Dept. ESAII, Universitat Politècnica de Catalunya, Barcelona, Spain.
J Electromyogr Kinesiol. 2013 Jun;23(3):548-57. doi: 10.1016/j.jelekin.2012.12.007. Epub 2013 Feb 19.
The study of the amplitude of respiratory muscle mechanomyographic (MMG) signals could be useful in clinical practice as an alternative non-invasive technique to assess respiratory muscle strength. The MMG signal is stochastic in nature, and its amplitude is usually estimated by means of the average rectified value (ARV) or the root mean square (RMS) of the signal. Both parameters can be used to estimate MMG activity, as they correlate well with muscle force. These estimations are, however, greatly affected by the presence of structured impulsive noise that overlaps in frequency with the MMG signal. In this paper, we present a method for assessing muscle activity based on the Lempel-Ziv algorithm: the Multistate Lempel-Ziv (MLZ) index. The behaviour of the MLZ index was tested with synthesised signals, with various amplitude distributions and degrees of complexity, and with recorded diaphragm MMG signals. We found that this index, like the ARV and RMS parameters, is positively correlated with changes in amplitude of the diaphragm MMG components, but is less affected by components that have non-random behaviour (like structured impulsive noise). Therefore, the MLZ index could provide more information to assess the MMG-force relationship.
呼吸肌肌动描记术（MMG）信号幅度的研究可能在临床实践中作为一种替代的非侵入性技术来评估呼吸肌力量有用。MMG 信号本质上是随机的，其幅度通常通过平均整流值（ARV）或信号的均方根值（RMS）来估计。这两个参数都可以用于估计 MMG 活动，因为它们与肌肉力量很好地相关。然而，这些估计受到与 MMG 信号重叠的结构化脉冲噪声的存在的极大影响。在本文中，我们提出了一种基于 Lempel-Ziv 算法的肌肉活动评估方法：多状态 Lempel-Ziv（MLZ）指数。使用具有不同幅度分布和复杂程度的合成信号以及记录的膈肌 MMG 信号对 MLZ 指数的行为进行了测试。我们发现，该指数与膈肌 MMG 分量幅度变化呈正相关，与具有非随机行为的分量（如结构化脉冲噪声）相比，该指数受其影响较小。因此，MLZ 指数可以提供更多信息来评估 MMG-力关系。
