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Updated: Oct 19, 2025

Kinematic Analysis Using 3D Motion Capture of Drinking Task in People With and Without Upper-extremity Impairments
Published on: March 28, 2018
Associations between upper extremity functioning and kinematics in people with spinal cord injury
Lamprini Lili1,2, Katharina S Sunnerhagen3,4, Tiina Rekand3,5
1Institute of Neuroscience and Physiology, Clinical Neuroscience, Rehabilitation Medicine, Sahlgrenska Academy, University of Gothenburg, Per Dubbsgatan 14, 3rd Floor, 41345, Göteborg, Sweden. lamprini.lili@gu.se.
Introduction:
More knowledge of the relationships between kinematic measures and clinical assessments is required to guide clinical decision making and future research.
Objectives:
To determine which kinematic variables obtained during a drinking task were associated with clinical assessments of upper extremity functioning in people with spinal cord injury (SCI).
Methods:
In total, 25 individuals with chronic cervical (n = 17) or thoracic (n = 8) complete (n = 14) or motor incomplete (n = 11) SCI (mean age 58.4, SD 13.8) were included. Kinematic data, including movement time, smoothness and joint angles was captured with a 5-camera optoelectronic system during a unimanual drinking task. Action Research Arm Test (ARAT), Sollerman Hand Function Test (SHFT) and basic hand classification of the Upper Extremity Data Set (ISCI-Hand) were used as clinical assessments. Multiple regression analysis was used to identify kinematic variables associated with clinical assessments after controlling for potential confounding factors, such as, age, severity of SCI, sensory function, and hand surgery.
Results:
Movement time, smoothness and movement pattern kinematics including trunk displacement, elbow and wrist joint angles were correlated (p < 0.05) with all three clinical scales while the velocity-related kinematics and inter-joint coordination showed low correlations. Multiple regression analysis revealed that wrist angle combined with movement time or smoothness explained 82% and 77% of the total variance in ARAT and SHFT, respectively. Wrist angle alone explained 59% of the variance in ISCI-Hand. The proprioception of the hand increased the explanatory power in the models of ARAT and SHFT. Associations between kinematics and clinical assessments in the subgroup with cervical SCI were equivalent to the whole group analyses. The number of participants in the subgroup with thoracic SCI was small and only allowed limited analysis.
Conclusions:
Wrist angle, movement time, movement smoothness are the most important kinematic variables associated with upper extremity clinical assessments in people with SCI. The results are most valid for individuals with cervical SCI. All three assessments are appropriate for SCI. Further research with larger representative sample of thoracic SCI needed.
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