Measurement of Three-Dimensional Back Shape of Normal Adults Using a Novel Three-Dimensional Imaging Mobile Surface Topography System (MSTS): An Intra- and Inter-Rater Reliability Study

Author:

Kandasamy Gok1ORCID,Bettany-Saltikov Josette1,Van Schaik Paul2

Affiliation:

1. School of Health and Life Sciences, Teesside University, Middlesbrough TS1 3BA, UK

2. Centre for Applied Psychological Science, School of Social Sciences and Law, Teesside University, Middlesbrough TS1 3BA, UK

Abstract

Postural and spinal deformities are major contributing factors to musculoskeletal (MSK) disorders. Posture screening and assessment can help to identify early morphological deformities, thereby preventing progression and reducing or correcting them with effective treatments. The study evaluates both intra- and inter-repeatability of using a mobile structured light sensor with a structured light pattern for building an accurate 3D human model and its use in postural screening. 16 young males (age: 25 ± 5.6 years, height: 172 ± 5.3 cm, mass: 69 ± 8.6 kg) participated without any musculoskeletal pain or pre-existing leg or spinal abnormalities. An iPad-based 3D mobile scanning tool, Structure SensorTM (2018 version), was used to capture the participants’ back and whole-body shape. The collected data (3D model) were realigned and processed in the open-source software, Netfabb BasicTM (7.2 version). For each participant, five trained raters individually measured three trials of standing back and body posture on two separate occasions to calculate both intra- and inter-rater reliability. With the use of this software, nine postural variables and angular displacements were individually measured by the raters. The results indicated good to excellent intra-rater and good to moderate inter-rater reliability for measuring 78% (7 out of 9) of postural variables with an ICC ranging from 0.70 to 0.98. The remaining 22% of variables (2 out of 9; lateral pelvic tilt and right frontal knee angle) showed moderate to low inter- and intra-rater reliability, with ICCs ranging from 0.26 to 0.79.

Publisher

MDPI AG

Subject

Health Information Management,Health Informatics,Health Policy,Leadership and Management

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