Estimation of Muscle Fiber Direction by Multi-channel Surface EMG Conductiong Wave Analysis Using Grid Surface Electrodes

被引:0
|
作者
Kosuge T. [1 ]
Kawaguchi T. [1 ]
Kumagai H. [1 ]
机构
[1] School of Allied Health Sciences, Kitasato University, 1-15-1, Kitasato, Minami-ku, Kanagawa, Sagamihara
关键词
Action Potential; Grid Surface Electrodes; Motor Unit; surface EMG;
D O I
10.1541/ieejeiss.143.413
中图分类号
学科分类号
摘要
Skeletal muscle is a set of motor units (MU). Muscle contractile activity is carried out by regulating the firing frequency of MU and the types of muscle fibers to be mobilized. Multi-channel surface electromyogram (sEMG) contains many conducting waves that represent a single motor unit action potentials (MUAP). In previous study, we proposed a method to extract conducting waves quantitatively and automatically. This method is useful for elucidating mobilized MUs and can be applied to kinematic analysis and diagnosis of muscle diseases. In multi-channel sEMG measurement, rows of electrodes need to be applied along the direction of the muscle fibers. However, the electrodes are difficult to set because the direction of the muscle fibers cannot be visually confirmed on the skin. This study investigated a method for estimating muscle fiber direction by analyzing conducting waves from two-dimensional multichannel surface electromyograms using grid-shaped surface electrodes. By examining the number of conducting waves acquired in each direction of the electrode row, it was suggested that the direction of muscle fiber may be estimated from the direction with the largest number of propagating wave acquisitions. It was also found that the method of acquiring differential potential signals has a significant impact on the analysis of propagation direction. © 2023 The Institute of Electrical Engineers of Japan.
引用
收藏
页码:413 / 419
页数:6
相关论文
共 50 条
  • [1] Relationship between conducting wave and muscle thickness in multi-channel surface EMG
    Kosuge T.
    Yamada K.
    Kumagai H.
    IEEJ Transactions on Electronics, Information and Systems, 2021, 141 (04) : 525 - 531
  • [2] Analysis of Conducting Waves Using Multi-channel Surface EMG Depends on Electrodes in Multiple Directions
    Okura, Kohei
    Mizuno, Tota
    Matsumoto, Yu
    Mito, Kazuyuki
    Itakura, Naoaki
    IEEJ Transactions on Electronics, Information and Systems, 2024, 144 (11) : 1108 - 1115
  • [3] Analysis of conducting waves using multi-channel surface EMG depends on difference in shape of electrodes
    Okura K.
    Mizuno T.
    Farahani M.A.
    Matsumoto Y.
    Mito K.
    Itakura N.
    IEEJ Transactions on Electronics, Information and Systems, 2021, 141 (04): : 539 - 545
  • [4] Analysis of end-plate using multi-channel surface EMG
    Marzieh Aliabadi Farahani
    Hiroki Yamada
    Kota Akehi
    Kazuyuki Mito
    Tota Mizuno
    Naoaki Itakura
    Artificial Life and Robotics, 2019, 24 : 390 - 395
  • [5] Analysis of end-plate using multi-channel surface EMG
    Farahani, Marzieh Aliabadi
    Yamada, Hiroki
    Akehi, Kota
    Mito, Kazuyuki
    Mizuno, Tota
    Itakura, Naoaki
    ARTIFICIAL LIFE AND ROBOTICS, 2019, 24 (03) : 390 - 395
  • [6] Surface EMG and muscle fatigue: multi-channel approaches to the study of myoelectric manifestations of muscle fatigue
    Marco, Gazzoni
    Alberto, Botter
    Taian, Vieira
    PHYSIOLOGICAL MEASUREMENT, 2017, 38 (05) : R27 - R60
  • [7] Multi-Channel Surface Electromyography Electrodes: A Review
    Kilby, Jeff
    Prasad, Krishnamachar
    Mawston, Grant
    IEEE SENSORS JOURNAL, 2016, 16 (14) : 5510 - 5519
  • [8] Automatic location of muscle innervation zones from multi-channel surface EMG signals
    Cescon, Corrado
    2006 IEEE INTERNATIONAL WORKSHOP ON MEDICAL MEASUREMENT AND APPLICATIONS, 2006, : 87 - 90
  • [9] Noninvasive imaging of internal muscle activities from multi-channel surface EMG recordings
    Zhang, Yingchun
    2013 35TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2013, : 5430 - 5432
  • [10] A new approach for multi-channel surface EMG signal simulation
    Ning Y.
    Zhang Y.
    Biomedical Engineering Letters, 2017, 7 (1) : 45 - 53