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Predicting kinetic outcomes from limb kinematics and muscle activation patterns

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:
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
项目状态:
已结题
起止时间:
2011-01-01 至 2012-12-31

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中文摘要
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英文摘要
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.
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