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

Author:

Kim Bokkyu,Neville Christopher

Abstract

AbstractWe developed a computer vision-based three-dimension (3D) motion capture system employing two action cameras to examine fine hand motor skill by tracking an object manipulated by a hand. This study aimed to examine the accuracy and feasibility of this approach for detecting changes in a fine hand motor skill. We conducted three distinct experiments to assess the system's accuracy and feasibility. We employed two high-resolution, high-frame-rate action cameras. We evaluated the accuracy of our system in calculating the 3D locations of moving object in various directions. We also examined the system's feasibility in identifying improvement in fine hand motor skill after practice in eleven non-disabled young adults. We utilized color-based object detection and tracking to estimate the object's 3D location, and then we computed the object's kinematics, representing the endpoint goal-directed arm reaching movement. Compared to ground truth measurements, the findings demonstrated that our system can adequately estimate the 3D locations of a moving object. We also showed that the system can be used to measure the endpoint kinematics of goal-directed arm reaching movements to detect changes in fine hand motor skill after practice. Future research is needed to confirm the system's reliability and validity in assessing fine hand motor skills in patient populations.

Funder

APTA New York

State University of New York Upstate Medical University,United States

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Early Childhood Action Monitoring and Analytics System (ECAMS);2023 IEEE 28th Pacific Rim International Symposium on Dependable Computing (PRDC);2023-10-24

2. A Dual-Input Moving Object Detection Method in Remote Sensing Image Sequences via Temporal Semantics;Remote Sensing;2023-04-23

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