Assessing the SNR Influence in the Estimation of the Mean Frequency of Lower Limbs sEMG Signals

被引:6
|
作者
Rojas, A. [1 ]
Farfan, A. [1 ]
Mora, E. [2 ]
Minchala, L., I [3 ,4 ]
Wong, S. [3 ]
机构
[1] Univ Cuenca, Cuenca, Ecuador
[2] Univ Cuenca, Dept Elect Elect & Telecommun Engn DEET, Cuenca, Ecuador
[3] Univ Cuenca, Dept Elect Elect & Telecommun Engn, Cuenca 010150, Ecuador
[4] Tecnol Monterrey, Monterrey 64849, Mexico
关键词
Electromyographic; signal to noise ratio; mean frequency; lower limbs; ELECTROMYOGRAPHIC ACTIVITY; MUSCLE; FATIGUE; TIME; EMG; FORCE;
D O I
10.1109/TLA.2018.8528223
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The mean frequency of the power spectrum (MNF) is commonly used to describe the frequency content of an electromyographic (EMG) signal. The objective of this study is to determine the minimum/desirable signal to noise ratio (SNR) value to achieve a reliable measurement of the MNF in superficial EMG (sEMG) signals of lower limbs during gait. To this end, measurements of MNF and SNR were taken in nine muscles of 21 healthy subjects, and recorded signals were contaminated with different noise levels. The minimum threshold of a desirable SNR was determined using the K-means algorithm. A lower bound of 10.11 dB was determined as the SNR value for sEMG acquisition, while 15.78 dB is the minimum SNR value desired for recording sEMG signals. The methodology presented throughout this paper helps in the determination of the minimum SNR value necessary to validate the sEMG acquisition process that can be used, for example, as a control signal for identifying motion intention in the development of control systems devoted for a lower limb exoskeleton.
引用
收藏
页码:2108 / 2114
页数:7
相关论文
共 47 条
  • [1] Estimation of mean and median frequency from synthetic sEMG signals: Effects of different spectral shapes and noise on estimation methods
    Corvini, Giovanni
    D'Anna, Carmen
    Conforto, Silvia
    BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2022, 73
  • [2] Motion Intention Estimation of Lower Limbs Based on sEMG Supplement with Acceleration Signal
    Zhao, Xingang
    Wang, Rui
    Ye, Dan
    2015 27TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2015, : 4414 - 4418
  • [3] A Simulation Study to Assess the Factors of Influence on Mean and Median Frequency of sEMG Signals during Muscle Fatigue
    Corvini, Giovanni
    Conforto, Silvia
    SENSORS, 2022, 22 (17)
  • [4] Mean frequency estimation of narrowband signals
    Fernando, KL
    Mathews, VJ
    Clark, EB
    IEEE SIGNAL PROCESSING LETTERS, 2004, 11 (02) : 175 - 178
  • [5] Mean Frequency and Noise from Patients with Pathologies in Lower Limbs
    Minchala, Luis, I
    Mora-Tola, Esteban
    Wong, Sara
    Astudillo-Salinas, Fabian
    Vazquez-Rodas, Andres
    Cardenas, Veronica
    Ayavaca, Maria
    2020 7TH INTERNATIONAL CONFERENCE ON CONTROL, DECISION AND INFORMATION TECHNOLOGIES (CODIT'20), VOL 1, 2020, : 1123 - 1126
  • [6] SNR Estimation for OFDM Signals in Frequency Selective Fading Channels
    Liu, Yu
    Zhang, Tian-qi
    Li, Can
    Zhang, Ya-juan
    2014 7TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING (CISP 2014), 2014, : 1068 - 1072
  • [7] Blind estimation of the PN sequence in lower SNR DS/SS signals
    Zhang, TQ
    Lin, XK
    Zhou, ZZ
    IEICE TRANSACTIONS ON COMMUNICATIONS, 2005, E88B (07) : 3087 - 3089
  • [8] An Efficient Algorithm for Instantaneous Frequency Estimation of Nonstationary Multicomponent Signals in Low SNR
    Lerga, Jonatan
    Sucic, Victor
    Boashash, Boualem
    EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING, 2011,
  • [9] Joint NDA Estimation of Carrier Frequency/Phase and SNR for Linearly Modulated Signals
    Gappmair, Wilfried
    Lopez-Valcarce, Roberto
    Mosquera, Carlos
    IEEE SIGNAL PROCESSING LETTERS, 2010, 17 (05) : 517 - 520
  • [10] SNR Estimation of Time-Frequency Overlapped Signals for Underlay Cognitive Radio
    Wang, Jianghong
    Li, Bingbing
    Liu, Mingqian
    Li, Junfang
    IEEE COMMUNICATIONS LETTERS, 2015, 19 (11) : 1925 - 1928