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基于肌肉感知的手势交互模型
引用本文:范俊君,田丰,黄进,刘杰,王宏安,戴国忠.基于肌肉感知的手势交互模型[J].软件学报,2018,29(S2):62-74.
作者姓名:范俊君  田丰  黄进  刘杰  王宏安  戴国忠
作者单位:人机交互北京市重点实验室(中国科学院 软件研究所), 北京 100190;中国科学院大学 计算机与控制学院, 北京 100049,人机交互北京市重点实验室(中国科学院 软件研究所), 北京 100190;中国科学院大学 计算机与控制学院, 北京 100049,人机交互北京市重点实验室(中国科学院 软件研究所), 北京 100190,人机交互北京市重点实验室(中国科学院 软件研究所), 北京 100190,人机交互北京市重点实验室(中国科学院 软件研究所), 北京 100190,人机交互北京市重点实验室(中国科学院 软件研究所), 北京 100190
基金项目:国家重点研发计划(2016YFB10011402);中国科学院前沿科学重点研究计划(QYZDY-SSW-JSC041)
摘    要:在人机交互技术由以计算机演化为以人为中心的背景下,通过感知肌肉活动的手势识别方法,因其可穿戴性、隐式交互性和可靠性的特点在近几年得到了人机交互研究领域的高度关注.但目前的相关研究缺乏统一的语义分析模型和系统模型支持研究和开发.为此,分析讨论了交互手势的分类并归纳总结出适合肌肉感知方法的输入原语,提出基于肌肉感知的手势交互语义分析模型和分层处理的系统结构模型,旨在提高该类型交互应用的研究和开发工作效率.最后分析了办公室环境下的操作手势交互应用场景,给出了该语义分析模型和分层系统结构模型的应用实例.

关 键 词:肌肉感知  手势交互  语义分析模型  系统结构模型  表面肌电信号
收稿时间:2017/6/1 0:00:00

Gesture Interaction Model Based on Muscle Sensing
FAN Jun-Jun,TIAN Feng,HUANG Jin,LIU Jie,WANG Hong-An and DAI Guo-Zhong.Gesture Interaction Model Based on Muscle Sensing[J].Journal of Software,2018,29(S2):62-74.
Authors:FAN Jun-Jun  TIAN Feng  HUANG Jin  LIU Jie  WANG Hong-An and DAI Guo-Zhong
Affiliation:Beijing Key Laboratory of Human-Computer Interaction(Institute of Software, The Chinese Academy of Sciences, Beijing 100190, China;School of Computer and Control Engineering, University of Chinese Academy of Sciences, Beijing 100049, China,Beijing Key Laboratory of Human-Computer Interaction(Institute of Software, The Chinese Academy of Sciences, Beijing 100190, China;School of Computer and Control Engineering, University of Chinese Academy of Sciences, Beijing 100049, China,Beijing Key Laboratory of Human-Computer Interaction(Institute of Software, The Chinese Academy of Sciences, Beijing 100190, China,Beijing Key Laboratory of Human-Computer Interaction(Institute of Software, The Chinese Academy of Sciences, Beijing 100190, China,Beijing Key Laboratory of Human-Computer Interaction(Institute of Software, The Chinese Academy of Sciences, Beijing 100190, China and Beijing Key Laboratory of Human-Computer Interaction(Institute of Software, The Chinese Academy of Sciences, Beijing 100190, China
Abstract:Gesture interaction based on muscle sensing has received great attention due to its wearability, implicit interaction, and reliability under the background of human-computer interaction technique shifting from computer-centered to human-centered. However, current researchs lack of a unified semantic model and system model. This paper discussed the classification of interactive gestures, summarized the input primitives suitable for physiological computing technology, and proposed muscle sensing based gesture interaction semantic model and hierarchical processing a system model. Finally, this paper implemented a prototype of object operating gesture recognition under scenario of office environment.
Keywords:muscle sensing  gesture interaction  semantic analysis model  system structure model  surface electromyography signal
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