Literature DB >> 21846609

Measuring increase in synchronization to identify muscle endurance limit.

Dinesh K Kumar1, Sridhar P Arjunan, Ganesh R Naik.   

Abstract

Changes in surface electromyogram (sEMG) spectral content are commonly associated with localized muscle fatigue. However, the significance of the changes is only evident during pair-wise comparison and these can only be used for comparison between the rested and fatigued muscle and cannot be used for identifying the limit of muscle endurance without having the rested data for comparison. This is due to the large variations between sEMG at different levels of strengths of contraction, and between different people. This is further compounded when the contraction is not isometric but is cyclic because there is large variation of sEMG within each cycle. This research has developed a new sEMG based method for studying muscle fatigue and for identifying the limit of muscle endurance. It is based on motor unit synchronization and is called increase in synchronization (IIS) index. IIS index measures the level of independence between two channels of sEMG recorded from the muscle and is the log of the determinant of the global matrix ( log||G||) which is generated by performing independent component analysis on the two channels. The experimental results for biceps brachii demonstrate that when the muscle was rested, the two channels had a high degree of independence and the IIS index was greater than -0.7 (range -0.65 to -0.05). However, the channels became dependent as the muscles progressively fatigued and IIS index became less than -6.2 (range -7.8 to -6.3 ) at the limit of muscle endurance. This was irrespective of the contraction being isometric or cyclic, or of the level of muscle contraction.

Entities:  

Mesh:

Year:  2011        PMID: 21846609     DOI: 10.1109/TNSRE.2011.2163527

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  5 in total

1.  Inter-Gender sEMG Evaluation of Central and Peripheral Fatigue in Biceps Brachii of Young Healthy Subjects.

Authors:  Federico Meduri; Matteo Beretta-Piccoli; Luca Calanni; Valentina Segreto; Giuseppe Giovanetti; Marco Barbero; Corrado Cescon; Giuseppe D'Antona
Journal:  PLoS One       Date:  2016-12-21       Impact factor: 3.240

2.  Quantitative Analysis of EEG Power Spectrum and EMG Median Power Frequency Changes after Continuous Passive Motion Mirror Therapy System.

Authors:  Taewoong Park; Mina Lee; Taejong Jeong; Yong-Il Shin; Sung-Min Park
Journal:  Sensors (Basel)       Date:  2020-04-21       Impact factor: 3.576

3.  Spatiotemporal characteristics of lower back muscle fatigue during a ten minutes endurance test at 50% upper body weight in healthy inactive, endurance, and strength trained subjects.

Authors:  Christoph Anders; Tim Schönau
Journal:  PLoS One       Date:  2022-09-13       Impact factor: 3.752

4.  Computation and evaluation of features of surface electromyogram to identify the force of muscle contraction and muscle fatigue.

Authors:  Sridhar P Arjunan; Dinesh K Kumar; Ganesh Naik
Journal:  Biomed Res Int       Date:  2014-06-04       Impact factor: 3.411

5.  Electromyographic Patterns during Golf Swing: Activation Sequence Profiling and Prediction of Shot Effectiveness.

Authors:  Antanas Verikas; Evaldas Vaiciukynas; Adas Gelzinis; James Parker; M Charlotte Olsson
Journal:  Sensors (Basel)       Date:  2016-04-23       Impact factor: 3.576

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.