Optimal feedback control of goal-directed arm movements

目标导向手臂运动的最佳反馈控制

• 批准号: 7795668
• 负责人: Emanuel Todorov
• 金额: $ 20.27万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-04-01 至 2012-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7795668
• 关键词: Affect; Algorithms; Basic Science; Behavior; Behavioral; Brain; Complex; Data; Disabled Persons; Electric Stimulation; Engineering; Environment; Equilibrium; Feedback; Funding; Goals; Health; Human; Light; Literature; Methods; Modeling; Motor; Movement; Movement Disorders; Muscle; Musculoskeletal; Musculoskeletal System; Noise; Outcome; Patients; Pattern; Prosthesis; Psychophysiology; Quality of life; Research Project Grants; Robotics; Sensorimotor functions; Sensory; Signal Transduction; Structure; System; Time; Work; arm; computerized tools; data modeling; design; direct application; electric impedance; eye hand coordination; improved functioning; kinematics; mathematical theory; mind control; novel; public health relevance; research study; response; simulation; theories

DESCRIPTION (provided by applicant): We propose to further develop our optimal feedback control theory of motor coordination, and utilize its potential to explain known phenomena and as well as novel experimental results on goal-directed arm movements in 2D and 3D. We will use the theory to shed new light on several important issues in sensorimotor control: regularities in kinematics and muscle activations, task-specific impedance and responses to perturbations, origins and structure of motor variability, and eye-hand coordination patterns. In addition to basic research, the project involves a substantial bio-engineering component with direct applications to health. We will construct detailed musculoskeletal models of the human arm and develop hierarchical control algorithms capable of making the model arm accomplish behavioral goals in real time. Such algorithms can then be used to control functional electric stimulators and robotic prostheses, and thereby restore motor function and improve the quality of life of disabled patients. PUBLIC HEALTH RELEVANCE: We will develop a general mathematical theory of how the brain controls arm movements. Better theoretical understanding of motor function can facilitate the design of new treatments for movement disorders. We will also develop automatic control algorithms that can use signals extracted from the brain to make a prosthetic arm accomplish desired movement goals.

描述（由申请人提供）：我们建议进一步发展运动协调的最佳反馈控制理论，并利用其潜力来解释已知现象以及 2D 和 3D 目标导向手臂运动的新颖实验结果。我们将利用该理论来阐明感觉运动控制中的几个重要问题：运动学和肌肉激活的规律性、任务特异性阻抗和对扰动的响应、运动变异性的起源和结构以及眼手协调模式。除了基础研究外，该项目还涉及直接应用于健康的重要生物工程部分。我们将构建详细的人类手臂肌肉骨骼模型，并开发能够使模型手臂实时完成行为目标的分层控制算法。然后，此类算法可用于控制功能性电刺激器和机器人假肢，从而恢复运动功能并提高残疾患者的生活质量。公共健康相关性：我们将开发一种关于大脑如何控制手臂运动的通用数学理论。对运动功能更好的理论理解可以促进运动障碍新疗法的设计。我们还将开发自动控制算法，可以使用从大脑提取的信号来使假肢完成所需的运动目标。