Prosthesis Control by Forward Dynamic Simulation of the Intact Biomedical system

描述（由申请人提供）：近期手部截肢的人希望现代手部假体能够像完整的手一样发挥功能。目前最先进的电动假手通常是单自由度（打开和闭合）的装置，其仅使用两个肌肉信号来控制。因此，大多数最先进的设备无法满足用户的期望，并且未得到充分利用或被拒绝。正因为如此，机械硬件的发展方向是提供与完好的人手相当的功能。尽管有这样的进步，复杂的手假体的性能仍然受到通过生理（例如，肌电图）信号。通常，支持任何肢体的多个自由度运动的假肢装置需要顺序控制，实现锁定机构或特殊开关信号以从一个自由度改变到另一个自由度。对于允许同时控制多个自由度并且用户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，我们将实现一个生物力学建模方法来开发一个控制算法，预测的手和手腕的动作，将发生在一个完整的手，给定的肌电图（EMG）信号测量从截肢者的前臂的残余肌肉。该建议的目标是首先描述手部肌肉在完整手部中创建复杂手部运动的功能，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为个人产生的姿势从美国手语（ASL）的手动字母表的子集，并执行两个模拟任务。记录的肌肉活动将定义在复杂运动期间可从外在肌肉获得的控制信号，并将成为生物力学模拟的输入，这将用于确定在没有手的内在肌肉（截肢失去的肌肉子集）的贡献的情况下如何有效地实现姿势。结果将指导假手的机械设计，以有效地补偿缺失的内在肌肉的机械动作。最终，假肢手旨在用于操纵物体。因此，我们将实施变分积分理论的最新发展，以开发实时模拟，将端点的力量，如那些发现时，指尖与物体接触，以及其他约束条件所需的模拟手与外部物体的相互作用。在完成模拟工作后，将开发和实现一个控制器，该控制器根据用户生成的肌肉信号驱动假手。完成本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。

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.