The study was aimed at exploring informative value of nonlinear parameters of surface electromyogram (sEMG) to characterization of neuromuscular activity in respect with duration of space flight (SF) and stepping mode. The working hypothesis held that sEMG entropy, correlation dimension (CD), and Lyapunov's exponent, which characterize signals in terms of regularity and predictability, may inform on motor units (MUs) synchronization or content of MUs of different types in muscle activity. In addition, median frequency (MDF), mean amplitude, and kurtosis of of the probability distribution of sEMG were computed. sEMG samples were collected from the soleus of 6 cosmonauts on board of the International Space Station during 5 modes of stepping on the passive-mode treadmill in the MO-3 test, and 5 study points - before and after SF on ground (preSF, postSF) and for 3 periods of time in SF (1–80, 81–120, 120–170 days of SF). Altogether, 15 individual sEMG sample sets were successfully obtained. It was found that 1) the sEMG parameters pooled for all subjects by the stepping mode, except for MDF and kurtosis, did modify in the direction of higher regularity of the signal with growing speed of stepping, 2) the conditions of SF exerted effect on MDF, Lyapunov's exponent, entropy, and kurtosis of the probability distribution of sEMG, which probably indicated on greater involvement of the faster type motor units in muscle activity. In conclusion, nonlinear sEMG parameters look promising for characterizing the neuromuscular activity of skeletal muscles under SF conditions. Nonetheless, a small number of sample sets combined with different study points in different cosmonauts allow considering these facts as promising, but not yet definitely established.

该研究旨在探索表面肌电图 (sEMG) 的非线性参数在空间飞行持续时间 (SF) 和步进模式方面对表征神经肌肉活动的信息价值。工作假设认为，sEMG 熵、相关维数 (CD) 和 Lyapunov 指数，它们在规律性和可预测性方面表征信号，可能会告知运动单位 (MU) 同步或肌肉活动中不同类型 MU 的内容。此外，还计算了 sEMG 概率分布的中值频率 (MDF)、平均幅度和峰度。sEMG 样本是在 MO-3 测试中在被动模式跑步机上的 5 种踩踏模式期间从国际空间站上 6 名宇航员的比目鱼肌采集的，以及 5 个研究点——在地面 SF 之前和之后（preSF，SF 后）和 SF 中的 3 个时间段（SF 的 1-80、81-120、120-170 天）。总共成功获得了 15 个单独的 sEMG 样本集。发现 1) 除 MDF 和峰度外，通过步进模式汇集的所有受试者的 sEMG 参数确实随着步进速度的增长而朝着信号的更高规律性方向改变，2) SF 的条件对MDF、Lyapunov 的指数、熵和 sEMG 概率分布的峰度，这可能表明更快类型的运动单位更多地参与肌肉活动。总之，非线性 sEMG 参数看起来很有希望用于表征 SF 条件下骨骼肌的神经肌肉活动。尽管如此，