Between-session reliability of subject-specific musculoskeletal models of the spine derived from optoelectronic motion capture data
This study evaluated the between-session reliability of creating subject-specific musculoskeletal models with optoelectronic motion capture data, and using them to estimate spine loading. Nineteen healthy participants aged 24–74 years underwent the same set of measurements on two separate occasions....
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Published in | Journal of biomechanics Vol. 112; p. 110044 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
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United States
Elsevier Ltd
09.11.2020
Elsevier Limited |
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Abstract | This study evaluated the between-session reliability of creating subject-specific musculoskeletal models with optoelectronic motion capture data, and using them to estimate spine loading. Nineteen healthy participants aged 24–74 years underwent the same set of measurements on two separate occasions. Retroreflective markers were placed on anatomical regions, including C7, T1, T4, T5, T8, T9, T12 and L1 spinous processes, pelvis, upper and lower limbs, and head. We created full-body musculoskeletal models with detailed thoracolumbar spines, and scaled these to create subject-specific models for each individual and each session. Models were scaled from distances between markers, and spine curvature was adjusted according to marker-estimated measurements. Using these models, we estimated vertebral compressive loading for five different standardized postures: neutral standing, 45˚ trunk flexion, 15˚ trunk extension, 20˚ lateral bend to the right, and 45˚ axial rotation to the right. Intraclass correlation coefficients (ICCs) and standard error of measurement were calculated as measures of between-session reliability and measurement error, respectively. Spine curvature measures showed excellent reliability (ICC = 0.79–0.91) and body scaling segments showed fair to excellent reliability (ICC = 0.46–0.95). We found that musculoskeletal models showed mostly excellent between-session reliability to estimate spine loading, with 91% of ICC values > 0.75 for all activities. This information is a necessary precursor for using motion capture data to estimate spine loading from subject-specific musculoskeletal models, and suggests that marker data will deliver reproducible subject-specific models and estimates of spine loading. |
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AbstractList | This study evaluated the between-session reliability of creating subject-specific musculoskeletal models with optoelectronic motion capture data, and using them to estimate spine loading. Nineteen healthy participants aged 24–74 years underwent the same set of measurements on two separate occasions. Retroreflective markers were placed on anatomical regions, including C7, T1, T4, T5, T8, T9, T12 and L1 spinous processes, pelvis, upper and lower limbs, and head. We created full-body musculoskeletal models with detailed thoracolumbar spines, and scaled these to create subject-specific models for each individual and each session. Models were scaled from distances between markers, and spine curvature was adjusted according to marker-estimated measurements. Using these models, we estimated vertebral compressive loading for five different standardized postures: neutral standing, 45° trunk flexion, 15° trunk extension, 20° lateral bend to the right, and 45° axial rotation to the right. Intraclass correlation coefficients (ICCs) and standard error of measurement were calculated as measures of between-session reliability and measurement error, respectively. Spine curvature measures showed excellent reliability (ICC= 0.79–0.91) and body scaling segments showed fair to excellent reliability (ICC = 0.46–0.95). We found that musculoskeletal models showed mostly excellent between-session reliability to estimate spine loading, with 91% of ICC values > 0.75 for all activities. This information is a necessary precursor for using motion capture data to estimate spine loading from subject-specific musculoskeletal models, and suggests that marker data will deliver reproducible subject-specific models and estimates of spine loading. This study evaluated the between-session reliability of creating subject-specific musculoskeletal models with optoelectronic motion capture data, and using them to estimate spine loading. Nineteen healthy participants aged 24-74 years underwent the same set of measurements on two separate occasions. Retroreflective markers were placed on anatomical regions, including C7, T1, T4, T5, T8, T9, T12 and L1 spinous processes, pelvis, upper and lower limbs, and head. We created full-body