Jiaqi Guo, Shuangyue Yu, Yanjun Li, T. Huang, Junlin Wang, Brian Lynn, Jeremy Fidock, Chien-Lung Shen, D. Edwards, Hao Su
{"title":"A soft robotic exo-sheath using fabric EMG sensing for hand rehabilitation and assistance","authors":"Jiaqi Guo, Shuangyue Yu, Yanjun Li, T. Huang, Junlin Wang, Brian Lynn, Jeremy Fidock, Chien-Lung Shen, D. Edwards, Hao Su","doi":"10.1109/ROBOSOFT.2018.8405375","DOIUrl":null,"url":null,"abstract":"This paper presents the design and evaluation of a soft hand exo-sheath integrated with a soft fabric electromyography (EMG) sensor for rehabilitation and activities of daily living (ADL) assistance of stroke and spinal cord injury (SCI) patients. This wearable robot addresses the limitations of the soft robot gloves with design considerations in terms of ergonomics and clinical practice. Its features include: this exo-sheath is based on electric actuation and has been designed to be compact and portable. It reduces the shear force and avoids kinematic singularity comparing with tendon-driven soft gloves as their tendon routings are typically in parallel with individual fingers. Disparate from conventional robotic gloves, this design optimizes a bio-inspired fin-ray structure to enhance the hand proprioception as the palm is not covered by wearable structures. With a novel self-fastening finger clasp design, wearers can self-don/doff the exoskeleton device simplifying ADL assistance. To develop more intuitive control interface, a soft fabric EMG sensor has been developed to understand human intentions. The functionality of this soft robot has been demonstrated with experimental results using the low-level position control, kinematics evaluation and reliable EMG measurements.","PeriodicalId":306255,"journal":{"name":"2018 IEEE International Conference on Soft Robotics (RoboSoft)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Conference on Soft Robotics (RoboSoft)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ROBOSOFT.2018.8405375","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15
Abstract
This paper presents the design and evaluation of a soft hand exo-sheath integrated with a soft fabric electromyography (EMG) sensor for rehabilitation and activities of daily living (ADL) assistance of stroke and spinal cord injury (SCI) patients. This wearable robot addresses the limitations of the soft robot gloves with design considerations in terms of ergonomics and clinical practice. Its features include: this exo-sheath is based on electric actuation and has been designed to be compact and portable. It reduces the shear force and avoids kinematic singularity comparing with tendon-driven soft gloves as their tendon routings are typically in parallel with individual fingers. Disparate from conventional robotic gloves, this design optimizes a bio-inspired fin-ray structure to enhance the hand proprioception as the palm is not covered by wearable structures. With a novel self-fastening finger clasp design, wearers can self-don/doff the exoskeleton device simplifying ADL assistance. To develop more intuitive control interface, a soft fabric EMG sensor has been developed to understand human intentions. The functionality of this soft robot has been demonstrated with experimental results using the low-level position control, kinematics evaluation and reliable EMG measurements.