EMG Validation of a Subject-Specific Thoracolumbar Spine Musculoskeletal Model During Dynamic Activities in Older Adults

Musculoskeletal models can uniquely estimate in vivo demands and injury risk. In this study, we aimed to compare muscle activations from subject-specific thoracolumbar spine OpenSim models with recorded muscle activity from electromyography (EMG) during five dynamic tasks. Specifically, 11 older adu...

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Bibliographic Details
Published inAnnals of biomedical engineering Vol. 51; no. 10; pp. 2313 - 2322
Main Authors Alemi, Mohammad Mehdi, Banks, Jacob J., Lynch, Andrew C., Allaire, Brett T., Bouxsein, Mary L., Anderson, Dennis E.
Format Journal Article
LanguageEnglish
Published Cham Springer International Publishing 01.10.2023
Springer Nature B.V
Subjects
Adults
Aged
Biochemistry
Biological and Medical Physics
Biomechanical Phenomena
Biomedical and Life Sciences
Biomedical Engineering and Bioengineering
Biomedicine
Biophysics
Body mass
Classical Mechanics
Cross correlation
Electromyography
Electromyography - methods
Health risks
Humans
In vivo methods and tests
Muscle, Skeletal - physiology
Muscles
Older people
Original Article
Rotating bodies
Similarity
Spine
OpenSim
Validation
Musculoskeletal model
Thoracolumbar spine
Electromyography (EMG)
Online AccessGet full text

