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我们的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，以及对2D和3D目标指导的ARM运动的新实验结果。我们将利用该理论对感官控制中的几个重要问题进行新的启示：运动学和肌肉激活的规律性，特定于任务的阻抗以及对运动变异性的扰动，起源和结构的响应以及眼睛手动协调模式。除了基础研究外，该项目还涉及到具有直接应用健康的实质性生物工程组成部分。我们将构建人类手臂的详细肌肉骨骼模型，并开发能够实时实现行为目标的层次控制算法。然后，这种算法可用于控制功能性刺激器和机器人假体，从而恢复运动功能并改善残疾患者的生活质量。公共卫生相关性：我们将开发出关于大脑如何控制手臂运动的一般数学理论。对运动功能的更好理论理解可以促进设计新治疗的运动障碍。我们还将开发自动控制算法，这些算法可以使用大脑提取的信号来使假肢实现所需的运动目标。