Predicting kinetic outcomes from limb kinematics and muscle activation patterns

作为人类，我们能够与我们的环境互动，因为我们的肌肉收缩并产生力量和/或围绕关节运动。肌肉围绕一个关节(如肘关节)所产生的旋转力或扭矩，可以转化为肢体上另一个点(如手腕或手)的线性力，使我们能够将这些力施加到环境中的物体上，并执行任务，如举起咖啡杯或杂货袋。一般来说，几块肌肉作用于一个单独的关节。例如，肘部由屈肌(二头肌、肱二头肌和肱二头肌)和伸肌(三头肌)控制，屈肌减小关节角度并将手腕拉向肩膀，伸肌(三头肌)伸直手臂。为了完成一项任务，中枢神经系统(CNS)以协调的方式激活相关肌肉。由于肌肉和肌肉骨骼系统的生物力学特性，单个肌肉产生的力是其激活程度以及关节位置和运动速度的函数。人们已经做了很多工作来了解这些因素之间的相互关系，并开发了几个模型。然而，这些模型不能完全解释输出力的产生或肌肉激活与关节位置和速度的相互作用。在拟议的工作中，将应用新的数学技术来模拟手腕处由于肘部产生的扭矩而产生的力的产生。这些技术将结合生理信息，允许评估单个肌肉的贡献水平和形式，以及关节参数(位置和速度)对力量产生的影响，并提供可靠的输出力预测。这将提高我们对中枢神经系统如何控制运动任务的理解。在未来，这些模型可以用来理解身体运动和力量的控制如何受到伤害或疾病的影响，用于改进康复策略的设计，以及用于控制辅助设备，例如提供与环境远程交互的假肢。

As humans, we are able interact with our environment because our muscles contract and produce force and/or movement about a joint. A rotational force, or torque, caused by muscles acting about one joint, e.g. the elbow, can translate to a linear force at another point along the limb, e.g. the wrist or hand, allowing us to apply these forces to objects in the environment and perform tasks, such as lifting a coffee cup or a bag of groceries. In general, several muscles act on an individual joint. For example, the elbow is controlled by the flexor muscles (the biceps brachii, brachialis and brachioradialis) which act to decrease the joint angle and pull the wrist towards the shoulder, and an extensor muscle (the triceps brachii) which acts to straighten the arm. In order to perform a task, the central nervous system (CNS) activates the relevant muscles in a coordinated fashion. Because of the biomechanical characteristics of the muscles and the musculoskeletal system, the force produced by individual muscles is a function of their activation levels, as well as joint position and movement velocity. Much work has been done to understand the interrelationship between these factors and several models have been developed. However, these models do not fully explain the production of output force or the interaction of the muscle activations and joint position and velocity. In the proposed work, novel mathematical techniques will be applied to model the production of force at the wrist, due to torque generated at the elbow. These techniques will incorporate physiological information, permitting an evaluation of the level and form of contribution of the individual muscles and the effect of joint parameters (position and velocity) on the production of force, and providing a reliable prediction of output force. This will improve our understanding of how motor tasks are controlled by the CNS. In future these models could be applied to understand how control of body movements and forces are affected by injury or disease, in the design of improved rehabilitation strategies, and for use in control of assistive devices, e.g. prosthetic limbs, which provide remote interaction with the environment.