Guang Feng, Jiaji Zhang, G. Chai, Maoqin Li, Guokun Zuo, Lei Yang
{"title":"An Effective Training Strategy for Upper-limb Rehabilitation Robots Based on Visual-haptic Feedback Using Potential Field","authors":"Guang Feng, Jiaji Zhang, G. Chai, Maoqin Li, Guokun Zuo, Lei Yang","doi":"10.1109/CYBER55403.2022.9907062","DOIUrl":null,"url":null,"abstract":"Visual and haptic feedback are crucial to enhance the effectiveness of robot-assisted rehabilitation. To improve the performance of clinical rehabilitation training for patients with motor dysfunction, we propose an effective training strategy based on visual and haptic feedback. Haptic feedback is generated by a designed artificial potential field, which allows patients to perceive the correct training direction. The effectiveness of the proposed training strategy is initially verified, by recruiting three healthy subjects to perform circle drawing tasks on an upper limb rehabilitation robot. Experimental results showed that higher training accuracies were obtained using visual-haptic feedback compared to those with unimodal feedback. The proposed strategy can enhance the users' perception of the training process and corrects the incorrect movements in real-time, simultaneously. The current training strategy can be applied to commercial rehabilitation robots and meet the rehabilitation training needs of the users with impaired vision or the vision is unavailable.","PeriodicalId":34110,"journal":{"name":"IET Cybersystems and Robotics","volume":"31 1","pages":"678-681"},"PeriodicalIF":1.5000,"publicationDate":"2022-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Cybersystems and Robotics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CYBER55403.2022.9907062","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Visual and haptic feedback are crucial to enhance the effectiveness of robot-assisted rehabilitation. To improve the performance of clinical rehabilitation training for patients with motor dysfunction, we propose an effective training strategy based on visual and haptic feedback. Haptic feedback is generated by a designed artificial potential field, which allows patients to perceive the correct training direction. The effectiveness of the proposed training strategy is initially verified, by recruiting three healthy subjects to perform circle drawing tasks on an upper limb rehabilitation robot. Experimental results showed that higher training accuracies were obtained using visual-haptic feedback compared to those with unimodal feedback. The proposed strategy can enhance the users' perception of the training process and corrects the incorrect movements in real-time, simultaneously. The current training strategy can be applied to commercial rehabilitation robots and meet the rehabilitation training needs of the users with impaired vision or the vision is unavailable.