Computing Brain White and Grey Matter Injury Severity in a Traumatic Fall
In the real world, the severity of traumatic injuries is measured using the Abbreviated Injury Scale (AIS). However, the AIS scale cannot currently be computed by using the output from finite element human computer models, which currently rely on maximum principal strains (MPS) to capture serious an...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-09-01
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| Series: | Mathematical and Computational Applications |
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| Online Access: | https://www.mdpi.com/2297-8747/25/3/61 |
| _version_ | 1797552941288128512 |
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| author | Christophe Bastien Clive Neal-Sturgess Huw Davies Xiang Cheng |
| author_facet | Christophe Bastien Clive Neal-Sturgess Huw Davies Xiang Cheng |
| author_sort | Christophe Bastien |
| collection | DOAJ |
| description | In the real world, the severity of traumatic injuries is measured using the Abbreviated Injury Scale (AIS). However, the AIS scale cannot currently be computed by using the output from finite element human computer models, which currently rely on maximum principal strains (MPS) to capture serious and fatal injuries. In order to overcome these limitations, a unique Organ Trauma Model (OTM) able to calculate the threat to the life of a brain model at all AIS levels is introduced. The OTM uses a power method, named Peak Virtual Power (PVP), and defines brain white and grey matter trauma responses as a function of impact location and impact speed. This research has considered ageing in the injury severity computation by including soft tissue material degradation, as well as brain volume changes due to ageing. Further, to account for the limitations of the Lagrangian formulation of the brain model in representing hemorrhage, an approach to include the effects of subdural hematoma is proposed and included as part of the predictions. The OTM model was tested against two real-life falls and has proven to correctly predict the post-mortem outcomes. This paper is a proof of concept, and pending more testing, could support forensic studies. |
| first_indexed | 2024-03-10T16:08:17Z |
| format | Article |
| id | doaj.art-041bcf775be34817b0837c7594706add |
| institution | Directory Open Access Journal |
| issn | 1300-686X 2297-8747 |
| language | English |
| last_indexed | 2024-03-10T16:08:17Z |
| publishDate | 2020-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematical and Computational Applications |
| spelling | doaj.art-041bcf775be34817b0837c7594706add2023-11-20T14:40:48ZengMDPI AGMathematical and Computational Applications1300-686X2297-87472020-09-012536110.3390/mca25030061Computing Brain White and Grey Matter Injury Severity in a Traumatic FallChristophe Bastien0Clive Neal-Sturgess1Huw Davies2Xiang Cheng3Institute for Future Transport and Cities, Coventry University, Priory Street, Coventry CV1 5FB, UKDepartment of Mechanical Engineering, University of Birmingham, Edgbaston, Birmingham B15 2TT, UKInstitute for Future Transport and Cities, Coventry University, Priory Street, Coventry CV1 5FB, UKInstitute for Future Transport and Cities, Coventry University, Priory Street, Coventry CV1 5FB, UKIn the real world, the severity of traumatic injuries is measured using the Abbreviated Injury Scale (AIS). However, the AIS scale cannot currently be computed by using the output from finite element human computer models, which currently rely on maximum principal strains (MPS) to capture serious and fatal injuries. In order to overcome these limitations, a unique Organ Trauma Model (OTM) able to calculate the threat to the life of a brain model at all AIS levels is introduced. The OTM uses a power method, named Peak Virtual Power (PVP), and defines brain white and grey matter trauma responses as a function of impact location and impact speed. This research has considered ageing in the injury severity computation by including soft tissue material degradation, as well as brain volume changes due to ageing. Further, to account for the limitations of the Lagrangian formulation of the brain model in representing hemorrhage, an approach to include the effects of subdural hematoma is proposed and included as part of the predictions. The OTM model was tested against two real-life falls and has proven to correctly predict the post-mortem outcomes. This paper is a proof of concept, and pending more testing, could support forensic studies.https://www.mdpi.com/2297-8747/25/3/61brain trauma modellingorgan trauma modelpeak virtual powerfalltrauma modelling |
| spellingShingle | Christophe Bastien Clive Neal-Sturgess Huw Davies Xiang Cheng Computing Brain White and Grey Matter Injury Severity in a Traumatic Fall Mathematical and Computational Applications brain trauma modelling organ trauma model peak virtual power fall trauma modelling |
| title | Computing Brain White and Grey Matter Injury Severity in a Traumatic Fall |
| title_full | Computing Brain White and Grey Matter Injury Severity in a Traumatic Fall |
| title_fullStr | Computing Brain White and Grey Matter Injury Severity in a Traumatic Fall |
| title_full_unstemmed | Computing Brain White and Grey Matter Injury Severity in a Traumatic Fall |
| title_short | Computing Brain White and Grey Matter Injury Severity in a Traumatic Fall |
| title_sort | computing brain white and grey matter injury severity in a traumatic fall |
| topic | brain trauma modelling organ trauma model peak virtual power fall trauma modelling |
| url | https://www.mdpi.com/2297-8747/25/3/61 |
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