Literature DB >> 29533202

Use of optical motion capture for the analysis of normative upper body kinematics during functional upper limb tasks: A systematic review.

Aïda M Valevicius1, Peter Y Jun2, Jacqueline S Hebert3, Albert H Vette4.   

Abstract

Quantifying three-dimensional upper body kinematics can be a valuable method for assessing upper limb function. Considering that kinematic model characteristics, performed tasks, and reported outcomes are not consistently standardized and exhibit significant variability across studies, the purpose of this review was to evaluate the literature investigating upper body kinematics in non-disabled individuals via optical motion capture. Specific objectives were to report on the kinematic model characteristics, performed functional tasks, and kinematic outcomes, and to assess whether kinematic protocols were assessed for validity and reliability. Five databases were searched. Studies using anatomical and/or cluster marker sets, along with optical motion capture, and presenting normative data on upper body kinematics were eligible for review. Information extracted included model characteristics, performed functional tasks, kinematic outcomes, and validity or reliability testing. 804 publication records were screened and 20 reviewed based on the selection criteria. Thirteen studies described their kinematic protocols adequately for reproducibility, and 8 studies followed International Society of Biomechanics standards for quantifying upper body kinematics. Six studies assessed their protocols for validity or reliability. While a substantial number of studies have adequately reported their protocols, more systematic work is needed to evaluate the validity and reliability of existing protocols.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Keywords:  Activities of daily living; Functional tasks; Kinematic outcomes; Optical motion capture; Three-dimensional kinematics; Upper limb function

Mesh:

Year:  2018        PMID: 29533202     DOI: 10.1016/j.jelekin.2018.02.011

Source DB:  PubMed          Journal:  J Electromyogr Kinesiol        ISSN: 1050-6411            Impact factor:   2.368


  10 in total

1.  Automatic Identification of Upper Extremity Rehabilitation Exercise Type and Dose Using Body-Worn Sensors and Machine Learning: A Pilot Study.

Authors:  Noah Balestra; Gaurav Sharma; Linda M Riek; Ania Busza
Journal:  Digit Biomark       Date:  2021-07-02

2.  Quantitative Eye Gaze and Movement Differences in Visuomotor Adaptations to Varying Task Demands Among Upper-Extremity Prosthesis Users.

Authors:  Jacqueline S Hebert; Quinn A Boser; Aïda M Valevicius; Hiroki Tanikawa; Ewen B Lavoie; Albert H Vette; Patrick M Pilarski; Craig S Chapman
Journal:  JAMA Netw Open       Date:  2019-09-04

3.  Myoelectric prosthesis users and non-disabled individuals wearing a simulated prosthesis exhibit similar compensatory movement strategies.

Authors:  Heather E Williams; Craig S Chapman; Patrick M Pilarski; Albert H Vette; Jacqueline S Hebert
Journal:  J Neuroeng Rehabil       Date:  2021-05-01       Impact factor: 4.262

4.  Automatically Determining Lumbar Load during Physically Demanding Work: A Validation Study.

Authors:  Charlotte Christina Roossien; Christian Theodoor Maria Baten; Mitchel Willem Pieter van der Waard; Michiel Felix Reneman; Gijsbertus Jacob Verkerke
Journal:  Sensors (Basel)       Date:  2021-04-02       Impact factor: 3.576

5.  Assessing the validity of inertial measurement units for shoulder kinematics using a commercial sensor-software system: A validation study.

Authors:  Jakob Henschke; Hannes Kaplick; Monique Wochatz; Tilman Engel
Journal:  Health Sci Rep       Date:  2022-08-10

6.  Topographic design in wearable MXene sensors with in-sensor machine learning for full-body avatar reconstruction.

Authors:  Haitao Yang; Jiali Li; Xiao Xiao; Jiahao Wang; Yufei Li; Kerui Li; Zhipeng Li; Haochen Yang; Qian Wang; Jie Yang; John S Ho; Po-Len Yeh; Koen Mouthaan; Xiaonan Wang; Sahil Shah; Po-Yen Chen
Journal:  Nat Commun       Date:  2022-09-09       Impact factor: 17.694

Review 7.  Optical Motion Capture Systems for 3D Kinematic Analysis in Patients with Shoulder Disorders.

Authors:  Umile Giuseppe Longo; Sergio De Salvatore; Arianna Carnevale; Salvatore Maria Tecce; Benedetta Bandini; Alberto Lalli; Emiliano Schena; Vincenzo Denaro
Journal:  Int J Environ Res Public Health       Date:  2022-09-23       Impact factor: 4.614

8.  Building FAIR Functionality: Annotating Events in Time Series Data Using Hierarchical Event Descriptors (HED).

Authors:  Kay Robbins; Dung Truong; Alexander Jones; Ian Callanan; Scott Makeig
Journal:  Neuroinformatics       Date:  2021-12-30

9.  Gaze and Movement Assessment (GaMA): Inter-site validation of a visuomotor upper limb functional protocol.

Authors:  Heather E Williams; Craig S Chapman; Patrick M Pilarski; Albert H Vette; Jacqueline S Hebert
Journal:  PLoS One       Date:  2019-12-30       Impact factor: 3.240

10.  Marker Placement Reliability and Objectivity for Biomechanical Cohort Study: Healthy Aging in Industrial Environment (HAIE-Program 4).

Authors:  Jan Malus; Jiri Skypala; Julia Freedman Silvernail; Jaroslav Uchytil; Joseph Hamill; Tomas Barot; Daniel Jandacka
Journal:  Sensors (Basel)       Date:  2021-03-05       Impact factor: 3.576

  10 in total

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