Quantitative Investigation of Hand Grasp Functionality: Thumb Grasping Behavior Adapting to Different Object Shapes, Sizes, and Relative Positions

Abstract

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 ( <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" id="M1"> <a:mn>3</a:mn> <a:mtext> </a:mtext> <a:mtext>shapes</a:mtext> <a:mo>×</a:mo> <a:mn>2</a:mn> <a:mtext> </a:mtext> <a:mtext>sizes</a:mtext> </a:math> ) in 27 different relative positions ( <c:math xmlns:c="http://www.w3.org/1998/Math/MathML" id="M2"> <c:mn>3</c:mn> <c:mtext> </c:mtext> <c:mi>X</c:mi> <c:mtext> </c:mtext> <c:mtext>deviation</c:mtext> <c:mo>×</c:mo> <c:mn>3</c:mn> <c:mtext> </c:mtext> <c:mi>Y</c:mi> <c:mtext> </c:mtext> <c:mtext>deviation</c:mtext> <c:mo>×</c:mo> <c:mn>3</c:mn> <c:mtext> </c:mtext> <c:mi>Z</c:mi> <c:mtext> </c:mtext> <c:mtext>deviation</c:mtext> </c:math> ). Thumb postures were investigated to each specific joint. The relative position ( <e:math xmlns:e="http://www.w3.org/1998/Math/MathML" id="M3"> <e:mi>X</e:mi> </e:math> , <g:math xmlns:g="http://www.w3.org/1998/Math/MathML" id="M4"> <g:mi>Y</g:mi> </g:math> , and <i:math xmlns:i="http://www.w3.org/1998/Math/MathML" id="M5"> <i:mi>Z</i:mi> </i:math> 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 <k:math xmlns:k="http://www.w3.org/1998/Math/MathML" id="M6"> <k:mi>F</k:mi> </k:math> value, the <m:math xmlns:m="http://www.w3.org/1998/Math/MathML" id="M7"> <m:mi>Y</m:mi> </m:math> deviation has the primary effects on thumb motion. When the <o:math xmlns:o="http://www.w3.org/1998/Math/MathML" id="M8"> <o:mi>Y</o:mi> </o:math> 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.