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Research on Key Techniques of Lower Limb Rehabilitation Training Based on Human Surface EMG Signal

Published: 26 January 2022 Publication History

Abstract

In this paper, the Support Vector Machine (SVM) was introduced into the pattern recognition of human lower limb movements, and a classification method based on multi-core Support Vector Machine was constructed. Through motion pattern recognition, a model representing the relationship between motion and surface EMG signals was established, which provided technical Support for the rehabilitation and diagnosis of patients with lower limb hemiplegia.

References

[1]
Liye Ren, Zongming Shao, Donglei Xu. 2019.Study on Feature Extraction of Human Surface EMG Signal in Time-frequency Domain. Journal of Changchun University,10-12.
[2]
Amari S,Wu S.1999. Improving support vector machine classifiers by modifying kernel functions.Neural Networks,112-120.
[3]
Aronszajn N.1950.Theory of reproducing kernels.Transactions of the American Mathematical Society,337-404.
[4]
Hu Liangmou, Cao Keqiang, Xu Haojun, and Dong Xinmin. 2011.The Fault Diagnosis and Control Technology of the Support Vetor Machine. Beijing: National Defense Industry Press,42 -63.
[5]
Mostafa S S,Awal M A,Ahmad M,Rashid M A. 2016.Voiceless Bangla vowel recognition using sEMG signal. SpringerPlus,15-22.
[6]
A. Doswald,F. Carrino,F. Ringeval. 2014.Advanced Processing of sEMG Signalsfor User Independent Recognition.Springer International ublishing,758-761.
[7]
Wu Xiao, Wei Yan, Wu Xia. 2011.Support Vector Machines Based on Hybrid Kernel Function. Journal of Chongqing University of Technology(in Chinese) .SCI,66-70.
[8]
Zhang Qian, Yang Yao. 2012.Research on Kernel Function Based on Support Vector Machine. Electric Power Science and Engineering,42-45.
[9]
She Qingshan, Meng Ming, Luo Zhizeng, Ma Yuliang.2015. Lower extremity EMG recognition based on multi-core learning. Journal of Zhejiang University (Engineering Science).
[10]
She Qingshan Gaoyunyuan Meng Ming and Luo Zhizeng. 2016.Multi-class Recognition of Lower Limb EMG Based on Wavelet Support Vector Machine. Journal of Huazhong University of Science and Technology (Natural Science Edition).
[11]
Hu Liangmou, Cao Keqiang, Xu Haojun, Dong Xinmin. 2011.Support vector machine fault diagnosis and control technology. Beijing: National Defense Industry Press.
[12]
Yang Weijian.2015. Research and Application of Intelligent Wheelchair Human-Machine Interface Technology Based on Vision and EMG Information Fusion. Hangzhou Dianzi University.
[13]
Qiu QJ.2009.Feature Extraction and Pattern Classification of Electromyographic Signals.shanghai: Shanghai Jiaotong University,11-13.
[14]
Wu Dongmei,Sun xin,Zhang Zhicheng,Du Zhijiang.2010.Feature collection and analysis of surface electromyography signals.Joural of Clinical Rehabilitative Tissue Engineering Research,8073-8074.
[15]
Disselhorst-Klug C,Schmitz-Rode T, Rau G.2019. Surface electromyography and muscle force: limits in sEMG-force relationship and new approaches for applications. Clin Biomech,Bristol, Avon.225-235.

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ICBBS '21: Proceedings of the 2021 10th International Conference on Bioinformatics and Biomedical Science
October 2021
207 pages
ISBN:9781450384308
DOI:10.1145/3498731
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 January 2022

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Author Tags

  1. Feature extraction
  2. Rehabilitation medicine
  3. Support vector machine
  4. Surface EMG signal

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