4D dynamic system for visual-motor integration analysis

Abstract

It is very important to evaluate visual-motor integration (VMI), as it is used as an index to evaluate cognitive abilities. However, it is difficult to use the existing paper-based tests to evaluate the dynamic process, including spatial and depth perception abilities. Therefore, this study aims to extract kinematic and dynamic features for dynamic assessment for VMI. We propose a 4D dynamic analysis system that implements a VMI test in a virtual space using Leap motion controller and Unity3D and acquires the time-series data of hand joints and traces. We selected three categories of features: postural control ability, spatial and depth perception ability, and 4D analysis. The degree and patterns of postural maintenance differed between subjects in the VMI and MC tests. In addition, the personal patterns were identified with dynamic features, including their fluency and hesitation in relation to the task figures of the VMI test tool. As such, this system enables dynamic feature extraction and analysis which were previously impossible and presents performance results for healthy adults.