| 应用于假手的肌电信号分类方法研究 |
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| 引用本文： | 尤波,周丽娜,黄玲. 应用于假手的肌电信号分类方法研究[J]. 哈尔滨理工大学学报, 2011, 16(3): 1-7,11 |
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| 作者姓名： | 尤波 周丽娜 黄玲 |
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| 作者单位： | 哈尔滨理工大学自动化学院,黑龙江哈尔滨,150080 |
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| 基金项目： | 国家“863”重大项目(2009AA043803); 哈尔滨市科技创新人才基金(2009RFQGG207); 黑龙江省教育厅科学技术研究项目(11551090) |
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| 摘 要： | 高效、准确的肌电信号分类方法是实现高仿生性肌电假手控制的关键技术之一.本文对肌电假手常用的信号分类方法进行了系统研究,阐述了目前常用的七种方法的基本原理和研究现状.重点分析了基于神经网络和支持向量机的肌电信号分类方法,分别从网络类型、所采用的信号特征、识别准确率等方面对分类结果进行了比较.最后,对各种方法的优缺点及适应...
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| 关 键 词： | 肌电信号 信号分类 肌电假手 |
Study of Pattern Recognition Methods for Prosthetic Hand Control |
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| YOU Bo,ZHOU Li-na,HUANG Ling. Study of Pattern Recognition Methods for Prosthetic Hand Control[J]. Journal of Harbin University of Science and Technology, 2011, 16(3): 1-7,11 |
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| Authors: | YOU Bo ZHOU Li-na HUANG Ling |
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| Affiliation: | YOU Bo,ZHOU Li-na,HUANG Ling(School of Automation,Harbin University of Science and Technology,Harbin 150080,China) |
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| Abstract: | In order to obtain the purpose of controlling the myoelectric prosthetic hand efficiently and accurately,good signal classification methods must be designed.Classification methods of EMG are studied systematically in this paper.The basic principles and current research status of seven methods which are used frequently are presented,and classification methods of EMG based on neural network and support vector machine are analyzed in particular,and their classification results are compared from the aspects of ... |
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| Keywords: | EMG signal classification myoelectric prosthetic hand |
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