presentation of original articles and technical notes, observing rigorous scientific standards. Furthermore, upon invitation, reviews, tutorials, discussion papers and minisymposia are featured. The main focus of THC is related to the overlapping areas of engineering and medicine. The following types of contributions are considered:
1.Original articles: New concepts, procedures and devices associated with the use of technology in medical research and clinical practice are presented to a readership with a widespread background in engineering and/or medicine. In particular, the clinical benefit deriving from the application of engineering methods and devices in clinical medicine should be demonstrated. Typically, full length original contributions have a length of 4000 words, thereby taking duly into account figures and tables.
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Reviews and Tutorials (upon invitation only): Tutorial and educational articles for persons with a primarily medical background on principles of engineering with particular significance for biomedical applications and vice versa are presented. The Editorial Board is responsible for the selection of topics.
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