Prosthesis Control by Forward Dynamic Simulation of the Intact Biomedical system

通过完整生物医学系统的正向动态仿真进行假肢控制

• 批准号: 8454556
• 负责人: Wendy M Murray
• 金额: $ 36.92万
• 依托单位: REHABILITATION INSTITUTE OF CHICAGO D/B/A SHIRLEY RYAN ABILITYLAB
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-04-05 至 2015-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8454556
• 关键词: Address; Algorithms; Amputation; Amputees; Biomechanics; Clinical; Complex; Data; Development; Devices; Ensure; Evaluation; Fingers; Forearm; Freedom; Goals; Hand; Hand functions; Human; Individual; Joints; Learning; Limb structure; Link; Manuals; Measures; Mechanics; Modeling; Motion; Motor; Movement; Muscle; Output; Performance; Persons; Physiological; Population; Posture; Prosthesis; Rehabilitation therapy; Residual state; Running; Sign Language; Signal Transduction; Simulate; Spinal cord injury; Stroke; System; Techniques; Thumb structure; Time; Work; Wrist; base; design; expectation; kinematics; meetings; motor control; public health relevance; simulation; theories

DESCRIPTION (provided by applicant): Persons with recent hand amputations expect modern hand prostheses to function like intact hands. Current state-of-the-art electric prosthetic hands are generally single degree-of-freedom (opening and closing) devices that are controlled using only two muscle signals. As a result, most state-of-the-art devices fail to meet user's expectations and are under-utilized or rejected. Because of this, advances in mechanical hardware are directed toward providing functionality comparable to the intact human hand. Despite such advances, the performance of sophisticated hand prostheses remains limited by the ability to control them via physiological (e.g., electromyographic) signals sensed from the user. In general, prosthetic devices that support multiple degree-of-freedom movements for any limb require sequential control, implementing locking mechanisms or special switch signals to change from one degree-of-freedom to another. There is a large, unmet need for control algorithms that allow simultaneous control of multiple degrees-of-freedom and are not difficult for the user to learn. In this study, we will implement a biomechanical modeling approach to develop a control algorithm that predicts the hand and wrist motions that would occur in an intact hand given the electromyographic (EMG) signals measured from the residual muscles of an amputee's forearm. The objectives for this proposal are to first characterize the function of the hand muscles in creating complex hand motions in the intact hand and to then develop the controller. To accomplish these objectives, extrinsic muscle activity and joint kinematics will be quantified as individuals produce a subset of postures from the manual alphabet of American Sign Language (ASL), and perform two prehensile tasks. Recorded muscle activity will define the control signals available from the extrinsic muscles during complex motions, and will become input for biomechanical simulations, which will be used to identify how effectively postures can be achieved without the contributions from the intrinsic muscles of the hand (the subset of muscles lost to amputation). Results will direct the mechanical design of prosthetic hands to effectively compensate for the mechanical actions of the missing intrinsic muscles. Ultimately, a prosthetic hand is intended to be used to manipulate objects. Thus, we will implement recent developments in variational integration theory to develop real-time simulations that incorporate endpoint forces, such as those found when the fingertips are in contact with an object, and other constraints required to simulate the hand interacting with external objects. Upon completion of the simulation work, a controller that drives the artificial hand based on user-generated muscle signals will be developed and implemented. Accomplishing the goals of this project will address a critical barrier to clinical implementation and user acceptance of multi-function prosthetic hands.

描述（由申请人提供）：最近手部截肢的人希望现代手部假肢能像完整的手一样工作。目前最先进的电动假肢手通常是单自由度（打开和关闭）装置，仅使用两个肌肉信号来控制。结果，大多数最先进的设备不能满足用户的期望，得不到充分利用或被拒绝。正因为如此，机械硬件的进步是为了提供与完整的人手相当的功能。尽管取得了这样的进步，但复杂的手假体的性能仍然受到通过用户感知的生理（例如肌电图）信号来控制它们的能力的限制。一般来说，支持任何肢体多自由度运动的假肢装置需要顺序控制，实现锁定机制或特殊开关信号从一个自由度转换到另一个自由度。对于允许同时控制多个自由度并且对用户来说不难学习的控制算法，存在大量未满足的需求。在这项研究中，我们将实施一种生物力学建模方法来开发一种控制算法，该算法可以根据从截肢者前臂残余肌肉中测量到的肌电图（EMG）信号，预测手部和手腕的运动，这些运动将发生在一个完整的手部。本提案的目标是首先描述手部肌肉在完整手部创造复杂手部运动中的功能，然后开发控制器。为了实现这些目标，外在的肌肉活动和关节运动学将被量化，因为个体从美国手语（ASL）的手势字母表中产生一个子集的姿势，并执行两个握住的任务。记录的肌肉活动将定义在复杂运动中外部肌肉可用的控制信号，并将成为生物力学模拟的输入，这将用于确定在没有手部内在肌肉（截肢肌肉的子集）的贡献的情况下如何有效地实现姿势。结果将指导假肢手的机械设计，以有效地补偿缺失的内在肌肉的机械动作。最终，假手是用来操纵物体的。因此，我们将实现变分积分理论的最新发展，以开发包含端点力的实时仿真，例如当指尖与物体接触时发现的力，以及模拟手与外部物体相互作用所需的其他约束。仿真工作完成后，将开发并实现基于用户生成的肌肉信号驱动假手的控制器。完成该项目的目标将解决临床实施和用户接受多功能假手的关键障碍。