Hayashibe Mitsuhiro, Guiraud David, Poignet Philippe
INRIA Sophia-Antipolis -DEMAR Project and LIRMM, UMR5506 CNRS UM2, 161 Rue Ada - 34392 Montpellier Cedex 5, France.
Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:6530-3. doi: 10.1109/IEMBS.2009.5333147.
EMG-based muscle model has many applications in human-machine interface and rehabilitation robotics. For the muscular force estimation, so-called Hill-type model has been used in most of the cases. It has already shown its promising performance, however it is known as a phenomenological model considering only macroscopic physiology. In this paper, we discuss EMG-force estimation with the full physiology based muscle model in voluntary contraction. In addition to Hill macroscopic representation, a microscopic physiology description as stated by Huxley and Zahalak is integrated. It has significant meaning to realize the same kind of EMG-force estimation with multiscale physiology based model not with a phenomenological Hill model, because it brings the understanding of the internal biophysical dynamics and new insights about neuromuscular activations.
基于肌电图的肌肉模型在人机接口和康复机器人领域有许多应用。在大多数情况下，对于肌肉力量估计，使用的是所谓的希尔型模型。它已经展现出了良好的性能，然而它是一个仅考虑宏观生理学的唯象模型。在本文中，我们讨论在自主收缩中基于全生理学肌肉模型的肌电图 - 力量估计。除了希尔宏观表示之外，还整合了赫胥黎和扎哈拉克所阐述的微观生理学描述。用基于多尺度生理学的模型而非唯象的希尔模型来实现同类型的肌电图 - 力量估计具有重要意义，因为它能带来对内部生物物理动力学的理解以及关于神经肌肉激活的新见解。
