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作 者:Jinwoo Lee Kangkyu Kwon Ira Soltis Jared Matthews Yoon Jae Lee Hojoong Kim Lissette Romero Nathan Zavanelli Youngjin Kwon Shinjae Kwon Jimin Lee Yewon Na Sung Hoon Lee Ki Jun Yu Minoru Shinohara Frank L.Hammond Woon-Hong Yeo
机构地区:[1]Department of Mechanical,Robotics,and Energy Engineering,Dongguk University,Seoul 04620,Republic of Korea [2]IEN Center for Wearable Intelligent Systems and Healthcare,Institute for Electronics and Nanotechnology,Georgia Institute of Technology,Atlanta,GA 30332,USA [3]School of Electrical and Computer Engineering,Georgia Institute of Technology,Atlanta,GA 30332,USA [4]George W.Woodruff School of Mechanical Engineering,Georgia Institute of Technology,Atlanta,GA 30332,USA [5]School of Industrial Design,Georgia Institute of Technology,Atlanta,GA 30332,USA [6]School of Electrical and Electronic Engineering,Yonsei University,Seoul 03722,Republic of Korea [7]School of Biological Sciences,Georgia Institute of Technology,Atlanta,GA 30332,USA [8]Wallace H.Coulter Department of Biomedical Engineering,Georgia Institute of Technology and Emory University School of Medicine,Atlanta,GA 30332,USA [9]Institute for Materials,Parker H.Petit Institute for Bioengineering and Biosciences,Institute for Robotics and Intelligent Machines,Georgia Institute of Technology,Atlanta,GA 30332,USA
出 处:《npj Flexible Electronics》2024年第1期856-868,共13页npj-柔性电子(英文)
基 金:the National Research Foundation of Korea(NRF)(Grant No.NRF-2019R1A2C2086085)。
摘 要:The age and stroke-associated decline in musculoskeletal strength degrades the ability to perform daily human tasks using the upper extremities.Here,we introduce an intelligent upper-limb exoskeleton system that utilizes deep learning to predict human intention for strength augmentation.The embedded soft wearable sensors provide sensory feedback by collecting real-time muscle activities,which are simultaneously computed to determine the user’s intended movement.Cloudbased deep learning predicts four upper-limb joint motions with an average accuracy of 96.2%at a 500–550 ms response rate,suggesting that the exoskeleton operates just by human intention.In addition,an array of soft pneumatics assists the intended movements by providing 897 newtons of force while generating a displacement of 87mm at maximum.The intent-driven exoskeleton can reduce human muscle activities by 3.7 times on average compared to the unassisted exoskeleton.
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