Evaluating Marker-Based and Markerless Motion Capture Systems in Reach-to-Grasp Task

This study evaluated the accuracy of marker-based versus markerless motion capture systems in tracking reach-to-grasp movements, using an electromagnetic tracking system as the gold standard. Reach-to-grasp tasks are fundamental activity in daily activities and often affected by neurological conditions like stroke, highlighting the importance of accurate measurement in rehabilitation research. The findings show that the marker-based system consistently outperformed the markerless system, with significantly lower root mean square errors (RMSE) across all axes. The marker-based system achieved an average RMSE of 4.55 millimeters (mm), demonstrating clinical-level accuracy, while the markerless system averaged 23.64 mm, indicating limitations in its ability to track movements with high accuracy.

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Publication Details

Published
2024-11-21
DOI
https://doi.org/10.1109/bmeicon64021.2024.10896308
Citations
1
Primary Topic
Robot Manipulation and Learning
Type
article
Field-Weighted Citation Impact
0.33
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article

Evaluating Marker-Based and Markerless Motion Capture Systems in Reach-to-Grasp Task

Natsakorn Liangsorn, Suradej Tretriluxana
1 citations
Robot Manipulation and Learning
0.33
article

Evaluating Marker-Based and Markerless Motion Capture Systems in Reach-to-Grasp Task

Natsakorn Liangsorn, Suradej Tretriluxana
article en
1 citations

Abstract

This study evaluated the accuracy of marker-based versus markerless motion capture systems in tracking reach-to-grasp movements, using an electromagnetic tracking system as the gold standard. Reach-to-grasp tasks are fundamental activity in daily activities and often affected by neurological conditions like stroke, highlighting the importance of accurate measurement in rehabilitation research. The findings show that the marker-based system consistently outperformed the markerless system, with significantly lower root mean square errors (RMSE) across all axes. The marker-based system achieved an average RMSE of 4.55 millimeters (mm), demonstrating clinical-level accuracy, while the markerless system averaged 23.64 mm, indicating limitations in its ability to track movements with high accuracy.

King Mongkut's Institute of Technology Ladkrabang (TH)
Openalex Percentile: Top 36%
Robot Manipulation and Learning
0.33
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