Literature DB >> 28422686

An Integrated Movement Analysis Framework to Study Upper Limb Function: A Pilot Study.

Kimberly L Kontson, Ian P Marcus, Barbara M Myklebust, Eugene F Civillico.   

Abstract

The functional capabilities of individuals with upper limb disabilities are assessed throughout rehabilitation and treatment regimens using functional outcome measures. For the upper limb amputee population, there are none which quantitatively take into account the quality of movement while an individual is performing tasks. In this paper, we demonstrate the use of an integrated movement analysis framework, based on motion capture and ground reaction force data, to capture quantitative information about how subjects complete a commonly used functional outcome measure, the Box and Blocks Test (BBT). In order to test the usefulness of the integrated movement analysis framework in capturing the quality of movements during task performance, a motion restriction was induced in able-bodied participants that reproduces some of the limitations imposed by conventional prosthetics. Each subject performed the BBT under normal conditions and also under the motion restriction condition. The motion capture and ground force plates captured movement that significantly differed between the two conditions, with the largest differences seen in shoulder motion, in the range of motions of head tilt and elbow flexion, and in the area of the center of pressure trajectory. These preliminary results show the feasibility of incorporating standardized, quantitative movement analysis into the assessment of function for those with an upper limb disability.

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Year:  2017        PMID: 28422686     DOI: 10.1109/TNSRE.2017.2693234

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  5 in total

1.  Targeted box and blocks test: Normative data and comparison to standard tests.

Authors:  Kimberly Kontson; Ian Marcus; Barbara Myklebust; Eugene Civillico
Journal:  PLoS One       Date:  2017-05-19       Impact factor: 3.240

2.  Movement-Based Control for Upper-Limb Prosthetics: Is the Regression Technique the Key to a Robust and Accurate Control?

Authors:  Mathilde Legrand; Manelle Merad; Etienne de Montalivet; Agnès Roby-Brami; Nathanaël Jarrassé
Journal:  Front Neurorobot       Date:  2018-07-26       Impact factor: 2.650

3.  Comparison of DEKA Arm and Body-Powered Upper Limb Prosthesis Joint Kinematics.

Authors:  Conor Bloomer; Kimberly L Kontson
Journal:  Arch Rehabil Res Clin Transl       Date:  2020-04-25

4.  Application of machine learning to the identification of joint degrees of freedom involved in abnormal movement during upper limb prosthesis use.

Authors:  Sophie L Wang; Conor Bloomer; Gene Civillico; Kimberly Kontson
Journal:  PLoS One       Date:  2021-02-11       Impact factor: 3.240

5.  Kinematic analysis of motor learning in upper limb body-powered bypass prosthesis training.

Authors:  Conor Bloomer; Sophie Wang; Kimberly Kontson
Journal:  PLoS One       Date:  2020-01-24       Impact factor: 3.240

  5 in total

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