Literature DB >> 27810690

A video based method to quantify posture of the head and trunk in sitting.

María B Sánchez1, Ian Loram2, John Darby3, Paul Holmes4, Penelope B Butler5.   

Abstract

Maintenance of a vertically aligned posture of the head and trunk in sitting is a fundamental skill that demonstrates the presence of neuromotor control. Clinical assessments of posture are generally subjective. Studies have quantified posture using different technologies, but the application of such technologies in a clinical environment remains difficult. Video recordings, however, are easily used clinically and have potential for quantitative analysis of movement. This study used a video-based method to generate a numerical measure of postural alignment of the head and trunk in sitting. Static and dynamic trials of 12 healthy seated adults were simultaneously recorded with a sagittal video camera and a 3D motion capture system. Segmental angles were calculated for the Head, Neck and six Trunk segments. An agreed definition of aligned static sitting posture agreed was used by five clinically experienced experts to identify video frames where the participants' posture was aligned. The five subsets of frames that defined the aligned posture were combined to give aligned segments (mean±SD) for each participant. Agreement between experts in the definition (mean) of aligned segmental angles was excellent (ICC=0.99) and intra-assessor reliability (SD) lay within 2.1°-11.6°. Agreement between the video-based method and the 3D system was below 3.8° and 8.4° for static and dynamic trials respectively. This video-based method allowed the quantification of sitting posture and provided greater detail of the trunk/spinal profile than previous methods. It has potential as a complementary tool, alongside subjective assessments, for patients with a wide variety of pathologies. Copyright Â
© 2016 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Alignment; Multi-segmental model; Posture; Sitting; Video

Mesh:

Year:  2016        PMID: 27810690     DOI: 10.1016/j.gaitpost.2016.10.012

Source DB:  PubMed          Journal:  Gait Posture        ISSN: 0966-6362            Impact factor:   2.840


  2 in total

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Authors:  Long Liu; Sen Qiu; ZheLong Wang; Jie Li; JiaXin Wang
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2.  The Validity, Reliability, and Sensitivity of a Smartphone-Based Seated Postural Control Assessment in Wheelchair Users: A Pilot Study.

Authors:  Mikaela L Frechette; Libak Abou; Laura A Rice; Jacob J Sosnoff
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  2 in total

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