Assessing kinematic variability during performance of Jebsen-Taylor Hand Function Test

Kimberly L Kontson; Sophie Wang; Sydney Barovsky; Conor Bloomer; Laura Wozniczka; Eugene F Civillico

doi:10.1016/j.jht.2018.10.002

Assessing kinematic variability during performance of Jebsen-Taylor Hand Function Test

J Hand Ther. 2020 Jan-Mar;33(1):34-44. doi: 10.1016/j.jht.2018.10.002. Epub 2019 Mar 8.

Authors

Kimberly L Kontson¹, Sophie Wang², Sydney Barovsky³, Conor Bloomer⁴, Laura Wozniczka⁵, Eugene F Civillico⁶

Affiliations

¹ Division of Biomedical Physics, U.S. Food and Drug Administration, Center for Devices and Radiological Health, Office of Science and Engineering Labs, Silver Spring, MD, USA. Electronic address: Kimberly.Kontson@fda.hhs.gov.
² Division of Biomedical Physics, U.S. Food and Drug Administration, Center for Devices and Radiological Health, Office of Science and Engineering Labs, Silver Spring, MD, USA; Department of Biomedical Engineering, University of Maryland, College Park, MD, USA.
³ Department of Biomedical Engineering, Marquette University, Milwaukee, WI, USA.
⁴ Division of Biomedical Physics, U.S. Food and Drug Administration, Center for Devices and Radiological Health, Office of Science and Engineering Labs, Silver Spring, MD, USA.
⁵ Department of Biological Sciences, Marquette University, Milwaukee, WI, USA.
⁶ Department of Health and Human Services, National Institutes of Health, Bethesda, MD, USA.

PMID: 30857890
DOI: 10.1016/j.jht.2018.10.002

Abstract

Study design: Clinical measurement; 22 subjects with no upper limb disability completed the Jebsen-Taylor Hand Function Test (JHFT).

Introduction: To realize the potential of 3D motion capture to augment evaluation of individuals with upper limb disability/impairment, it is important to understand the expected kinematic motion that characterizes performance during functional evaluation.

Purpose of the study: To assess kinematic variability and establish kinematic patterns for the JHFT.

Methods: Upper body joint kinematics were collected using a Vicon motion capture system. Average range of motion and maximum angle were calculated for all tasks. Intrasubject and intersubject variability were assessed by calculating Pearson's correlation coefficient, adjusted coefficient of multiple correlation (CMC_adj), and standard deviation for 10 joint angles at the wrist, elbow, shoulder, and torso.

Results: The writing and picking up small objects tasks generally had high intrasubject variability, with most joint angles having median Pearson's correlation coefficients lower than 0.7. The CMC_adj values were generally greater than 0.5 for elbow, shoulder, and torso joints during can-lifting tasks, indicating high consistency in those kinematic trajectories across subjects. Low consistency across subjects in all joint angles was observed for writing (CMC_adj < 0.07; SD_max > 10°).

Discussion: Kinematic patterns for the JHFT tasks were analyzed.

Conclusions: With kinematic patterns for the JHFT tasks analyzed, optimal patterns of activity performance can be defined, allowing for easier identification and adjustment of atypical motion. Results can be used to inform selection of tasks for kinematic evaluation and provide expected variability for comparison to patient populations, which is useful for regulatory review and clinical assessment.

Keywords: JHFT; Motion capture; Outcome measures; Upper limb; Variability.

Published by Elsevier Inc.

MeSH terms

Activities of Daily Living
Adult
Female
Humans
Joints / physiology*
Male
Motor Activity / physiology*
Motor Skills / physiology*
Range of Motion, Articular / physiology*
Reproducibility of Results
Task Performance and Analysis
Torso / physiology
Upper Extremity / physiology*
Young Adult