Predicting kinetic outcomes from limb kinematics and muscle activation patterns

根据肢体运动学和肌肉激活模式预测动力学结果

• 批准号: 42545-2008
• 负责人: Morin, Evelyn
• 金额: $ 1.31万
• 依托单位: Queen's University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2011
• 资助国家: 加拿大
• 起止时间: 2011-01-01 至 2012-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=474970
• 关键词: Predicting; kinetic; outcomes; limb; kinematics

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.

作为人类，我们能够与环境互动，因为我们的肌肉收缩并产生力和/或关节运动。由肌肉作用在一个关节（例如手肘）周围引起的旋转力或扭矩可以转化为沿着肢体（例如手腕或手）的另一点处的线性力，从而允许我们将这些力施加到环境中的物体并执行任务，例如举起咖啡杯或杂货袋。一般来说，几块肌肉作用于单个关节。例如手肘由屈肌（肱二头肌、肱肌和肱桡肌）和伸肌（肱三头肌）控制，屈肌的作用是减小关节角度并将手腕拉向肩部，伸肌的作用是伸直手臂。为了完成任务，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水平以及关节位置和运动速度的函数。为了了解这些因素之间的相互关系，已经做了很多工作，并开发了几种模型。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，新的数学技术将被应用到建模的生产力在手腕上，由于手肘产生的扭矩。这些技术将结合生理信息，允许评估个体肌肉的贡献水平和形式以及关节参数（位置和速度）对力的产生的影响，并提供输出力的可靠预测。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，这些模型可以应用于了解身体运动和力量的控制是如何受到伤害或疾病的影响，在改进的康复策略的设计，并用于控制辅助设备，如假肢，它提供了与环境的远程交互。