An Efficient Approach for Feature Selection of SEMG Signal

被引：0
|
作者：
Liang Qi [1 ]
Ye Ming [1 ]
Ma Wenjie [1 ]
机构：
[1] Hanzghou Dianzi Univ, Inst Intelligent Control & Robert Res, Hangzhou 310018, Zhejiang, Peoples R China
来源：
PROCEEDINGS OF THE 2008 INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DESIGN, VOL 2 | 2008年
关键词：
D O I：
10.1109/ISCID.2008.171
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper introduces an approach to obtain the feature vectors of surface electromyography (sEMG) signal based on Hilbert Huang Transform (HHT). An adaptive segmentation method that could effectively select appropriate Intrinsic Mode Function (IMF) is proposed. With the features gathered by using the energy of one channel signal, we also provide an optimized strategy based on experiments and experiences to increase the recognition rate of hand-motion patterns. The results from SVM neural networks classifier are presented to support this approach.
引用
收藏
页码：134 / 137
页数：4
相关论文
共 50 条
  • [41] An efficient feature selection based Bayesian and Rough set approach for intrusion detection
    Prasad, Mahendra
    Tripathi, Sachin
    Dahal, Keshav
    APPLIED SOFT COMPUTING, 2020, 87 (87)
  • [42] An Efficient Parallel Reptile Search Algorithm and Snake Optimizer Approach for Feature Selection
    Al-Shourbaji, Ibrahim
    Kachare, Pramod H.
    Alshathri, Samah
    Duraibi, Salahaldeen
    Elnaim, Bushra
    Abd Elaziz, Mohamed
    MATHEMATICS, 2022, 10 (13)
  • [43] Effective features extraction and selection for hand gesture recognition using sEMG signal
    Miah A.S.M.
    Shin J.
    Hasan M.A.M.
    Multimedia Tools and Applications, 2024, 83 (37) : 85169 - 85193
  • [44] sEMG signal classification with novel feature extraction using different machine learning approaches
    Narayan, Yogendra
    Mathew, Lini
    Chatterji, S.
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2018, 35 (05) : 5099 - 5109
  • [45] A new approach to feature selection
    Scherf, M
    ARTIFICIAL INTELLIGENCE IN MEDICINE, 1997, 1211 : 181 - 184
  • [46] A hybrid approach to feature selection
    Boussouf, M
    PRINCIPLES OF DATA MINING AND KNOWLEDGE DISCOVERY, 1998, 1510 : 230 - 238
  • [47] AN APPROACH TO META FEATURE SELECTION
    Li, JianLin
    2013 26TH ANNUAL IEEE CANADIAN CONFERENCE ON ELECTRICAL AND COMPUTER ENGINEERING (CCECE), 2013, : 854 - 857
  • [48] A Hybrid Approach for Feature Selection
    Tiwari, Sadhana
    Singh, Birmohan
    2015 THIRD INTERNATIONAL CONFERENCE ON IMAGE INFORMATION PROCESSING (ICIIP), 2015, : 277 - 280
  • [49] A Novel Approach for Feature Selection
    Swapna, Ch. Swetha
    Kumar, V. Vijaya
    Murthy, J. V. R.
    INFORMATION SYSTEMS DESIGN AND INTELLIGENT APPLICATIONS, VOL 1, 2015, 339 : 877 - 885
  • [50] Feature Extraction of Surface Electromyography (sEMG) and Signal Processing Technique in Wavelet Transform: A Review
    Burhan, Nuradebah
    Kasno, Mohammad 'Afif
    Ghazali, Rozaimi
    2016 IEEE INTERNATIONAL CONFERENCE ON AUTOMATIC CONTROL AND INTELLIGENT SYSTEMS (I2CACIS), 2016, : 141 - 146
12345