Lyu Chenglin, Panteli Georgios, Bollheimer L Cornelius, Leonhardt Steffen, von Platen Philip
Annu Int Conf IEEE Eng Med Biol Soc. 2024 Jul;2024:1-4. doi: 10.1109/EMBC53108.2024.10782626.
Functional Electrical Stimulation (FES) plays a crucial role in the rehabilitation and mobility of patients, but it introduces muscle fatigue which can impact the treatment process. This work presents a novel approach for monitoring FES-induced muscle fatigue and recovery by torque and surface electromyography (sEMG) signals. A predefined pattern of FES is applied on the rectus femoris muscle to induce isometric contraction, while torque and sEMG data are collected to assess muscle fatigue and subsequent recovery. The sEMG data are filtered using notch stop and high-pass filters, and subsequently assessed in both the time domain (Root Mean Square, RMS) and frequency domain (mean frequency). The results indicated that torque and RMS decreased during fatigue and increased during recovery, while the mean frequency of the sEMG signal exhibited an opposite trend. These findings provide valuable insights into the dynamics of muscle fatigue under FES and have implications for enhancing the understanding and management of muscle fatigue in rehabilitation therapy.
功能性电刺激（FES）在患者康复和行动能力方面发挥着关键作用，但它会引发肌肉疲劳，进而影响治疗过程。这项研究提出了一种通过扭矩和表面肌电图（sEMG）信号监测FES诱发的肌肉疲劳及恢复情况的新方法。将预定义的FES模式施加于股直肌以诱发等长收缩，同时收集扭矩和sEMG数据来评估肌肉疲劳及随后的恢复情况。sEMG数据使用陷波和高通滤波器进行滤波，随后在时域（均方根，RMS）和频域（平均频率）进行评估。结果表明，疲劳期间扭矩和RMS下降，恢复期间上升，而sEMG信号的平均频率呈现相反趋势。这些发现为FES作用下肌肉疲劳的动态变化提供了有价值的见解，并对加强康复治疗中肌肉疲劳的理解和管理具有重要意义。
