A Postural Control Paradigm for EMG Control of Advanced Prosthetic Hands

描述(由申请人提供)： 在这个项目中，我们将探索使用一种基于主成分分析原理的新型假肢控制器来实现高自由度假手的无缝姿势选择。本项目的目标是开发一种使用肌电信号(EMG)作为控制输入的多自由度(DOF)假手姿态控制器，并利用主成分分析(PCA)对其进行维度优化。目前可用的多自由度假手不能被充分利用，因为控制输入少于要控制的自由度的数量(即欠驱动系统)。根据神经科学文献1的研究表明，掌握是一项“低维度”的任务。这项工作使用主成分分析来量化掌握过程中涉及的主成分(维度数量)。研究发现，前两个主成分可以很好地描述抓握任务。两个主成分意味着，一只多自由度的手在抓取时，只需2个控制自由度就可以控制其姿势。这是一个令人鼓舞的发现，因为目前的临床上肢假体实践表明只有3到4个独立的肌电部位。 可以位于典型的经桡动脉截肢患者的残肢上。我们建议探索基于Santello等人描述的前两个主成分的手势控制器的优点，并使用2、3或4个肌电部位来驱动。Santello等人。测量受试者手中的15个关节角度，同时“抓住”57件家居物品。结果分析表明，当抓取不同的物体时，关节之间的协方差很高。主成分分析表明，前两个主成分可以解释84%的方差。这一结果表明，对于抓取任务，我们的22自由度自然手的控制在很大程度上归结为一个2维控制问题。将这一发现应用于多关节假手的控制，意味着我们可以使用2-4个肌电极，但仍然能够在多自由度手的不同姿势之间无缝移动。我们将开发一种控制算法，将肌电信号映射到Santello等人的前两个主成分的加权组合，以产生所需的姿势。Keller等人(1947)定义的所有功能把握都可以通过改变任一主成分的加权程度来实现。这种控制器只需3到4个肌电部位就可以控制高维抓握，从而利用目前可用的临床实践来控制多自由度假手。这一点很有意义，因为市场上有许多新的商业可用手，它们具有关节手指和多位置拇指--但无法轻松地在抓手之间进行选择。我们将演示肌电驱动的基于PCA的控制器，使其驱动Bebionic Hand2，该Bebionic Hand2已被修改为具有两个自由度的拇指-将其转换为6自由度的手。1 Santello，M.，Flanders，M.和Soechting J.F.，(1998)：工具使用的手势协同效应。神经科学，18(23)10105-10115。2 RSL Steeper，英国罗切斯特。

DESCRIPTION (provided by applicant): In this project we will explore the use of a novel prosthesis controller based on the principle of Principal Component Analysis to enable seamless posture selection in high degree-of-freedom (DOF) prosthetic hands. The goal of this project is to develop a multi-degree of freedom (DOF) hand prosthesis posture controller that uses myoelectric signals (EMG) as control inputs and which has been dimensionally optimized using principal component analysis (PCA). Currently available multi-DOF hand prostheses cannot be fully utilized because there are fewer control inputs than the number of DOFs to be controlled (i.e. an underactuated system). Based on work from the neuroscience literature1 it has been shown that grasping is a 'low dimensional' task. This work used PCA to quantify the principal components (number of dimensions) involved in grasping. It was found that grasping tasks could be well described by the first two principal components. Two principal components implies that the posture of a multi-DOF hand, while grasping, can be controlled using only 2 degrees-of-control. This is an encouraging finding since current clinical upper limb prosthetic practice indicates only 3 or 4 independent myoelectric sites can be located on the residual limb of a typical person with a transradial amputation. We propose to explore the merits of a hand posture controller based on the first two principal components described by Santello et al.1 and driven using 2, 3 or 4 myoelectric sites. Santello et al. measured 15 joint angles in the hand of the subjects while 'grasping' 57 household objects. The resulting analysis showed a high amount of covariance between the joints while grasping different objects. A principal component analysis showed that the first two principal components accounted for 84% of the variance. This result suggests that, for grasping tasks, control of our 22 DOF natural hand reduces to a largely 2 dimensional control problem. Applying this finding to the control of multi-articulated prosthetic hands means we can use 2-4 myoelectrodes yet still be able to seamlessly move between postures in a multi-DOF hand. We will develop a control algorithm that will map the myoelectric signals to weighted combinations of Santello et al.s first two principal components to yield a desired posture. All functional grasp as defined by Keller et al., (1947) are achievable by varying the degree to which either principal component is weighted. This controller will direct high-dimension grasps with only 3 or 4 myoelectric sites and therefore control a multi-degree of freedom prosthetic hand using currently available clinical practices. This is of relevance because there are a number of new commercially available hands coming onto the market with articulated fingers and multi- positional thumbs - but with no way to select between grasps in a easy manner. We will demonstrate an EMG- driven PCA-based controller by having it drive a Bebionic Hand2 which has been modified to have a two degree-of-freedom thumb - converting it into a 6 DOF hand. 1 Santello, M., Flanders, M., and Soechting J.F., (1998): Postural hand synergies for tool use. J. Neuroscience, 18(23)10105-10115. 2 RSLSteeper, Rochester, United Kingdom.