Skeleton tracking solutions for a low-cost stroke rehabilitation support system

Publication Type

Conference Proceeding Article

Publication Date

9-2023

Abstract

Computer systems based on motion assessment are promising solutions to support stroke survivors' autonomous rehabilitation exercises. In this regard, researchers keep trying to achieve engaging and low-cost solutions suitable mainly for home use. Aiming to achieve a system with a minimal technical setup, we compare Microsoft Kinect, OpenPose, and MediaPipe skeleton tracking approaches for upper extremity quality of movement assessment after stroke. We determine if classification models assess accurately exercise performance with OpenPose and MediaPipe data against Kinect, using a dataset of 15 stroke survivors. We compute Root Mean Squared Error to determine the alignment of trajectories and kinematic variables. MediaPipe World Landmarks revealed high alignment with Kinect, revealing to be a potential alternative method.

Keywords

tracking, computational modeling, stroke (medical condition), assistive robots, skeleton, motion capture, libraries

Discipline

Artificial Intelligence and Robotics

Research Areas

Intelligent Systems and Optimization

Publication

2023 International Conference on Rehabilitation Robotics (ICORR): Singapore, September 24-28: Proceedings

ISBN

9798350342765

Identifier

10.1109/ICORR58425.2023.10304749

Publisher

IEEE

City or Country

Piscataway, NJ

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.1109/ICORR58425.2023.10304749

This document is currently not available here.

Share

COinS