musculoskeletal models with detailed thoracolumbar spines, and scaled these to create subject-specific models for each individual and each session. Models were scaled from distances between markers, and spine curvature was adjusted according to marker-estimated measurements. Using these models, we estimated vertebral compressive loading for five different standardized postures: neutral standing, 45˚ trunk flexion, 15˚ trunk extension, 20˚ lateral bend to the right, and 45˚ axial rotation to the right. Intraclass correlation coefficients (ICCs) and standard error of measurement were calculated as measures of between-session reliability and measurement error, respectively. Spine curvature measures showed excellent reliability (ICC = 0.79-0.91) and body scaling segments showed fair to excellent reliability (ICC = 0.46-0.95). We found that musculoskeletal models showed mostly excellent between-session reliability to estimate spine loading, with 91% of ICC values > 0.75 for all activities. This information is a necessary precursor for using motion capture data to estimate spine loading from subject-specific musculoskeletal models, and suggests that marker data will deliver reproducible subject-specific models and estimates of spine loading.This study evaluated the between-session reliability of creating subject-specific musculoskeletal models with optoelectronic motion capture data, and using them to estimate spine loading. Nineteen healthy participants aged 24-74 years underwent the same set of measurements on two separate occasions. Retroreflective markers were placed on anatomical regions, including C7, T1, T4, T5, T8, T9, T12 and L1 spinous processes, pelvis, upper and lower limbs, and head. We created full-body musculoskeletal models with detailed thoracolumbar spines, and scaled these to create subject-specific models for each individual and each session. Models were scaled from distances between markers, and spine curvature was adjusted according to marker-estimated measurements. Using these models, we estimated vertebral compressive loading for five different standardized postures: neutral standing, 45˚ trunk flexion, 15˚ trunk extension, 20˚ lateral bend to the right, and 45˚ axial rotation to the right. Intraclass correlation coefficients (ICCs) and standard error of measurement were calculated as measures of between-session reliability and measurement error, respectively. Spine curvature measures showed excellent reliability (ICC = 0.79-0.91) and body scaling segments showed fair to excellent reliability (ICC = 0.46-0.95). We found that musculoskeletal models showed mostly excellent between-session reliability to estimate spine loading, with 91% of ICC values > 0.75 for all activities. This information is a necessary precursor for using motion capture data to estimate spine loading from subject-specific musculoskeletal models, and suggests that marker data will deliver reproducible subject-specific models and estimates of spine loading. This study evaluated the between-session reliability of creating subject-specific musculoskeletal models with optoelectronic motion capture data, and using them to estimate spine loading. Nineteen healthy participants aged 24–74 years underwent the same set of measurements on two separate occasions. Retroreflective markers were placed on anatomical regions, including C7, T1, T4, T5, T8, T9, T12 and L1 spinous processes, pelvis, upper and lower limbs, and head. We created full-body musculoskeletal models with detailed thoracolumbar spines, and scaled these to create subject-specific models for each individual and each session. Models were scaled from distances between markers, and spine curvature was adjusted according to marker-estimated measurements. Using these models, we estimated vertebral compressive loading for five different standardized postures: neutral standing, 45˚ trunk flexion, 15˚ trunk extension, 20˚ lateral bend to the right, and 45˚ axial rotation to the right. Intraclass correlation coefficients (ICCs) and standard error of measurement were calculated as measures of between-session reliability and measurement error, respectively. Spine curvature measures showed excellent reliability (ICC = 0.79–0.91) and body scaling segments showed fair to excellent reliability (ICC = 0.46–0.95). We found that musculoskeletal models showed mostly excellent between-session reliability to estimate spine loading, with 91% of ICC values > 0.75 for all activities. This information is a necessary precursor for using motion capture data to estimate spine loading from subject-specific musculoskeletal models, and suggests that marker data will deliver reproducible subject-specific models and estimates of spine loading. This study evaluated the between-session reliability of creating subject-specific