Levin O, Mizrahi J
Department of Biomedical Engineering, Technion-Israel Institute of Technology, Haifa, Israel.
IEEE Trans Rehabil Eng. 1999 Sep;7(3):301-14. doi: 10.1109/86.788467.
A major issue associated with functional electrical stimulation (FES) of a paralyzed limb is the decay with time of the muscle force as a result of fatigue. A possible means to reduce fatigue during FES is by using interrupted stimulation, in which fatigue and recovery occur in sequence. In this study, we present a model which enables us to evaluate the temporal force generation capacity within the electrically activated muscle during first stimulation fatigue, i.e., when the muscle is activated from unfatigued initial conditions, and during postrest stimulation, i.e., after different given rest durations. The force history of the muscle is determined by the activation as derived from actually measured electromyogram (EMG) data, and by the metabolic fatigue function expressing the temporal changes of muscle metabolites, from existing data acquired by in vivo 31P MR spectroscopy in terms of the inorganic phosphorus variables, Pi or H2PO4-, and by the intracellular pH. The model was solved for supra-maximal stimulation in isometric contractions separated by rest periods, and compared to experimentally obtained measurements. EMG data were fundamental for prediction of the ascending force during its posttetanic response. On the other hand, prediction of the decaying phase of the force was possible only by means of the metabolite-based fatigue function. The prediction capability of the model was assessed by means of the error between predicted and measured force profiles. The predicted force obtained from the model in first stimulation fatigue fits well with the experimental one. In postrest stimulation fatigue, the different metabolites provided different prediction capabilities of the force, depending on the duration of the rest period. Following rest duration of 1 min, Pi provided the best prediction of force; H2PO4- extended the prediction capacity of the model to up to 6 min and pH provided a reliable prediction for rest durations longer than 12 min. The results presented shed light on the roles of EMG and of metabolites in prediction of the force history of a paralyzed muscle under conditions where fatigue and recovery occur in sequence.
与瘫痪肢体的功能性电刺激(FES)相关的一个主要问题是,由于疲劳,肌肉力量会随时间衰减。在FES期间减少疲劳的一种可能方法是使用间断刺激,即疲劳和恢复依次发生。在本研究中,我们提出了一个模型,该模型使我们能够评估在首次刺激疲劳期间(即肌肉从未疲劳的初始状态被激活时)以及在休息后刺激期间(即在给定不同的休息持续时间之后)电激活肌肉内随时间变化的力量产生能力。肌肉的力量历史由从实际测量的肌电图(EMG)数据得出的激活情况、以及根据体内31P磁共振波谱学获取的现有数据,用表示肌肉代谢物随时间变化的代谢疲劳函数(依据无机磷变量Pi或H2PO4-以及细胞内pH值)来确定。该模型针对由休息期隔开的等长收缩中的超强刺激进行求解,并与实验获得的测量结果进行比较。EMG数据对于预测强直后反应期间力量的上升至关重要。另一方面,只有借助基于代谢物的疲劳函数才有可能预测力量的衰减阶段。通过预测和测量的力量曲线之间的误差来评估该模型的预测能力。从模型获得的首次刺激疲劳中的预测力量与实验结果吻合良好。在休息后刺激疲劳中,不同的代谢物根据休息期的持续时间提供了不同的力量预测能力。休息1分钟后,Pi对力量的预测最佳;H2PO4-将模型的预测能力扩展至长达6分钟,而pH值则为超过12分钟的休息持续时间提供了可靠的预测。所呈现的结果揭示了在疲劳和恢复依次发生的条件下,EMG和代谢物在预测瘫痪肌肉力量历史中的作用。