Literature DB >> 32340969

Reachable Workspace and Proximal Function Measures for Quantifying Upper Limb Motion.

Robert P Matthew, Sarah Seko, Gregorij Kurillo, Ruzena Bajcsy, Louis Cheng, Jay J Han, Jeffrey Lotz.   

Abstract

There are a lack of quantitative measures for clinically assessing upper limb function. Conventional biomechanical performance measures are restricted to specialist labs due to hardware cost and complexity, while the resulting measurements require specialists for analysis. Depth cameras are low cost and portable systems that can track surrogate joint positions. However, these motions may not be biologically consistent, which can result in noisy, inaccurate movements. This paper introduces a rigid body modelling method to enforce biological feasibility of the recovered motions. This method is evaluated on an existing depth camera assessment: the reachable workspace (RW) measure for assessing gross shoulder function. As a rigid body model is used, position estimates of new proximal targets can be added, resulting in a proximal function (PF) measure for assessing a subject's ability to touch specific body landmarks. The accuracy, and repeatability of these measures is assessed on ten asymptomatic subjects, with and without rigid body constraints. This analysis is performed both on a low-cost depth camera system and a gold-standard active motion capture system. The addition of rigid body constraints was found to improve accuracy and concordance of the depth camera system, particularly in lateral reaching movements. Both RW and PF measures were found to be feasible candidates for clinical assessment, with future analysis needed to determine their ability to detect changes within specific patient populations.

Entities:  

Year:  2020        PMID: 32340969     DOI: 10.1109/JBHI.2020.2989722

Source DB:  PubMed          Journal:  IEEE J Biomed Health Inform        ISSN: 2168-2194            Impact factor:   5.772


  2 in total

1.  Feasibility and effectiveness of a novel dynamic arm support in persons with spinal muscular atrophy and duchenne muscular dystrophy.

Authors:  Mariska M H P Janssen; Jolinda Horstik; Paulien Klap; Imelda J M de Groot
Journal:  J Neuroeng Rehabil       Date:  2021-05-21       Impact factor: 4.262

2.  The Black Box of Technological Outcome Measures: An Example in Duchenne Muscular Dystrophy.

Authors:  Karin J Naarding; Mariska M H P Janssen; Ruben D Boon; Paulina J M Bank; Robert P Matthew; Gregorij Kurillo; Jay J Han; Jan J G M Verschuuren; Imelda J M de Groot; Menno van der Holst; Hermien E Kan; Erik H Niks
Journal:  J Neuromuscul Dis       Date:  2022
  2 in total

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