肌肉疲劳

  • 网络muscle fatigue;muscular fatigue;exercise-induced muscle fatigue;fatigue of muscle
肌肉疲劳肌肉疲劳
  1. 运动性肌肉疲劳和细胞pH

    Muscle fatigue and intracellular pH during exercise

  2. 静态运动负荷诱发肌肉疲劳过程中SEMG信号变化的生理机制

    Physiological Mechanisms of SEMG Signal Responses to Muscle Fatigue During Isometric Contractions

  3. 首先,建立适宜H反射诱发研究的大鼠神经肌肉疲劳模型。

    First , a rat neuromuscular fatigue model was established which fit for the study of evoking H reflex .

  4. 肌肉疲劳的EMG定量分析新方法

    A New Method for the Quantitative Analysis of EMG of Muscular Fatigue

  5. 静态运动负荷诱发局部肌肉疲劳和恢复过程中sEMG信号复杂度变化规律

    The sEMG Signal Complexity Changes during and following Local Muscle Fatigue Induced by Isometric Loading

  6. 静态负荷诱发肌肉疲劳后恢复期sEMG信号变化规律

    SEMG signal change characteristics during the short period of recovery after muscular fatigue with isometric contractions

  7. 肌肉疲劳的sEMG时频分析技术及其在工效学中的应用

    SEMG Time-frequency Analysis Techniques for Evaluation of Muscle Fatigue and It 's Application in Ergonomic Studies

  8. 小波包分析与人工神经网络相结合探索运动性肌肉疲劳过程中sEMG变化特征

    Study on Characteristics of sEMG Change during the Process of Muscle Fatigue Using Wavelet Packet Transformation and Artificial Neural Network

  9. 通过表面肌电信号的功率谱中值频率(f_(med))来监测局部肌肉疲劳,对人体的肱二头肌做了疲劳实验。

    This study was designed to monitor localized muscular fatigue with the power spectrum medium frequency of surface myoelectric signal , and test the muscular fatigue of body bices .

  10. 对12名被试的肌电疲劳阈(EMGFT)与通气无氧阈(VAT)和肌肉疲劳指数之间的关系进行研究。

    The relationship of EMGFT with VAT and muscle fatigue index on12 subjects was studied .

  11. 结论局部肌肉疲劳过程中MPF和MF下降率变化能够对相应关节最大肌力变化作出比较准确预测。

    Conclusion : The slope of MPF and MF during local muscle fatigue progress can be used to predict the corresponding joint muscle force changes .

  12. 结论:静态负荷诱发肌肉疲劳过程中sEMG的MPF和C(n)呈单调递减,DET%呈单调递增性变化,且变化斜率具有运动负荷强度依赖性;

    Conclusion : Both MPF and C ( n ) of sEMG decreased linearly while DET % increase linearly during isometric exercise-induced local muscle fatigue . And the slopes of them showed significant load dependence .

  13. 研究目的在于探讨不同强度等长运动诱发肌肉疲劳过程中sEMG非线性信号变化特征及其与肌肉运动耐力的关系。

    This study was particularly designed to evaluate the relation between character of sEMG signal and muscle exercise endurance at different intensity during exhaustive isometric muscle contraction .

  14. 中医消除运动性肌肉疲劳临床实验研究之二&人体骨骼肌两周离心运动对血液IL-1β、IL-2和β-EP的影响

    Clinic Experiment of Eliminating Exercise-induced Muscular Fatigue by Traditional Chinese Medicine ( TCM ) - Effects of Internal and External TCM on IL-1 β、 IL-2 ?β - EP in Blood after Two-week Eccentric Muscle Training in Man

  15. 所检神经对应的肌肉疲劳后,再以上述频率和电流重复进行RNS检查。

    After the correspondent muscles to the tested nerves fatigued , the RNS test was repeated with the mentioned above frequency and current one by one .

  16. 目的:通过分析双侧股内侧肌疲劳时表面肌电图(SEMG)信号特征,探讨利用SEMG评价肌肉疲劳的新方法,拓展表面肌电图的临床应用。

    Objective To explore a new method for evaluating muscle fatigue by analyzing the surface electromyographic ( SEMG ) signal characteristics and to search for the practical use of SEMG .

