Accuracy and feasibility of a novel fine hand motor skill assessment using computer vision object tracking

Abstract Computer vision-based 3D motion capture systems are useful for human movement kinematic evaluation. We developed a computer vision-based 3D motion capture system by tracking an object manipulated by a hand to assess fine hand motor function. This study aimed to determine the accuracy and feasibility of this system to assess fine hand motor skill learning. We conducted four different experiments to test the accuracy and feasibility of this system. We used two action cameras with high resolution and high frame rate. We tested our system's accuracy in estimating the 3D positions of a static object and a moving object in different directions. We tested the feasibility of this system to assess fine hand motor skill learning in four non-disabled young adults. This clinical feasibility experiment used a standard motor skill learning experimental design. We utilized color-based object detection and tracking. Our results support that this computer vision-based motion capture system is accurate in reconstructing the 3D positions of a moving object. Also, we demonstrated that the system can be used to quantify the kinematics of the target object movements to evaluate fine hand motor skill learning. Future studies are needed to establish the reliability and validity of this system to assess fine hand motor skills in patient populations.