musculoskeletal models with optoelectronic motion capture data, and using them to estimate spine loading. Nineteen healthy participants aged 24–74 years underwent the same set of measurements on two separate occasions. Retroreflective markers were placed on anatomical regions, including C7, T1, T4, T5, T8, T9, T12 and L1 spinous processes, pelvis, upper and lower limbs, and head. We created full-body musculoskeletal models with detailed thoracolumbar spines, and scaled these to create subject-specific models for each individual and each session. Models were scaled from distances between markers, and spine curvature was adjusted according to marker-estimated measurements. Using these models, we estimated vertebral compressive loading for five different standardized postures: neutral standing, 45˚ trunk flexion, 15˚ trunk extension, 20˚ lateral bend to the right, and 45˚ axial rotation to the right. Intraclass correlation coefficients (ICCs) and standard error of measurement were calculated as measures of between-session reliability and measurement error, respectively. Spine curvature measures showed excellent reliability (ICC = 0.79–0.91) and body scaling segments showed fair to excellent reliability (ICC = 0.46–0.95). We found that musculoskeletal models showed mostly excellent between-session reliability to estimate spine loading, with 91% of ICC values > 0.75 for all activities. This information is a necessary precursor for using motion capture data to estimate spine loading from subject-specific musculoskeletal models, and suggests that marker data will deliver reproducible subject-specific models and estimates of spine loading. |
ArticleNumber | 110044 |
Author | Grindle, Daniel Anderson, Dennis E. Burkhart, Katelyn Bouxsein, Mary L. |
AuthorAffiliation | 2 Center for Advanced Orthopaedic Studies, Beth Israel Deaconess Medical Center, 330 Brookline Ave., Boston 02215, Massachusetts 1 Harvard-MIT Health Sciences and Technology Program, Massachusetts Institute of Technology, Cambridge 02139, Massachusetts 4 Division of Engineering Mechanics, Department of Biomedical Engineering and Mechanics, Virginia Polytechnic Institute and State University, Blacksburg, VA, United States 3 Department of Orthopaedic Surgery, Harvard Medical School, Boston 02115, Massachusetts |
AuthorAffiliation_xml | – name: 2 Center for Advanced Orthopaedic Studies, Beth Israel Deaconess Medical Center, 330 Brookline Ave., Boston 02215, Massachusetts – name: 4 Division of Engineering Mechanics, Department of Biomedical Engineering and Mechanics, Virginia Polytechnic Institute and State University, Blacksburg, VA, United States – name: 1 Harvard-MIT Health Sciences and Technology Program, Massachusetts Institute of Technology, Cambridge 02139, Massachusetts – name: 3 Department of Orthopaedic Surgery, Harvard Medical School, Boston 02115, Massachusetts |
Author_xml | – sequence: 1 givenname: Katelyn surname: Burkhart fullname: Burkhart, Katelyn organization: Harvard-MIT Health Sciences and Technology Program, Massachusetts Institute of Technology, Cambridge 02139, MA, United States – sequence: 2 givenname: Daniel surname: Grindle fullname: Grindle, Daniel organization: Center for Advanced Orthopaedic Studies, Beth Israel Deaconess Medical Center, 330 Brookline Ave., Boston 02215, MA, United States – sequence: 3 givenname: Mary L. surname: Bouxsein fullname: Bouxsein, Mary L. organization: Harvard-MIT Health Sciences and Technology Program, Massachusetts Institute of Technology, Cambridge 02139, MA, United States – sequence: 4 givenname: Dennis E. surname: Anderson fullname: Anderson, Dennis E. email: danders7@harvard.bidmc.edu organization: Center for Advanced Orthopaedic Studies, Beth Israel Deaconess Medical Center, 330 Brookline Ave., Boston 02215, MA, United States |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/32977297$$D View this record in MEDLINE/PubMed |
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Keywords | Repeatability Model scaling Spine loading Musculoskeletal model Motion analysis |
Language | English |
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SubjectTerms | Adult Aged Ankle Back pain Biomechanical Phenomena Correlation coefficients Curvature Error analysis Hip joint Humans Investigations Markers Middle Aged Model scaling Motion analysis Motion capture Musculoskeletal model Optoelectronics Pelvis Posture Range of Motion, Articular Reliability analysis Repeatability Reproducibility of Results Rotation Spine Spine loading Standard error Vertebrae Young Adult |
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Title | Between-session reliability of subject-specific musculoskeletal models of the spine derived from optoelectronic motion capture data |
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