AI RESEARCH
Enhancing Box and Block Test with Computer Vision for Post-Stroke Upper Extremity Motor Evaluation
arXiv CS.CV
•
ArXi:2603.29101v1 Announce Type: new Standard clinical assessments of upper-extremity motor function after stroke either rely on ordinal scoring, which lacks sensitivity, or time-based task metrics, which do not capture movement quality. In this work, we present a computer vision-based framework for analysis of upper-extremity movement during the Box and Block Test (BBT) through world-aligned joint angles of fingers, arm, and trunk without depth sensors or calibration objects.