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首页> 外文期刊>Journal of NeuroEngineering Rehabilitation >Development of a mathematical model for predicting electrically elicited quadriceps femoris muscle forces during isovelocity knee joint motion
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Development of a mathematical model for predicting electrically elicited quadriceps femoris muscle forces during isovelocity knee joint motion

机译：预测等速膝关节运动过程中电诱发股四头肌肌力的数学模型的开发

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Background Direct electrical activation of skeletal muscles of patients with upper motor neuron lesions can restore functional movements, such as standing or walking. Because responses to electrical stimulation are highly nonlinear and time varying, accurate control of muscles to produce functional movements is very difficult. Accurate and predictive mathematical models can facilitate the design of stimulation patterns and control strategies that will produce the desired force and motion. In the present study, we build upon our previous isometric model to capture the effects of constant angular velocity on the forces produced during electrically elicited concentric contractions of healthy human quadriceps femoris muscle. Modelling the isovelocity condition is important because it will enable us to understand how our model behaves under the relatively simple condition of constant velocity and will enable us to better understand the interactions of muscle length, limb velocity, and stimulation pattern on the force produced by the muscle. Methods An additional term was introduced into our previous isometric model to predict the force responses during constant velocity limb motion. Ten healthy subjects were recruited for the study. Using a KinCom dynamometer, isometric and isovelocity force data were collected from the human quadriceps femoris muscle in response to a wide range of stimulation frequencies and patterns. % error, linear regression trend lines, and paired t-tests were used to test how well the model predicted the experimental forces. In addition, sensitivity analysis was performed using Fourier Amplitude Sensitivity Test to obtain a measure of the sensitivity of our model's output to changes in model parameters. Results Percentage RMS errors between modelled and experimental forces determined for each subject at each stimulation pattern and velocity showed that the errors were in general less than 20%. The coefficients of determination between the measured and predicted forces show that the model accounted for ~86% and ~85% of the variances in the measured force-time integrals and peak forces, respectively. Conclusion The range of predictive abilities of the isovelocity model in response to changes in muscle length, velocity, and stimulation frequency for each individual make it ideal for dynamic applications like FES cycling.
机译：背景技术上运动神经元病变患者的骨骼肌直接电激活可以恢复功能性运动，例如站立或行走。由于对电刺激的响应高度非线性且随时间变化，因此精确控制肌肉以产生功能性运动非常困难。准确的和预测性的数学模型可以促进刺激模式和控制策略的设计，从而产生所需的力和运动。在当前的研究中，我们以以前的等距模型为基础，以捕捉恒定角速度对健康人股四头肌肌肉电诱发的同心收缩过程中产生的力的影响。对等速条件进行建模很重要，因为它将使我们能够了解模型在恒定速度的相对简单条件下的行为，并使我们能够更好地理解肌肉长度，肢体速度和刺激模式对由肌肉产生的力的相互作用。肌肉。方法我们在以前的等距模型中引入了一个附加术语，以预测等速肢体运动期间的力响应。招募了十名健康受试者进行研究。使用KinCom测力计，响应各种刺激频率和模式，从人类股四头肌收集等距和等速力数据。误差百分比，线性回归趋势线和配对t检验用于测试模型预测实验力的能力。此外，使用傅立叶振幅灵敏度测试执行灵敏度分析，以衡量我们模型输出对模型参数变化的敏感性。结果在每个刺激模式和速度下，针对每个受试者确定的模型力和实验力之间的RMS误差百分比表明，误差通常小于20％。测得力和预测力之间的确定系数表明，该模型分别占测得力-时间积分和峰值力的方差的〜86％和〜85％。结论等速模型对每个人的肌肉长度，速度和刺激频率变化的预测能力范围使其非常适合动态应用（如FES循环）。

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