Data Acquisition Through Participatory Design for Automated Rehabilitation Assessment
Journal:
arXiv
Published Date:
Jan 2, 2025
Abstract
Through participatory design, we are developing a computational system for
the semi-automated assessment of the Action Research Arm Test (ARAT) for stroke
rehabilitation. During rehabilitation assessment, clinicians rate movement
segments and components in the context of overall task performance. Clinicians
change viewing angles to assess particular components. Through studies with
clinicians, we develop a system that includes: a) unobtrusive multi-camera
capture, b) a segmentation interface for non-expert segmentors, and c) a rating
interface for expert clinicians. Five clinicians independently captured 1800
stroke survivor videos with <5$\%$ errors. Three segmentors have segmented 760
of these videos, averaging 20 seconds per segment. They favor the recommended
camera view $>$ 90\%. Multiple clinicians have rated the segmented videos while
reporting minimal problems. The complete data will be used for training an
automated segmentation and rating system that empowers the clinicians as the
ratings will be compatible with clinical practice and intuition.
