Assessment of the sensitivity of thoracic injury criteria to subject-specific characteristics using human body models
Introduction: Chest deformation has been proposed as the best predictor of thoracic injury risk in frontal impacts. Finite Element Human Body Models (FE-HBM) can enhance the results obtained in physical crash tests with Anthropometric Test Devices (ATD) since they can be exposed to omnidirectional i...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-02-01
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| Series: | Frontiers in Bioengineering and Biotechnology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fbioe.2023.1106554/full |
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| author | Ana Piqueras Johan Iraeus Bengt Pipkorn Francisco J. López-Valdés |
| author_facet | Ana Piqueras Johan Iraeus Bengt Pipkorn Francisco J. López-Valdés |
| author_sort | Ana Piqueras |
| collection | DOAJ |
| description | Introduction: Chest deformation has been proposed as the best predictor of thoracic injury risk in frontal impacts. Finite Element Human Body Models (FE-HBM) can enhance the results obtained in physical crash tests with Anthropometric Test Devices (ATD) since they can be exposed to omnidirectional impacts and their geometry can be modified to reflect specific population groups. This study aims to assess the sensitivity of two thoracic injury risk criteria (PC Score and Cmax) to several personalization techniques of FE-HBMs.Methods: Three 30° nearside oblique sled tests were reproduced using the SAFER HBM v8 and three personalization techniques were applied to this model to evaluate the influence on the risk of thoracic injuries. First, the overall mass of the model was adjusted to represent the weight of the subjects. Second, the model anthropometry and mass were modified to represent the characteristics of the post-mortem human subjects (PMHS). Finally, the spine alignment of the model was adapted to the PMHS posture at t = 0 ms, to conform to the angles between spinal landmarks measured in the PMHS. The following two metrics were used to predict three or more fractured ribs (AIS3+) of the SAFER HBM v8 and the effect of personalization techniques: the maximum posterior displacement of any studied chest point (Cmax), and the sum of the upper and lower deformation of selected rib points (PC score).Results: Despite having led to statistically significant differences in the probability of AIS3+ calculations, the mass-scaled and morphed version provided, in general, lower values for injury risk than the baseline model and the postured version being the latter, which exhibited the better approximation to the PMHS tests in terms of probability of injury. Additionally, this study found that the prediction of AIS3+ chest injuries based on PC Score resulted in higher probability values than the prediction based on Cmax for the loading conditions and personalization techniques analyzed within this study.Discussion: This study could demonstrate that the personalization techniques do not lead to linear trends when they are used in combination. Furthermore, the results included here suggest that these two criteria will result in significantly different predictions if the chest is loaded more asymmetrically. |
| first_indexed | 2024-04-10T15:36:33Z |
| format | Article |
| id | doaj.art-57a5683860c74eb7838c26edf9e96c60 |
| institution | Directory Open Access Journal |
| issn | 2296-4185 |
| language | English |
| last_indexed | 2024-04-10T15:36:33Z |
| publishDate | 2023-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Bioengineering and Biotechnology |
| spelling | doaj.art-57a5683860c74eb7838c26edf9e96c602023-02-13T04:51:47ZengFrontiers Media S.A.Frontiers in Bioengineering and Biotechnology2296-41852023-02-011110.3389/fbioe.2023.11065541106554Assessment of the sensitivity of thoracic injury criteria to subject-specific characteristics using human body modelsAna Piqueras0Johan Iraeus1Bengt Pipkorn2Francisco J. López-Valdés3Department of Mechanical Engineering, EINA, University of Zaragoza, Zaragoza, SpainDivision of Vehicle Safety, Department of Mechanics and Maritime Sciences, Chalmers University of Technology, Gothenburg, SwedenAutoliv Research, Vargarda, SwedenInstituto de Investigación Tecnológica (IIT), Department of Mechanical Engineering, ICAI, Universidad Pontificia Comillas, Madrid, SpainIntroduction: Chest deformation has been proposed as the best predictor of thoracic injury risk in frontal impacts. Finite Element Human Body Models (FE-HBM) can enhance the results obtained in physical crash tests with Anthropometric Test Devices (ATD) since they can be exposed to omnidirectional impacts and their geometry can be modified to reflect specific population groups. This study aims to assess the sensitivity of two thoracic injury risk criteria (PC Score and Cmax) to several personalization techniques of FE-HBMs.Methods: Three 30° nearside oblique sled tests were reproduced using the SAFER HBM v8 and three personalization techniques were applied to this model to evaluate the influence on the risk of thoracic injuries. First, the overall mass of the model was adjusted to represent the weight of the subjects. Second, the model anthropometry and mass were modified to represent the characteristics of the post-mortem human subjects (PMHS). Finally, the spine alignment of the model was adapted to the PMHS posture at t = 0 ms, to conform to the angles between spinal landmarks measured in the PMHS. The following two metrics were used to predict three or more fractured ribs (AIS3+) of the SAFER HBM v8 and the effect of personalization techniques: the maximum posterior displacement of any studied chest point (Cmax), and the sum of the upper and lower deformation of selected rib points (PC score).Results: Despite having led to statistically significant differences in the probability of AIS3+ calculations, the mass-scaled and morphed version provided, in general, lower values for injury risk than the baseline model and the postured version being the latter, which exhibited the better approximation to the PMHS tests in terms of probability of injury. Additionally, this study found that the prediction of AIS3+ chest injuries based on PC Score resulted in higher probability values than the prediction based on Cmax for the loading conditions and personalization techniques analyzed within this study.Discussion: This study could demonstrate that the personalization techniques do not lead to linear trends when they are used in combination. Furthermore, the results included here suggest that these two criteria will result in significantly different predictions if the chest is loaded more asymmetrically.https://www.frontiersin.org/articles/10.3389/fbioe.2023.1106554/fullhuman body model (HBM)injury metricsnearsideoblique impactthoracic injury riskpersonification |
| spellingShingle | Ana Piqueras Johan Iraeus Bengt Pipkorn Francisco J. López-Valdés Assessment of the sensitivity of thoracic injury criteria to subject-specific characteristics using human body models Frontiers in Bioengineering and Biotechnology human body model (HBM) injury metrics nearside oblique impact thoracic injury risk personification |
| title | Assessment of the sensitivity of thoracic injury criteria to subject-specific characteristics using human body models |
| title_full | Assessment of the sensitivity of thoracic injury criteria to subject-specific characteristics using human body models |
| title_fullStr | Assessment of the sensitivity of thoracic injury criteria to subject-specific characteristics using human body models |
| title_full_unstemmed | Assessment of the sensitivity of thoracic injury criteria to subject-specific characteristics using human body models |
| title_short | Assessment of the sensitivity of thoracic injury criteria to subject-specific characteristics using human body models |
| title_sort | assessment of the sensitivity of thoracic injury criteria to subject specific characteristics using human body models |
| topic | human body model (HBM) injury metrics nearside oblique impact thoracic injury risk personification |
| url | https://www.frontiersin.org/articles/10.3389/fbioe.2023.1106554/full |
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