A neuromechanical approach to define muscle recruitment strategies and control of the upper limb

定义肌肉募集策略和上肢控制的神经力学方法

• 批准号: RGPIN-2015-05765
• 负责人: Holmes, Michael
• 金额: $ 2.11万
• 依托单位: Brock University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=653783
• 关键词: neuromechanical; approach; define; muscle; recruitment

To complete most activities of daily living we must coordinate limb movements through the control of muscles in the upper extremity. As humans, we continuously interact with tools and objects in our environment and we are often presented with situations where objects and tools apply variable forces and torques to the hand. This further challenges our ability to provide control. Muscle actions must counter an external disturbance and these actions are governed by the central nervous system and depend on the external conditions, task demands and limb posture. Biomechanical characteristics partially dictate roles for each muscle, but mechanical output is ultimately a consequence of signals sent by the central nervous system to the muscle. These neuromechanical aspects need to be considered to fully understand the links between motor commands, neural activity and limb mechanics. My research implements an approach to the development of a paradigm that better understands how the central nervous system controls hand and arm motion during workplace related tasks. The workplace provides a unique environment to study these changes since both fine and gross motor skills are needed daily to perform upper extremity tasks. This work uses perturbation experiments and fatigue protocols to simulate workplace demands and then uses electrical stimulation techniques (including transcranial magnetic stimulation, nerve and muscle stimulation) and computer modelling to bridge the gap between neural and biomechanical factors. Focusing on the manipulation of individual muscle parameters (force, length, velocity and fatigue) this work evaluates recruitment strategies due to changes in muscle mechanics and muscle roles (co-activation vs. antagonists). Muscle recruitment and control strategies will be determined such that a framework for identifying co-contraction and synergist muscle actions are established. This work is novel and spans several disciplines to evolve our understanding of how the central nervous system drives muscles to perform actions. This work is important to industrial applications and will lead to improved human factors and engineering of both the workplace and of tool design.

为了完成日常生活的大部分活动，我们必须通过控制上肢肌肉来协调肢体运动。作为人类，我们不断地与环境中的工具和物体互动，我们经常遇到物体和工具对手施加可变力和扭矩的情况。这进一步挑战了我们提供控制的能力。肌肉运动必须对抗外部干扰，这些运动由中枢神经系统控制，并取决于外部条件、任务要求和肢体姿势。生物力学特征部分决定了每块肌肉的作用，但机械输出最终是中枢神经系统向肌肉发送信号的结果。为了充分理解运动指令、神经活动和肢体力学之间的联系，需要考虑这些神经力学方面。我的研究实现了一种开发范式的方法，该范式可以更好地理解中枢神经系统如何在工作场所相关任务中控制手和手臂的运动。工作场所为研究这些变化提供了一个独特的环境，因为每天都需要精细和大肌肉运动技能来执行上肢任务。这项工作使用扰动实验和疲劳协议来模拟工作场所的需求，然后使用电刺激技术（包括经颅磁刺激、神经和肌肉刺激）和计算机建模来弥合神经和生物力学因素之间的差距。关注单个肌肉参数（力、长度、速度和疲劳）的操纵，本工作评估了由于肌肉力学和肌肉作用（共激活与拮抗剂）变化而产生的招募策略。将确定肌肉招募和控制策略，以便建立识别共同收缩和协同肌肉动作的框架。这项工作是新颖的，跨越了几个学科，以发展我们对中枢神经系统如何驱动肌肉执行动作的理解。这项工作对工业应用非常重要，并将改善工作场所和工具设计的人为因素和工程。