Journal
FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY
Volume 9, Issue -, Pages -Publisher
FRONTIERS MEDIA SA
DOI: 10.3389/fbioe.2021.660015
Keywords
stroke; upper extremity; kinematics; motor function; principal component analysis
Funding
- National Natural Science Foundation of China [U 1913601, 91648203]
Ask authors/readers for more resources
The study revealed that kinematic components during the finger-to-nose test are associated with upper extremity motor function in subacute stroke survivors. Three principal components, accounting for 91.3% variance, include metrics such as mean velocity, peak velocity, number of movement units, and normalized integrated jerk.
Background: Kinematic analysis facilitates interpreting the extent and mechanisms of motor restoration after stroke. This study was aimed to explore the kinematic components of finger-to-nose test obtained from principal component analysis (PCA) and the associations with upper extremity (UE) motor function in subacute stroke survivors. Methods: Thirty-seven individuals with subacute stroke and twenty healthy adults participated in the study. Six kinematic metrics during finger-to-nose task (FNT) were utilized to perform PCA. Clinical assessments for stroke participants included the Fugl-Meyer Assessment for Upper Extremity (FMA-UE), Action Research Arm Test (ARAT), and Modified Barthel Index (MBI). Results: Three principal components (PC) accounting for 91.3% variance were included in multivariable regression models. PC1 (48.8%) was dominated by mean velocity, peak velocity, number of movement units (NMU) and normalized integrated jerk (NIJ). PC2 (31.1%) described percentage of time to peak velocity and movement time. PC3 (11.4%) profiled percentage of time to peak velocity. The variance explained by principal component regression in FMA-UE (R-2 = 0.71) were higher than ARAT (R-2 = 0.59) and MBI (R-2 = 0.29) for stroke individuals. Conclusion: Kinematic components during finger-to-nose test identified by PCA are associated with UE motor function in subacute stroke. PCA reveals the intrinsic association among kinematic metrics, which may add value to UE assessment and future intervention targeted for kinematic components for stroke individuals.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available