Adib H Laskar, Reza Tafreshi, Muhammad Bin Mughees, Khaled Al-Halabi, Reza Langari, Md Ferdous Wahid
{"title":"Assessing Repeatability of CLEVERArm Exoskeleton Using Healthy Subjects: A Pilot Study.","authors":"Adib H Laskar, Reza Tafreshi, Muhammad Bin Mughees, Khaled Al-Halabi, Reza Langari, Md Ferdous Wahid","doi":"10.1109/ICORR66766.2025.11062963","DOIUrl":null,"url":null,"abstract":"<p><p>Upper extremity (UE) impairments resulting from non-communicable diseases continue to rise annually across the globe. Robotic devices offer promising solutions for mitigating the long-term logistical challenges and limited recovery outcomes associated with short-term, one-to-one rehabilitation sessions. This study presents a repeatability analysis of CLEVERArm (compact, lightweight, ergonomic, VR/AR-enhanced rehabilitation arm), an eight-degrees-of-freedom (DOF) robotic exoskeleton for treating patients with UE impairments, focusing on validating both single-DOF (sDOF) and multi-DOF (mDOF) trajectories produced by the device. Eighteen healthy subjects performed tasks ranging from simple to complex UE movements associated with activities of daily living. The device then autonomously repeated the movements made by the participants. Across all tasks, CLEVERArm demonstrated low root mean square deviation (<3.42°), and high correlations (>0.99) between reference and repetition trajectories recorded by absolute encoders. High intra-class coefficient values (>0.9) further constitute the system's consistency and accuracy in UE movement over time. These results suggest that CLEVERArm can reliably replicate input trajectories, providing consistent and positive outcomes in rehabilitation settings. Future work will utilize the device's ability to accurately replicate trajectories for designing personalized rehabilitation regimens, monitoring patient progress, and tailoring exercises to individual needs, ultimately enhancing long-term recovery for patients with UE impairments.</p>","PeriodicalId":73276,"journal":{"name":"IEEE ... International Conference on Rehabilitation Robotics : [proceedings]","volume":"2025 ","pages":"160-165"},"PeriodicalIF":0.0000,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE ... International Conference on Rehabilitation Robotics : [proceedings]","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICORR66766.2025.11062963","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
Upper extremity (UE) impairments resulting from non-communicable diseases continue to rise annually across the globe. Robotic devices offer promising solutions for mitigating the long-term logistical challenges and limited recovery outcomes associated with short-term, one-to-one rehabilitation sessions. This study presents a repeatability analysis of CLEVERArm (compact, lightweight, ergonomic, VR/AR-enhanced rehabilitation arm), an eight-degrees-of-freedom (DOF) robotic exoskeleton for treating patients with UE impairments, focusing on validating both single-DOF (sDOF) and multi-DOF (mDOF) trajectories produced by the device. Eighteen healthy subjects performed tasks ranging from simple to complex UE movements associated with activities of daily living. The device then autonomously repeated the movements made by the participants. Across all tasks, CLEVERArm demonstrated low root mean square deviation (<3.42°), and high correlations (>0.99) between reference and repetition trajectories recorded by absolute encoders. High intra-class coefficient values (>0.9) further constitute the system's consistency and accuracy in UE movement over time. These results suggest that CLEVERArm can reliably replicate input trajectories, providing consistent and positive outcomes in rehabilitation settings. Future work will utilize the device's ability to accurately replicate trajectories for designing personalized rehabilitation regimens, monitoring patient progress, and tailoring exercises to individual needs, ultimately enhancing long-term recovery for patients with UE impairments.