Upper limb motion intent recognition using tactile sensing

Thekla Stefanou, Allie J. Turton, A. Lenz, S. Dogramadzi
{"title":"Upper limb motion intent recognition using tactile sensing","authors":"Thekla Stefanou, Allie J. Turton, A. Lenz, S. Dogramadzi","doi":"10.1109/IROS.2017.8206573","DOIUrl":null,"url":null,"abstract":"Focusing on upper limb rehabilitation of weak stroke patients, this pilot study explores how motion intent can be detected using force sensitive resistors (FSR). This is part of a bigger project which will see the actuation and control of an intent-driven exoskeleton. The limited time stroke survivors have with their therapists means that they can not often get enough training. During active-assisted training, therapists guide the paralysed limb through a movement only after detecting visual or haptic cues of the motion intent from the patient. Aiming to replicate therapist practices of recognising patients' intention to move, a pilot study of a tactile system is performed. The system will perform consistently even with patients who have low muscle strength and control ability. Currently available devices for detecting muscle activity do not offer the robustness and performance necessary; Electromyography (EMG) sensors, a well-established method, is affected by factors like skin moisture and BCI (Brain Computer Interface) has a slow response time. The proposed tactile sensing system is a simple yet robust solution both from a sensing as well as a usability point of view. Pilot experiments have been performed with a healthy subject emulating low muscle activation conditions. An overall accuracy of 80.45% is achieved when detecting forearm and arm muscle contractions and hence motion intent.","PeriodicalId":6658,"journal":{"name":"2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"97 1","pages":"6601-6608"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IROS.2017.8206573","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

Focusing on upper limb rehabilitation of weak stroke patients, this pilot study explores how motion intent can be detected using force sensitive resistors (FSR). This is part of a bigger project which will see the actuation and control of an intent-driven exoskeleton. The limited time stroke survivors have with their therapists means that they can not often get enough training. During active-assisted training, therapists guide the paralysed limb through a movement only after detecting visual or haptic cues of the motion intent from the patient. Aiming to replicate therapist practices of recognising patients' intention to move, a pilot study of a tactile system is performed. The system will perform consistently even with patients who have low muscle strength and control ability. Currently available devices for detecting muscle activity do not offer the robustness and performance necessary; Electromyography (EMG) sensors, a well-established method, is affected by factors like skin moisture and BCI (Brain Computer Interface) has a slow response time. The proposed tactile sensing system is a simple yet robust solution both from a sensing as well as a usability point of view. Pilot experiments have been performed with a healthy subject emulating low muscle activation conditions. An overall accuracy of 80.45% is achieved when detecting forearm and arm muscle contractions and hence motion intent.
基于触觉感知的上肢运动意图识别
针对弱脑卒中患者的上肢康复,本初步研究探讨了如何使用力敏电阻(FSR)检测运动意图。这是一个更大项目的一部分,该项目将看到一个意图驱动的外骨骼的驱动和控制。中风幸存者与治疗师相处的时间有限,这意味着他们往往得不到足够的训练。在主动辅助训练中,治疗师只有在检测到患者的动作意图的视觉或触觉线索后,才能引导瘫痪的肢体进行运动。为了复制治疗师识别病人移动意图的做法,对触觉系统进行了初步研究。即使对于肌肉力量和控制能力较低的患者,该系统也能始终如一地发挥作用。目前可用的检测肌肉活动的设备不能提供必要的鲁棒性和性能;肌电(EMG)传感器是一种成熟的方法,受皮肤水分等因素的影响,BCI(脑机接口)反应时间较慢。从传感和可用性的角度来看,所提出的触觉传感系统是一个简单而强大的解决方案。在健康受试者身上进行了模拟低肌肉激活条件的先导实验。在检测前臂和手臂肌肉收缩和运动意图时,总体准确率达到80.45%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信