Development and Evaluation of a 3D Motion Capture Model for Upper Extremity Kinematics During Wheelchair Maneuvering in Individuals with Spinal Cord Injuries: A Pilot Study

Spinal cord injury (SCI) often necessitates the use of a manual wheelchair, which can overload the shoulders and contribute to upper extremity (UE) pain. Currently, no standardized methods exist to assess UE kinematics during wheelchair propulsion. This study aimed to develop and evaluate a marker-b...

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Main Authors: Lina Bunketorp Käll, Gudni Rafn Harðarson, Erik Tullin, Ann-Sofi Lamberg, Roy Tranberg, Johanna Wangdell
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Bioengineering
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Online Access:https://www.mdpi.com/2306-5354/12/6/648
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Summary:Spinal cord injury (SCI) often necessitates the use of a manual wheelchair, which can overload the shoulders and contribute to upper extremity (UE) pain. Currently, no standardized methods exist to assess UE kinematics during wheelchair propulsion. This study aimed to develop and evaluate a marker-based motion capture model for analyzing UE movement during wheelchair use, with a secondary goal of assessing test–retest reliability. The study was conducted in two phases: (1) development of the motion analysis model and (2) reliability testing. Eleven participants with SCI were included. Reliability was assessed using intraclass correlation coefficients (ICCs) across 15 movement parameters, including total range of motion and minimum and maximum movement values. The model demonstrated good test–retest reliability. For minimum movement, 12 of 15 parameters were significant (ICC = 0.681–0.965). For maximum movement, 13 of 15 were significant (ICC = 0.726–0.981). For total range of motion, 12 of 15 showed significant reliability (ICC = 0.596–0.952). In conclusion, the motion capture model showed promising reliability for assessing UE kinematics during wheelchair maneuvering in individuals with SCI. However, due to the small sample size, further research is needed to validate and refine the model.
ISSN:2306-5354