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Abstract Musculoskeletal models can uniquely estimate in vivo demands and injury risk. In this study, we aimed to compare muscle activations from subject-specific thoracolumbar spine OpenSim models with recorded muscle activity from electromyography (EMG) during five dynamic tasks. Specifically, 11 older adults (mean = 65 years, SD = 9) lifted a crate weighted to 10% of their body mass in axial rotation, 2-handed sagittal lift, 1-handed sagittal lift, and lateral bending, and simulated a window opening task. EMG measurements of back and abdominal muscles were directly compared to equivalent model-predicted activity for temporal similarity via maximum absolute normalized cross-correlation (MANCC) coefficients and for magnitude differences via root-mean-square errors (RMSE), across all combinations of participants, dynamic tasks, and muscle groups. We found that across most of the tasks the model reasonably predicted temporal behavior of back extensor muscles (median MANCC = 0.92 ± 0.07) but moderate temporal similarity was observed for abdominal muscles (median MANCC = 0.60 ± 0.20). Activation magnitude was comparable to previous modeling studies, and median RMSE was 0.18 ± 0.08 for back extensor muscles. Overall, these results indicate that our thoracolumbar spine model can be used to estimate subject-specific in vivo muscular activations for these dynamic lifting tasks.
AbstractList Musculoskeletal models can uniquely estimate in vivo demands and injury risk. In this study, we aimed to compare muscle activations from participant-specific thoracolumbar spine OpenSim models with recorded muscle activity (EMG) during five dynamic tasks. Specifically, 11 older adults (mean = 65 years, SD = 9) lifted a crate weighted to 10% of their body mass in axial rotation, 2-handed sagittal lift, 1-handed sagittal lift, and lateral bending, and simulated a window opening task. EMG measurements of back and abdominal muscles were directly compared to equivalent model-predicted activity for both temporal similarity via maximum absolute normalized cross-correlation (MANCC) coefficients and magnitude differences via root mean square errors (RMSE), across all combinations of participants, dynamic tasks, and muscle groups. We found that the model reasonably predicted temporal behavior of back extensor muscles (median MANCC = 0.92±0.07) but moderate temporal similarity was observed for abdominal muscles (median MANCC = 0.60±0.20) across most of the tasks. Activation magnitude was comparable to previous modeling studies, and median RMSE was 0.18±0.08 for back extensor muscles. Overall, these results indicate that our thoracolumbar spine model can be used to estimate participant-specific in vivo muscular activations for these dynamic lifting tasks.
Musculoskeletal models can uniquely estimate in vivo demands and injury risk. In this study, we aimed to compare muscle activations from subject-specific thoracolumbar spine OpenSim models with recorded muscle activity from electromyography (EMG) during five dynamic tasks. Specifically, 11 older adults (mean = 65 years, SD = 9) lifted a crate weighted to 10% of their body mass in axial rotation, 2-handed sagittal lift, 1-handed sagittal lift, and lateral bending, and simulated a window opening task. EMG measurements of back and abdominal muscles were directly compared to equivalent model-predicted activity for temporal similarity via maximum absolute normalized cross-correlation (MANCC) coefficients and for magnitude differences via root-mean-square errors (RMSE), across all combinations of participants, dynamic tasks, and muscle groups. We found that across most of the tasks the model reasonably predicted temporal behavior of back extensor muscles (median MANCC = 0.92 ± 0.07) but moderate temporal similarity was observed for abdominal muscles (median MANCC = 0.60 ± 0.20). Activation magnitude was comparable to previous modeling studies, and median RMSE was 0.18 ± 0.08 for back extensor muscles. Overall, these results indicate that our thoracolumbar spine model can be used to estimate subject-specific in vivo muscular activations for these dynamic lifting tasks.Musculoskeletal models can uniquely estimate in vivo demands and injury risk. In this study, we aimed to compare muscle activations from subject-specific thoracolumbar spine OpenSim models with recorded muscle activity from electromyography (EMG) during five dynamic tasks. Specifically, 11 older adults (mean = 65 years, SD = 9) lifted a crate weighted to 10% of their body mass in axial rotation, 2-handed sagittal lift, 1-handed sagittal lift, and lateral bending, and simulated a window opening task. EMG measurements of back and abdominal muscles were directly compared to equivalent model-predicted activity for temporal similarity via maximum absolute normalized cross-correlation (MANCC) coefficients and for magnitude differences via root-mean-square errors (RMSE), across all combinations of participants, dynamic tasks, and muscle groups. We found that across most of the tasks the model reasonably predicted temporal behavior of back extensor muscles (median MANCC = 0.92 ± 0.07) but moderate temporal similarity was observed for abdominal muscles (median MANCC = 0.60 ± 0.20). Activation magnitude was comparable to previous modeling studies, and median RMSE was 0.18 ± 0.08 for back extensor muscles. Overall, these results indicate that our thoracolumbar spine model can be used to estimate subject-specific in vivo muscular activations for these dynamic lifting tasks.
Musculoskeletal models can uniquely estimate in vivo demands and injury risk. In this study, we aimed to compare muscle activations from subject-specific thoracolumbar spine OpenSim models with recorded muscle activity from electromyography (EMG) during five dynamic tasks. Specifically, 11 older adults (mean = 65 years, SD = 9) lifted a crate weighted to 10% of their body mass in axial rotation, 2-handed sagittal lift, 1-handed sagittal lift, and lateral bending, and simulated a window opening task. EMG measurements of back and abdominal muscles were directly compared to equivalent model-predicted activity for temporal similarity via maximum absolute normalized cross-correlation (MANCC) coefficients and for magnitude differences via root-mean-square errors (RMSE), across all combinations of participants, dynamic tasks, and muscle groups. We found that across most of the tasks the model reasonably predicted temporal behavior of back extensor muscles (median MANCC = 0.92 ± 0.07) but moderate temporal similarity was observed for abdominal muscles (median MANCC = 0.60 ± 0.20). Activation magnitude was comparable to previous modeling studies, and median RMSE was 0.18 ± 0.08 for back extensor muscles. Overall, these results indicate that our thoracolumbar spine model can be used to estimate subject-specific in vivo muscular activations for these dynamic lifting tasks.
Musculoskeletal models can uniquely estimate in vivo demands and injury risk. In this study, we aimed to compare muscle activations from subject-specific thoracolumbar spine OpenSim models with recorded muscle activity from electromyography (EMG) during five dynamic tasks. Specifically, 11 older adults (mean = 65 years, SD = 9) lifted a crate weighted to 10% of their body mass in axial rotation, 2-handed sagittal lift, 1-handed sagittal lift, and lateral bending, and simulated a window opening task. EMG measurements of back and abdominal muscles were directly compared to equivalent model-predicted activity for temporal similarity via maximum absolute normalized cross-correlation (MANCC) coefficients and for magnitude differences via root-mean-square errors (RMSE), across all combinations of participants, dynamic tasks, and muscle groups. We found that across most of the tasks the model reasonably predicted temporal behavior of back extensor muscles (median MANCC = 0.92 ± 0.07) but moderate temporal similarity was observed for abdominal muscles (median MANCC = 0.60 ± 0.20). Activation magnitude was comparable to previous modeling studies, and median RMSE was 0.18 ± 0.08 for back extensor muscles. Overall, these results indicate that our thoracolumbar spine model can be used to estimate subject-specific in vivo muscular activations for these dynamic lifting tasks.
Author Anderson, Dennis E.
Alemi, Mohammad Mehdi
Banks, Jacob J.
Lynch, Andrew C.
Allaire, Brett T.
Bouxsein, Mary L.
AuthorAffiliation 1 Center for Advanced Orthopaedic Studies, Beth Israel Deaconess Medical Center, Boston, MA, United States
2 Department of Orthopaedic Surgery, Harvard Medical School, Boston, MA, United States
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  fullname: Anderson, Dennis E.
  organization: Center for Advanced Orthopaedic Studies, Beth Israel Deaconess Medical Center, Department of Orthopaedic Surgery, Harvard Medical School
BackLink https://www.ncbi.nlm.nih.gov/pubmed/37353715$$D View this record in MEDLINE/PubMed
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Fri Jul 25 19:13:59 EDT 2025
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Thu Apr 24 23:04:03 EDT 2025
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Keywords OpenSim
Validation
Musculoskeletal model
Thoracolumbar spine
Electromyography (EMG)
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License 2023. The Author(s) under exclusive licence to Biomedical Engineering Society.
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Snippet Musculoskeletal models can uniquely estimate in vivo demands and injury risk. In this study, we aimed to compare muscle activations from subject-specific...
Musculoskeletal models can uniquely estimate in vivo demands and injury risk. In this study, we aimed to compare muscle activations from participant-specific...
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SubjectTerms Adults
Aged
Biochemistry
Biological and Medical Physics
Biomechanical Phenomena
Biomedical and Life Sciences
Biomedical Engineering and Bioengineering
Biomedicine
Biophysics
Body mass
Classical Mechanics
Cross correlation
Electromyography
Electromyography - methods
Health risks
Humans
In vivo methods and tests
Muscle, Skeletal - physiology
Muscles
Older people
Original Article
Rotating bodies
Similarity
Spine
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Title EMG Validation of a Subject-Specific Thoracolumbar Spine Musculoskeletal Model During Dynamic Activities in Older Adults
URI https://link.springer.com/article/10.1007/s10439-023-03273-3
https://www.ncbi.nlm.nih.gov/pubmed/37353715
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Volume 51
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