Knaflitz M, Bonato P
Dipartimento di Elettronica, Politecnico di Torina, Italy.
J Electromyogr Kinesiol. 1999 Oct;9(5):337-50. doi: 10.1016/s1050-6411(99)00009-7.
This paper discusses the assessment of the electrical manifestations of muscle fatigue during dynamic contractions. In the past, the study of muscle fatigue was restricted to isometric constant force contractions because, in this contraction paradigm, the myoelectric signal may be considered as wide sense stationary over epochs lasting up to two or three seconds, and hence classic spectral estimation techniques may be applied. Recently, the availability of spectral estimation techniques specifically designed for nonstationary signal analysis made it possible to extend the employment of muscle fatigue assessment to cyclic dynamic contractions, thus increasing noticeably its possible clinical applications. After presenting the basics of time-frequency distributions, we introduce instantaneous spectral parameters well suited to tracking spectral changes due to muscle fatigue, discuss the issues of quasi-stationarity and quasi-cyclostationarity, and present different strategies of signal analysis to be utilized with cyclic dynamic contractions. We present preliminary results obtained by analyzing data collected from paraspinal muscles during repetitive lift movements, from the first dorsal interosseus during abduction-adduction movements of the index finger, and from knee flexors and extensors during isokinetic exercise. In conclusion, data herein reported demonstrate that the described techniques allow for evidencing the electrical manifestations of muscle fatigue in different paradigms of cyclic dynamic contractions. We believe that the extension of the objective assessment of the electrical manifestations of muscle fatigue from static to dynamic contractions may increase considerably the interest of researchers and clinicians and open new application fields, as ergonomics and sports medicine.
本文讨论了动态收缩过程中肌肉疲劳的电表现评估。过去,肌肉疲劳的研究仅限于等长恒力收缩,因为在这种收缩模式下,肌电信号在持续两到三秒的时间段内可被视为广义平稳信号,因此可以应用经典的谱估计技术。最近,专门为非平稳信号分析设计的谱估计技术的出现,使得将肌肉疲劳评估扩展到周期性动态收缩成为可能,从而显著增加了其潜在的临床应用。在介绍了时频分布的基础知识后,我们引入了非常适合跟踪肌肉疲劳引起的频谱变化的瞬时频谱参数,讨论了准平稳性和准循环平稳性问题,并介绍了用于周期性动态收缩的不同信号分析策略。我们展示了通过分析在重复举升动作过程中从脊柱旁肌肉、食指外展 - 内收动作过程中从第一背侧骨间肌以及等速运动过程中从膝关节屈伸肌收集的数据所获得的初步结果。总之,本文报告的数据表明,所描述的技术能够在不同的周期性动态收缩模式中揭示肌肉疲劳的电表现。我们认为,将肌肉疲劳电表现的客观评估从静态收缩扩展到动态收缩,可能会极大地提高研究人员和临床医生的兴趣,并开辟新的应用领域,如人体工程学和运动医学。