手指肌电信号稀疏分解重构与活动段特征提取研究 |
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引用本文: | 黄鹏程,林雪,鲍官军,杨庆华. 手指肌电信号稀疏分解重构与活动段特征提取研究[J]. 机电工程, 2016, 0(5): 566-572. DOI: 10.3969/j.issn.1001-4551.2016.05.013 |
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作者姓名: | 黄鹏程 林雪 鲍官军 杨庆华 |
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作者单位: | 1. 金华职业技术学院机电工程学院,浙江金华,321000;2. 浙江省农业机械研究院,浙江金华,321000;3. 浙江工业大学特种装备制造与先进加工技术教育部/浙江省重点实验室,浙江杭州,310032 |
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基金项目: | 国家自然科学基金资助项目(51405441),浙江省自然科学基金资助项目(Q15E050025) |
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摘 要: | 针对传统信号处理方法在非平稳信号处理中的局限性问题,对稀疏分解思想和自适应过完备原子库进行了研究,提出了将稀疏分解思想应用到表面肌电信号处理中的方法。采用数据分割的方式,对原始信号进行了预处理。在正交匹配追踪算法的基础上,利用K均值-奇异值分解(K-SVD)算法构造了自适应过完备原子库,对分割后的各个样本块分别进行了稀疏分解,将其多维特征重构为一维稀疏系数。同时,以便于实际应用与连续控制为原则,对每个样本块的稀疏系数进行了重组,用单个特征值表征了样本块的多维特征。数据分析结果表明,重构后的一维稀疏系数可以保留四维原始信号的绝大部分能量,而重组后的特征值可以准确反映原始信号活动段的变化。
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关 键 词: | K-SVD multi-dimensional s EMG orthogonal matching pursuit sparse decomposition 多维表面肌电信号 正交匹配追踪 稀疏分解 K均值-奇异值分解 Language of Keywords: English Chinese |
Sparse decomposition and reconstruction of finger EMG and feature extraction of active segment |
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Abstract: | Aiming at the limitation of traditional signal processing method in non-stable signal processing, Sparse Decomposition and self-adaptive overcomplete dictionary were studied. Sparse Decomposition was investigated in s EMG processing. And data partitioning was used in the signal preprocessing. Based on Orthogonal Matching Pursuit, the multi-dimensional characteristic of sample blocks was reconstructed to one-dimensional sparse coefficient by self-adaptive overcomplete dictionary. And the dictionary was built by K-SVD. Meanwhile, in order to facilitate practical application and continuous control, sample block sparse coefficients were recombined into single eigenvalue. The multi-dimensional characteristic of sample block was shown in this signal eigenvalue. The result of data analysis indicates that one-dimensional sparse coefficient inherits most energy from the original four-dimensional signal; the changes of original signal active segment could be reflected accurately by single eigenvalue. [ABSTRACT FROM AUTHOR] |
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Keywords: | sparse decomposition orthogonal matching pursuit K-SVD multi-dimensional sEMG |
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