Dextrous Hands: Human, Prosthetic, and Robotic

IF 0.7 4区 计算机科学 Q4 COMPUTER SCIENCE, CYBERNETICS Presence-Teleoperators and Virtual Environments Pub Date : 1997-02-01 DOI:10.1162/pres.1997.6.1.29
L. Jones
{"title":"Dextrous Hands: Human, Prosthetic, and Robotic","authors":"L. Jones","doi":"10.1162/pres.1997.6.1.29","DOIUrl":null,"url":null,"abstract":"The sensory and motor capacities of the human hand are reviewed in the context of providing a set of performance characteristics against which prosthetic and dextrous robot hands can be evaluated. The sensors involved in processing tactile, thermal, and proprioceptive (force and movement) information are described, together with details on their spatial densities, sensitivity, and resolution. The wealth of data on the human hand's sensory capacities is not matched by an equivalent database on motor performance. Attempts at quantifying manual dexterity have met with formidable technological difficulties due to the conditions under which many highly trained manual skills are performed. Limitations in technology have affected not only the quantifying of human manual performance but also the development of prosthetic and robotic hands. Most prosthetic hands in use at present are simple grasping devices, and imparting a natural sense of touch to these hands remains a challenge. Several dextrous robot hands exist as research tools and even though some of these systems can outperform their human counterparts in the motor domain, they are still very limited as sensory processing systems. It is in this latter area that information from studies of human grasping and processing of object information may make the greatest contribution.","PeriodicalId":54588,"journal":{"name":"Presence-Teleoperators and Virtual Environments","volume":"21 1","pages":"29-56"},"PeriodicalIF":0.7000,"publicationDate":"1997-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"54","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Presence-Teleoperators and Virtual Environments","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1162/pres.1997.6.1.29","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, CYBERNETICS","Score":null,"Total":0}
引用次数: 54

Abstract

The sensory and motor capacities of the human hand are reviewed in the context of providing a set of performance characteristics against which prosthetic and dextrous robot hands can be evaluated. The sensors involved in processing tactile, thermal, and proprioceptive (force and movement) information are described, together with details on their spatial densities, sensitivity, and resolution. The wealth of data on the human hand's sensory capacities is not matched by an equivalent database on motor performance. Attempts at quantifying manual dexterity have met with formidable technological difficulties due to the conditions under which many highly trained manual skills are performed. Limitations in technology have affected not only the quantifying of human manual performance but also the development of prosthetic and robotic hands. Most prosthetic hands in use at present are simple grasping devices, and imparting a natural sense of touch to these hands remains a challenge. Several dextrous robot hands exist as research tools and even though some of these systems can outperform their human counterparts in the motor domain, they are still very limited as sensory processing systems. It is in this latter area that information from studies of human grasping and processing of object information may make the greatest contribution.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
灵巧的手:人类、假肢和机器人
在提供一组性能特征的背景下,对假肢和灵巧的机器人手进行评估,回顾了人手的感觉和运动能力。描述了涉及处理触觉、热和本体感觉(力和运动)信息的传感器,以及它们的空间密度、灵敏度和分辨率的细节。关于人类手部感官能力的丰富数据与关于运动表现的等效数据库并不匹配。由于许多训练有素的手工技能都是在一定条件下进行的,因此对手工灵巧性进行量化的尝试遇到了巨大的技术困难。技术上的限制不仅影响了人类手动性能的量化,也影响了假肢和机械手的发展。目前使用的大多数假肢手都是简单的抓取装置,赋予这些手自然的触觉仍然是一个挑战。一些灵巧的机器人手作为研究工具存在,尽管其中一些系统在运动领域可以胜过它们的人类对手,但它们作为感觉处理系统仍然非常有限。正是在后一个领域,来自人类抓取和处理对象信息的研究的信息可能做出最大的贡献。
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 去求助
来源期刊
CiteScore
2.20
自引率
0.00%
发文量
8
审稿时长
>12 weeks
期刊最新文献
Correlates of Presence in a Virtual Reality Gamification Environment for Rehabilitation after Musculoskeletal Injury Intrinsically Secure Information Barrier for Arms Control Verification. Sandia National Labs Scaled Wind Farm Technology (SWiFT) Facility - Navigating Safely into the 2020s. HydroGEN: Solar Thermochemical Hydrogen (STCH) Water Splitting. Determining Hazard Severity via Probabilistic Risk Assessment in the Commercial Trucking Industry to Inform Design and Qualification.
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1