Prosthesis Control by Forward Dynamic Simulation of the Intact Biomedical system

描述(由申请人提供)：最近手部截肢的人希望现代手部假体能像完整的手一样发挥作用。目前最先进的电动假手通常是单自由度(打开和关闭)设备，仅使用两个肌肉信号进行控制。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，机械硬件的进步是为了提供可与完整的人类手相媲美的功能。尽管有这样的进步，复杂的假手的性能仍然受到通过从用户感测到的生理(例如，肌电)信号来控制它们的能力的限制。一般来说，支持任何肢体的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的开关信号来从一个自由度切换到另一个自由度。对于允许同时控制多个自由度并且对用户来说并不难学习的控制算法，存在大量未得到满足的需求。在这项研究中，我们将实施生物力学建模方法来开发一种控制算法，该算法可以根据截肢者前臂残馀肌肉测量的肌电(EMG)信号来预测完好手的手部和手腕运动。这项建议的目标是首先描述手部肌肉在完整的手中创造复杂手部运动的功能，然后开发控制器。为了实现这些目标，外部肌肉活动和关节运动学将被量化，因为个体根据美国手语(ASL)的手动字母表产生一组姿势，并执行两项抓取任务。记录的肌肉活动将定义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，用于确定在没有手的内部肌肉(因截肢而失去的肌肉子集)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。归根结底，假手是用来操纵物体的。因此，我们将实施变分积分理论的最新发展，以开发包含端点力的实时模拟，例如当指尖与对象接触时发现的端点力，以及模拟手与外部对象交互所需的其他约束。在模拟工作完成后，将开发和实现基于用户产生的肌肉信号来驱动假手的控制器。实现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。

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.