  17. 其次,建立人体神经肌肉疲劳模型,应用运动训练、间歇性低氧训练等干预手段,观察低氧训练前后以及疲劳恢复过程中H反射参数的变化。

    Second , a model of human neuromuscular fatigue was established . Intervention studies of treadmill training and IHT were also applied in this model in order to observe the changes of H reflex parameters before and after neuromuscular fatigue and during the recovery of neuromuscular fatigue .

  18. 在此基础上确定特异性和可靠性良好的表征肌肉疲劳的SEMG指标,为进一步应用这些指标评价肌肉功能状态提供理论依据。

    We look for indicators of SEMG which are correct , reliable and easy to interpret with this understanding and try to provide theoretic reference for the applications of these indicators .

  19. 认为用sEMG信号的时频分析评估驾驶员肌肉疲劳状态是可行的。

    It is concluded that lumbar fatigue of drivers increased after simulated driving and it was feasible to evaluate drivers ' lumbar fatigue via sEMG signals based on time - and frequency-domain analysis .

  20. 为了评价周期性动态收缩期间的局部肌肉疲劳,针对肌肉动态收缩时表面肌电信号的特点,提出了基于互Wigner-Ville分布的瞬时频率检测方法。

    To evaluate muscle fatigue during cyclic dynamic contraction , according to the features of surface myoelectric signal during dynamic contraction , an instantaneous frequency detection technique based on cross Wigner-Ville distribution is proposed .

  21. 通过研究静态持续收缩和动态重复收缩过程中肌电信号的演化模式相对概率和Dreg的变化,揭示了肌肉疲劳进程中肌电信号趋于规则性变化的规律。

    By studying changes in the relative probability of EPs and Dreg of SEMG signals during both static sustained contractions and dynamic repetitive contractions , we find out that SEMG tends to be more regular with fatigue progressing .

  22. 肌电指标(如MVE%,MF,MPF及其斜率)在操作过程中的变化可以反映动态劳动的肌肉疲劳,JASA分析证实了这一点。

    The EMG parameters such as MVE % , MF and MPF , and especially their changes during the performance were still able in indicating muscle fatigue during repetitive work , which was demonstrated further by the JASA method .

  23. 目的:肌肉疲劳的问题自100多年前莫桑(MOSSO)开始研究以来,一直是运动医学关注的热点。

    Objective : The problem of muscle fatigue from 100 years ago Moissanite ( MOSSO ) began to study , has been the focus of attention of Sports Medicine .

  24. 作为一类特殊类型肌肉疲劳,目前DOMS的研究主要是围绕其产生原因与机理,对机体的影响以及如何有效消除不利因素等方面进行的。

    As one special type of muscular fatigue , the present studies on DOMS mainly focused on several aspects , such as its creation reason and mechanism , the studies relating to the effects of DOMS on the body and how to remove unfavorable factors effectively were rarely seen .

  25. 局部肌肉疲劳的表面肌电信号复杂度和熵变化

    SEMG signal complexity and entropy changes during exercise-induced local muscle fatigue

  26. 有关核磁共振研究肌肉疲劳的进展

    The Development of Research on Muscle Fatigue with Nuclear Magnetic Resonance

  27. 股四头肌作等长收缩时的粘弹性分析等长收缩诱发肌肉疲劳及恢复过程中表面肌电信号特征变化规律

    Changes of sEMG parameters during isometric fatiguing contractions and recovery period

  28. 女性压力性尿失禁与神经-肌肉疲劳关系的研究

    The Relationship Between Nerve-muscle Fatigue and Stress Urinary Incontinence in Women

  29. 肌肉疲劳过程中电诱发表面肌电信号的小波分析

    Wavelet Analysis of Electrically Evoked Surface Electromyography Signals During Muscle Fatigue

  30. 利用表面肌电信号评价肌肉疲劳的方法

    Methods Applied to Muscle Fatigue Assessment Using Surface Myoelectric Signals