Characterization of surface EMG signals using improved approximate entropy.

被引：26
|
作者：
Chen W.T. [1 ]
Wang Z.Z. [1 ]
Ren X.M. [1 ]
机构：
[1] Department of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai
来源：
Journal of Zhejiang University SCIENCE B | 2006年 / 7卷 / 10期
基金：
中国国家自然科学基金;
关键词：
Surface EMG (sEMG) signal; Nonlinear analysis; Approximate entropy (ApEn); Fractal dimension; R318.04;
D O I：
10.1631/jzus.2006.B0844
中图分类号：
学科分类号：
摘要：
An improved approximate entropy (ApEn) is presented and applied to characterize surface electromyography (sEMG) signals. In most previous experiments using nonlinear dynamic analysis, this certain processing was often confronted with the problem of insufficient data points and noisy circumstances, which led to unsatisfactory results. Compared with fractal dimension as well as the standard ApEn, the improved ApEn can extract information underlying sEMG signals more efficiently and accurately. The method introduced here can also be applied to other medium-sized and noisy physiological signals.
引用
收藏
页码：844 / 848
页数：4
相关论文
共 50 条
  • [1] Characterization of surface EMG signals using improved approximate entropy
    CHEN Wei-ting
    Journal of Zhejiang University Science(Life Science), 2006, (10) : 844 - 848
  • [2] Surface EMG Classification Using Moving Approximate Entropy
    Ahmad, Siti A.
    Chappell, Paul H.
    ICIAS 2007: INTERNATIONAL CONFERENCE ON INTELLIGENT & ADVANCED SYSTEMS, VOLS 1-3, PROCEEDINGS, 2007, : 1163 - 1167
  • [3] Time series analysis using approximate entropy and sample entropy.
    Richman, J
    Moorman, R
    BIOPHYSICAL JOURNAL, 2000, 78 (01) : 218A - 218A
  • [4] An Improved Knee Abnormality Prediction System Using Surface EMG Signals
    Issa, Sali
    Khaled, Abel Rohman
    JOURNAL OF INFORMATION ASSURANCE AND SECURITY, 2022, 17 (02): : 55 - 65
  • [5] Toward improved control of prosthetic fingers using surface electromyogram (EMG) signals
    Khushaba, Rami N.
    Kodagoda, Sarath
    Takruri, Maen
    Dissanayake, Gamini
    EXPERT SYSTEMS WITH APPLICATIONS, 2012, 39 (12) : 10731 - 10738
  • [6] Nonequilibrium entropy. Characterization of stationary states
    Perez-Madrid, A.
    ENERGY, 2007, 32 (04) : 301 - 305
  • [7] Moving approximate entropy applied to surface electromyographic signals
    Ahmad, Siti A.
    Chappell, Paul H.
    BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2008, 3 (01) : 88 - 93
  • [8] Characterization of surface EMG signal based on fuzzy entropy
    Chen, Weiting
    Wang, Zhizhong
    Xie, Hongbo
    Yu, Wangxin
    IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 2007, 15 (02) : 266 - 272
  • [9] Characterization of EEG Signals for Identification of Alcoholics using ANOVA Ranked Approximate Entropy and Classifiers
    Shri, T. K. Padma
    Sriraam, N.
    Bhat, Vidya
    2014 INTERNATIONAL CONFERENCE ON CIRCUITS, COMMUNICATION, CONTROL AND COMPUTING (I4C), 2014, : 109 - 112
  • [10] Recording intramuscular EMG signals using surface electrodes
    Stoykov, NS
    Lowery, MM
    Heckman, CJ
    Taflove, A
    Kuiken, TA
    2005 IEEE 9TH INTERNATIONAL CONFERENCE ON REHABILITATION ROBOTICS, 2005, : 291 - 294
12345