Literature DB >> 32950760

Marker-less versus marker-based driven musculoskeletal models of the spine during static load-handling activities.

F Asadi1, N Arjmand2.   

Abstract

Evaluation of workers' body posture in workstations is a prerequisite to estimate spinal loads and assess risk of injury for the subsequent design of preventive interventions. The Microsoft Kinect™ sensor is, in this regard, advantageous over the traditional skin-marker-based optical motion capture systems for being marker-less, portable, cost-effective, and easy-to-use in real workplaces. While several studies have demonstrated the validity/reliability of the Kinect for posture measurements especially during gait trials, its capability to adequately drive a detailed spine musculoskeletal model for injury risk assessments remains to be investigated. Lumbosacral (L5-S1) load predictions of a Kinect-driven and a gold-standard marker-based Vicon-driven musculoskeletal model were compared for various standing static load-handling activities at different heights/asymmetry angles/distances. Full body kinematics of eight individuals each performing eighteen activities were simultaneously recorded by a single-front-placed Kinect and a 10-camera Vicon motion capture system and input to AnyBody Modeling System. The predicted spinal loads by the two models were in average different by 17.8 and 25.9% for the L5-S1 disc compressive and shear forces, respectively, with smaller errors for the activities at higher load heights. Some activities performed near the floor could, however, not be recorded by a single-front-placed Kinect sensor due to the joint occlusion. The capability of the Kinect to adequately drive a spine musculoskeletal model depended on the complexity of the activity. While a single front-placed Kinect camera can be used to evaluate spinal loads in a wide range of static/quasi-static activities, cautious should be exercised when evaluating tasks performed near the floor.
Copyright © 2020 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Injury risk; Kinect; Load-handling; Lumbar spine; Motion analysis; Musculoskeletal model

Mesh:

Year:  2020        PMID: 32950760     DOI: 10.1016/j.jbiomech.2020.110043

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.712


  3 in total

1.  A Wearable System Based on Multiple Magnetic and Inertial Measurement Units for Spine Mobility Assessment: A Reliability Study for the Evaluation of Ankylosing Spondylitis.

Authors:  Adriana Martínez-Hernández; Juan S Perez-Lomelí; Ruben Burgos-Vargas; Miguel A Padilla-Castañeda
Journal:  Sensors (Basel)       Date:  2022-02-10       Impact factor: 3.576

2.  Feasibility and validity of a single camera CNN driven musculoskeletal model for muscle force estimation during upper extremity strength exercises: Proof-of-concept.

Authors:  Lisa Noteboom; Marco J M Hoozemans; H E J Veeger; Frans C T Van Der Helm
Journal:  Front Sports Act Living       Date:  2022-09-23

3.  Simple benchmarking method for determining the accuracy of depth cameras in body landmark location estimation: Static upright posture as a measurement example.

Authors:  Pin-Ling Liu; Chien-Chi Chang; Jia-Hua Lin; Yoshiyuki Kobayashi
Journal:  PLoS One       Date:  2021-07-21       Impact factor: 3.240

  3 in total

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