Liu Yuan, Zeng Bo, Jiang Li, Liu Hong, Ming Dong
Tianjin University, Academy of Medical Engineering and Translational Medicine (AMT), Tianjin, China.
Beijing Institute of Precision Mechatronics and Controls, Laboratory of Aerospace Servo Actuation and Transmission, Beijing, China.
Appl Bionics Biomech. 2021 Nov 15;2021:2640422. doi: 10.1155/2021/2640422. eCollection 2021.
This paper is the first in the two-part series quantitatively modelling human grasp functionality and understanding the way human grasp objects. The aim is to investigate the thumb movement behavior influenced by object shapes, sizes, and relative positions. Ten subjects were requested to grasp six objects (3 shapes × 2 sizes) in 27 different relative positions (3 deviation × 3 deviation × 3 deviation). Thumb postures were investigated to each specific joint. The relative position (, , and deviation) significantly affects thumb opposition rotation (Rot) and flexion (interphalangeal (IP) and metacarpo-phalangeal (MCP)), while the object property (object shape and size) significantly affects thumb abduction/adduction (ABD) motion. Based on the value, the deviation has the primary effects on thumb motion. When the deviation changing from proximal to distal, thumb opposition rotation (Rot) and flexion (IP and MCP joint) angles were increased and decreased, respectively. For principal component analysis (PCA) results, thumb grasp behavior can be accurately reconstructed by first two principal components (PCs) which variance explanation ratio reached 93.8% and described by the inverse and homodromous coordination movement between thumb opposition and IP flexion. This paper provides a more comprehensive understanding of thumb grasp behavior. The postural synergies can reproduce the anthropomorphic motion, reduce the robot hardware, and control dimensionality. All of these provide a more accurate and general basis for the design and control of the bionic thumb and novel wearable assistant robot, thumb function assessment, and rehabilitation.
本文是一个两部分系列论文中的第一篇,对人类抓握功能进行定量建模,并理解人类抓握物体的方式。目的是研究受物体形状、大小和相对位置影响的拇指运动行为。要求10名受试者在27种不同的相对位置(3种偏差×3种偏差×三种偏差)下抓握6个物体(3种形状×2种大小)。对每个特定关节的拇指姿势进行了研究。相对位置(x、y和z偏差)显著影响拇指对掌旋转(Rot)和屈曲(指间关节(IP)和掌指关节(MCP)),而物体属性(物体形状和大小)显著影响拇指外展/内收(ABD)运动。基于p值,z偏差对拇指运动起主要作用。当z偏差从近端向远端变化时,拇指对掌旋转(Rot)角度增加,而拇指屈曲(IP和MCP关节)角度分别减小。对于主成分分析(PCA)结果,拇指抓握行为可以通过前两个主成分(PCs)准确重建,其方差解释率达到93.8%,并通过拇指对掌和IP屈曲之间的反向和同向协调运动来描述。本文对拇指抓握行为提供了更全面的理解。姿势协同作用可以再现拟人运动,减少机器人硬件并控制维度。所有这些为仿生拇指和新型可穿戴辅助机器人的设计与控制、拇指功能评估及康复提供了更准确和通用的基础。