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Appraisal of the New Posture Analyzing and Virtual Reconstruction Device (PAViR) for Assessing Sagittal Posture Parameters: A Prospective Observational Study

Authors
 Chan Woong Jang  ;  Jihyun Park  ;  Han Eol Cho  ;  Jung Hyun Park 
Citation
 INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, Vol.19(17) : 11109, 2022-09 
Journal Title
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
ISSN
 1661-7827 
Issue Date
2022-09
MeSH
Artificial Intelligence* ; Humans ; Lordosis* ; Pelvis ; Posture ; Spine
Keywords
diagnostic imaging ; imaging ; posture ; skeleton ; spine ; three-dimensional
Abstract
The purpose of this study was to report the clinical validation of the posture analyzing and virtual reconstruction device (PAViR) system, focusing on the accuracy of sagittal spinal parameters, compared with the EOS imaging system. Seventy patients diagnosed with segmental and somatic dysfunction were recruited between February 2020 and November 2020. Each patient was examined using the EOS imaging system and PAViR; the sagittal parameters of human body posture [forward head posture (FHP), T1 tilt angle (T1t), knee flexion angle (KF), lumbar lordosis angle (LL), and pelvic tilt angle (PT)] were analyzed to verify the correlation between the results of the two devices. The median differences in the results of the two devices showed significant differences in FHP (T4-frontal head and T4-auditory canal), T1t, and PT. In the correlation analysis, the values of FHP (C7-auditory canal, T4-frontal head, and T4-auditory canal), T1t, and PT showed a moderate correlation between the two devices (r = 0.741, 0.795, 0.761, 0.621, and 0.692, respectively) (p < 0.001). The KF and LL was fairly correlated (r = 0.514 and 0.536, respectively) (p = 0.004, both). This study presents the potential of a novel skeletal imaging system without radiation exposure, based on a 3D red-green-blue-depth camera (PAViR), as a next-generation diagnostic tool by estimating more accurate parameters through continuous multi-data-based upgrades with artificial intelligence technology.
Files in This Item:
T202203860.pdf Download
DOI
10.3390/ijerph191711109
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Rehabilitation Medicine (재활의학교실) > 1. Journal Papers
Yonsei Authors
Park, Jung Hyun(박중현) ORCID logo https://orcid.org/0000-0003-3262-7476
Jang, Chan Woong(장찬웅)
Cho, Han Eol(조한얼) ORCID logo https://orcid.org/0000-0001-5625-3013
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/192037
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