Using a marker-less method for estimating L5/S1 moments during symmetrical lifting

Rahil Mehrizi; Xu Xu; Shaoting Zhang; Vladimir Pavlovic; Dimitris Metaxas; Kang Li

doi:10.1016/j.apergo.2017.01.007

Using a marker-less method for estimating L5/S1 moments during symmetrical lifting

Rahil Mehrizi, Xu Xu, Shaoting Zhang, Vladimir Pavlovic, Dimitris Metaxas, Kang Li

Research output: Contribution to journal › Article › peer-review

15 Scopus citations

Abstract

The aim of this study is to analyze the validity of a computer vision-based method to estimate 3D L5/S1 joint moment during symmetrical lifting. An important criterion to identify the non-ergonomic lifting task is the value of net moment at L5/S1 joint. This is usually calculated in a laboratory environment which is not practical for on-site biomechanical analysis. The validity of the proposed method, was assessed externally by comparing the results with a lab-based reference method and internally by comparing the estimated L5/S1 joint moments from top-down model and bottom-up model. It was shown that no significant differences in peak and mean moments between the two methods and intra-class correlation coefficients revealed excellent reliability of the proposed method (>0.91). The proposed method provides a reliable tool for assessment of lower back loads during occupational lifting and can be an alternative when the use of marker-based motion tracking systems is not possible.

Original language	English (US)
Pages (from-to)	541-550
Number of pages	10
Journal	Applied Ergonomics
Volume	65
DOIs	https://doi.org/10.1016/j.apergo.2017.01.007
State	Published - Nov 2017

All Science Journal Classification (ASJC) codes

Human Factors and Ergonomics
Physical Therapy, Sports Therapy and Rehabilitation
Safety, Risk, Reliability and Quality
Engineering (miscellaneous)

Keywords

Computer vision
Lifting
Marker-less motion capture

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10.1016/j.apergo.2017.01.007

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title = "Using a marker-less method for estimating L5/S1 moments during symmetrical lifting",

abstract = "The aim of this study is to analyze the validity of a computer vision-based method to estimate 3D L5/S1 joint moment during symmetrical lifting. An important criterion to identify the non-ergonomic lifting task is the value of net moment at L5/S1 joint. This is usually calculated in a laboratory environment which is not practical for on-site biomechanical analysis. The validity of the proposed method, was assessed externally by comparing the results with a lab-based reference method and internally by comparing the estimated L5/S1 joint moments from top-down model and bottom-up model. It was shown that no significant differences in peak and mean moments between the two methods and intra-class correlation coefficients revealed excellent reliability of the proposed method (>0.91). The proposed method provides a reliable tool for assessment of lower back loads during occupational lifting and can be an alternative when the use of marker-based motion tracking systems is not possible.",

keywords = "Computer vision, Lifting, Marker-less motion capture",

author = "Rahil Mehrizi and Xu Xu and Shaoting Zhang and Vladimir Pavlovic and Dimitris Metaxas and Kang Li",

note = "Funding Information: This work was supported in part by the New Jersey Healthcare Foundation (PC106-13), and NSF (CNS 1229628, CMMI 1334389, IIS 1451292 and IIS 1555408). The human motion data was collected at Liberty Mutual Research Institute for Safety when the second author was in Harvard School of Public Health - Liberty Mutual postdoctoral program. Publisher Copyright: {\textcopyright} 2017 Elsevier Ltd",

year = "2017",

month = nov,

doi = "10.1016/j.apergo.2017.01.007",

language = "English (US)",

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AU - Mehrizi, Rahil

AU - Xu, Xu

AU - Zhang, Shaoting

AU - Pavlovic, Vladimir

AU - Metaxas, Dimitris

AU - Li, Kang

N1 - Funding Information: This work was supported in part by the New Jersey Healthcare Foundation (PC106-13), and NSF (CNS 1229628, CMMI 1334389, IIS 1451292 and IIS 1555408). The human motion data was collected at Liberty Mutual Research Institute for Safety when the second author was in Harvard School of Public Health - Liberty Mutual postdoctoral program. Publisher Copyright: © 2017 Elsevier Ltd

PY - 2017/11

Y1 - 2017/11

N2 - The aim of this study is to analyze the validity of a computer vision-based method to estimate 3D L5/S1 joint moment during symmetrical lifting. An important criterion to identify the non-ergonomic lifting task is the value of net moment at L5/S1 joint. This is usually calculated in a laboratory environment which is not practical for on-site biomechanical analysis. The validity of the proposed method, was assessed externally by comparing the results with a lab-based reference method and internally by comparing the estimated L5/S1 joint moments from top-down model and bottom-up model. It was shown that no significant differences in peak and mean moments between the two methods and intra-class correlation coefficients revealed excellent reliability of the proposed method (>0.91). The proposed method provides a reliable tool for assessment of lower back loads during occupational lifting and can be an alternative when the use of marker-based motion tracking systems is not possible.

AB - The aim of this study is to analyze the validity of a computer vision-based method to estimate 3D L5/S1 joint moment during symmetrical lifting. An important criterion to identify the non-ergonomic lifting task is the value of net moment at L5/S1 joint. This is usually calculated in a laboratory environment which is not practical for on-site biomechanical analysis. The validity of the proposed method, was assessed externally by comparing the results with a lab-based reference method and internally by comparing the estimated L5/S1 joint moments from top-down model and bottom-up model. It was shown that no significant differences in peak and mean moments between the two methods and intra-class correlation coefficients revealed excellent reliability of the proposed method (>0.91). The proposed method provides a reliable tool for assessment of lower back loads during occupational lifting and can be an alternative when the use of marker-based motion tracking systems is not possible.

KW - Computer vision

KW - Lifting

KW - Marker-less motion capture

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Using a marker-less method for estimating L5/S1 moments during symmetrical lifting

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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