Ding Jun, Wexler Anthony S, Binder-Macleod Stuart A
Interdisciplinary Graduate Program in Biomechanics and Movement Science, University of Delaware, Newark 19716, USA.
IEEE Trans Neural Syst Rehabil Eng. 2002 Mar;10(1):48-58. doi: 10.1109/TNSRE.2002.1021586.
Previously we developed a mathematical force- and fatigue-model system that could predict fatigue produced by a wide range of frequencies and pulse patterns. However, the models tended to overestimate the forces produced by higher frequency trains. This paper presents modifications to our previously developed force- and fatigue-model system to improve the accuracy in predicting forces during repetitive activation of human skeletal muscle. By comparing the predictions produced by the modified force and fatigue models to those by our previous models, the modification appears to be successful. The current force- and fatigue-model system accounts for about 93% variance in experimental data produced by fatigue protocols consisting of trains with a wide range of frequencies and pulse patterns. In addition, the present models successfully predict the effect of stimulation frequency and pulse pattern on muscle fatigue. The success of our current force- and fatigue-model system suggests its potential use in helping to identify the optimal activation pattern to use during the clinical application of functional electrical stimulation.
此前,我们开发了一个数学力与疲劳模型系统,该系统能够预测由多种频率和脉冲模式产生的疲劳。然而,这些模型往往高估了高频序列产生的力。本文介绍了对我们先前开发的力与疲劳模型系统的改进,以提高在预测人体骨骼肌重复激活过程中的力时的准确性。通过将改进后的力和疲劳模型产生的预测结果与我们先前模型的预测结果进行比较,这种改进似乎是成功的。当前的力与疲劳模型系统解释了由包含多种频率和脉冲模式的序列组成的疲劳方案所产生的实验数据中约93%的方差。此外,当前模型成功地预测了刺激频率和脉冲模式对肌肉疲劳的影响。我们当前的力与疲劳模型系统的成功表明其在帮助确定功能性电刺激临床应用中使用的最佳激活模式方面的潜在用途。