Reducing Power Line Interference from sEMG Signals Based on Synchrosqueezed Wavelet Transform

被引:2
|
作者
Chen, Jingcheng [1 ,2 ]
Sun, Yining [1 ,2 ]
Sun, Shaoming [1 ,2 ,3 ]
Yao, Zhiming [1 ,2 ,4 ]
机构
[1] Chinese Acad Sci, Inst Intelligent Machines, Hefei Inst Phys Sci, Hefei 230031, Peoples R China
[2] Univ Sci & Technol China, Hefei 230026, Peoples R China
[3] Chinese Acad Sci, Hefei Inst Technol Innovat, Hefei 230088, Peoples R China
[4] Tongling Univ, Sch Math & Comp, Tongling, Peoples R China
关键词
power line interference; synchrosqueezed wavelet transform; surface electromyography; adaptive ridge extraction; SURFACE; ALGORITHM;
D O I
10.3390/s23115182
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Power line interference (PLI) is a major source of noise in sEMG signals. As the bandwidth of PLI overlaps with the sEMG signals, it can easily affect the interpretation of the signal. The processing methods used in the literature are mostly notch filtering and spectral interpolation. However, it is difficult for the former to reconcile the contradiction between completely filtering and avoiding signal distortion, while the latter performs poorly in the case of a time-varying PLI. To solve these, a novel synchrosqueezed-wavelet-transform (SWT)-based PLI filter is proposed. The local SWT was developed to reduce the computation cost while maintaining the frequency resolution. A ridge location method based on an adaptive threshold is presented. In addition, two ridge extraction methods (REMs) are proposed to fit different application requirements. Parameters were optimized before further study. Notch filtering, spectral interpolation, and the proposed filter were evaluated on the simulated signals and real signals. The output signal-to-noise ratio (SNR) ranges of the proposed filter with two different REMs are 18.53-24.57 and 18.57-26.92. Both the quantitative index and the time-frequency spectrum diagram show that the performance of the proposed filter is significantly better than that of the other filters.
引用
收藏
页数:20
相关论文
共 50 条
  • [1] Harmonic signal extraction from chaotic interference based on synchrosqueezed wavelet transform
    Wang Xiang-Li
    Wang Bin
    Wang Wen-Bo
    Yu Min
    Wang Zhen
    Chang Yu-Chan
    ACTA PHYSICA SINICA, 2015, 64 (10)
  • [2] Harmonic signal extraction from noisy chaotic interference based on synchrosqueezed wavelet transform
    Wang Xiang-Li
    Wang Wen-Bo
    CHINESE PHYSICS B, 2015, 24 (08)
  • [3] Harmonic signal extraction from noisy chaotic interference based on synchrosqueezed wavelet transform
    汪祥莉
    王文波
    Chinese Physics B, 2015, 24 (08) : 142 - 148
  • [4] Power Line Interference Removal from EECG Signals Using Wavelet Transform based Component-Retrieval
    Sharma, Tanushree
    Sharma, Kamalesh K.
    2016 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, COMMUNICATIONS AND INFORMATICS (ICACCI), 2016, : 95 - 101
  • [5] Synchrosqueezed wavelet transform for frequency and damping identification from noisy signals
    Montejo, Luis A.
    Vidot-Vega, Aidcer L.
    SMART STRUCTURES AND SYSTEMS, 2012, 9 (05) : 441 - 459
  • [6] Nonstationary harmonic signal extraction from strong chaotic interference based on synchrosqueezed wavelet transform
    Wang, Xiang-Li
    Li, Chun-Lin
    Yan, Xin
    SIGNAL IMAGE AND VIDEO PROCESSING, 2019, 13 (02) : 397 - 403
  • [7] Nonstationary harmonic signal extraction from strong chaotic interference based on synchrosqueezed wavelet transform
    Xiang-Li Wang
    Chun-Lin Li
    Xin Yan
    Signal, Image and Video Processing, 2019, 13 : 397 - 403
  • [8] Improved Epoch Extraction From Speech Signals Using Wavelet Synchrosqueezed Transform
    Govind, D.
    Priya, S. Lakshmi
    Akarsh, S.
    Gowri, B. Ganga
    Soman, K. P.
    2019 25TH NATIONAL CONFERENCE ON COMMUNICATIONS (NCC), 2019,
  • [9] QRS Complex Detection in ECG Signals Using the Synchrosqueezed Wavelet Transform
    Sharma, Tanushree
    Sharma, Kamalesh K.
    IETE JOURNAL OF RESEARCH, 2016, 62 (06) : 885 - 892
  • [10] Primary Signal Suppression Based on Synchrosqueezed Wavelet Transform
    Wu L.
    Niu J.
    Wang Z.
    He S.
    Zhao Y.
    Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology, 2020, 42 (08): : 2045 - 2052