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首页> 外文期刊>Journal of NeuroEngineering Rehabilitation >Analysis of hand synergies in healthy subjects during bimanual manipulation of various objects
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Analysis of hand synergies in healthy subjects during bimanual manipulation of various objects

机译：在健康人的双手协同操作各种对象过程中的手协同作用分析

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Background Hand synergies have been extensively studied over the last few decades. Objectives of such research are numerous. In neuroscience, the aim is to improve the understanding of motor control and its ability to reduce the control dimensionality. In applied research fields like robotics the aim is to build biomimetic hand structures, or in prosthetics to design more performant underactuated replacement hands. Nevertheless, most of the synergy schemes identified to this day have been obtained from grasping experiments performed with one single (generally dominant) hand to objects placed in a given position and orientation in space. Aiming at identifying more generic synergies, we conducted similar experiments on postural synergy identification during bimanual manipulation of various objects in order to avoid the factors due to the extrinsic spatial position of the objects. Methods Ten healthy naive subjects were asked to perform a selected “grasp-give-receive” task with both hands using 9 objects. Subjects were wearing Cyberglove ? on both hands, allowing a measurement of the joint posture (15 degrees of freedom) of each hand. Postural synergies were then evaluated through Principal Component Analysis (PCA). Matches between the identified Principal Components and the human hand joints were analyzed thanks to the correlation matrix. Finally, statistical analysis was performed on the data in order to evaluate the effect of some specific variables on the hand synergies: object shape, hand side (i.e., laterality) and role (giving or receiving hand). Results Results on PCs are consistent with previous literature showing that a few principal components might be sufficient to describe a large variety of different grasps. Nevertheless some simple and strong correlations between PCs and clearly identified sets of hand joints were obtained in this study. In addition, these groupings of DoF corresponds to well-defined anatomo-functional finger joints according to muscle groups. Moreover, despite our protocol encouraging symmetric grasping, some right-left side differences were observed. Conclusion The set of identified synergies presented here should be more representative of hand synergies in general since they are based on both hands motion. Preliminary results, that should be deepened, also highlight the influence of hand dominance and side. Thanks to their strong correlation with anatomo-functional joints, these synergies could therefore be used to design underactuated robotics hands.
机译：背景技术在过去的几十年中，对手的协同作用进行了广泛的研究。这类研究的目的很多。在神经科学中，目的是增进对运动控制及其对降低控制维度的理解。在诸如机器人技术的应用研究领域，目标是建立仿生手结构，或在假肢中设计性能更高的欠驱动替换手。然而，迄今为止，大多数迄今为止确定的协同计划都是通过用一只（通常是占优势的）一只手对放置在空间中给定位置和方向的物体进行的抓握实验获得的。为了识别更多的通用协同作用，我们在双手操纵各种物体的过程中对姿势协同识别进行了类似的实验，以避免物体外在空间位置的影响。方法要求10名健康的初学者受试者用两只手用9个对象执行选定的“抓握-接受-接受”任务。受试者都穿着电子手套？可以测量两只手的关节姿势（15个自由度）。然后通过主成分分析（PCA）评估姿势协同作用。借助相关矩阵，可以分析识别出的主要成分与人手关节之间的匹配情况。最后，对数据进行统计分析，以评估某些特定变量对手部协同作用的影响：对象形状，手部侧面（即侧边）和角色（给予或接受手部）。结果PC机上的结果与以前的文献一致，后者表明一些主要成分可能足以描述各种不同的理解。尽管如此，在这项研究中仍获得了PC与明确识别的手关节之间的一些简单而强大的相关性。此外，DoF的这些分组对应于根据肌肉组明确定义的解剖功能手指关节。此外，尽管我们的协议鼓励对称抓握，但仍观察到一些左右差异。结论此处提出的已确定的协同作用集应总体上代表手协同作用，因为它们是基于双手运动的。应当深化的初步结果也突出了手的优势和侧边的影响。由于它们与解剖功能关节之间的紧密联系，因此这些协同作用可用于设计动作不足的机器人手。

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