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Hostetler ZS, Gayzik FS. Lower Extremity Injury Risk Curve Development for a Human Body Model in the Underbody Blast Environment. J Biomech Eng 2024; 146:031006. [PMID: 37682582 DOI: 10.1115/1.4063349] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Accepted: 08/30/2023] [Indexed: 09/09/2023]
Abstract
Computational human body models (HBMs) provide the ability to explore numerous candidate injury metrics ranging from local strain based criteria to global combined criteria such as the Tibia Index. Despite these efforts, there have been relatively few studies that focus on determining predicted injury risk from HBMs based on observed postmortem human subjects (PMHS) injury data. Additionally, HBMs provide an opportunity to construct risk curves using measures that are difficult or impossible to obtain experimentally. The Global Human Body Models Consortium (GHBMC) M50-O v 6.0 lower extremity was simulated in 181 different loading conditions based on previous PMHS tests in the underbody blast (UBB) environment and 43 different biomechanical metrics were output. The Brier Metric Score were used to determine the most appropriate metric for injury risk curve development. Using survival analysis, three different injury risk curves (IRC) were developed: "any injury," "calcaneus injury," and "tibia injury." For each injury risk curve, the top three metrics selected using the Brier Metric Score were tested for significant covariates including boot use and posture. The best performing metric for the "any injury," "calcaneus injury" and "tibia injury" cases were calcaneus strain, calcaneus force, and lower tibia force, respectively. For the six different injury risk curves where covariates were considered, the presence of the boot was found to be a significant covariate reducing injury risk in five out of six cases. Posture was significant for only one curve. The injury risk curves developed from this study can serve as a baseline for model injury prediction, personal protective equipment (PPE) evaluation, and can aid in larger scale testing and experimental protocols.
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Affiliation(s)
- Zachary S Hostetler
- Department of Biomedical Engineering, Wake Forest School of Medicine, Winston-Salem, NC 27101
| | - F Scott Gayzik
- Department of Biomedical Engineering, Wake Forest School of Medicine, Winston-Salem, NC 27101
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Lindgren N, Yuan Q, Pipkorn B, Kleiven S, Li X. Development of personalizable female and male pedestrian SAFER human body models. TRAFFIC INJURY PREVENTION 2024; 25:182-193. [PMID: 38095596 DOI: 10.1080/15389588.2023.2281280] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Accepted: 11/05/2023] [Indexed: 01/03/2024]
Abstract
OBJECTIVES Vulnerable road users are globally overrepresented as victims of road traffic injuries. Developing biofidelic male and female pedestrian human body models (HBMs) that represent diverse anthropometries is essential to enhance road safety and propose intervention strategies. METHODS In this study, 50th percentile male and female pedestrians of the SAFER HBM were developed via a newly developed image registration-based mesh morphing framework. The performance of the HBMs was evaluated by means of a set of cadaver experiments, involving subjects struck laterally by a generic sedan buck. RESULTS In simulated whole-body pedestrian collisions, the personalized HBMs effectively replicate trajectories of the head and lower body regions, as well as head kinematics, in lateral impacts. The results also demonstrate the personalization framework's capacity to generate personalized HBMs with reliable mesh quality, ensuring robust simulations. CONCLUSIONS The presented pedestrian HBMs and personalization framework provide robust means to reconstruct and evaluate head impacts in pedestrian-to-vehicle collisions thoroughly and accurately.
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Affiliation(s)
- Natalia Lindgren
- Division of Neuronic Engineering, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Qiantailang Yuan
- Division of Neuronic Engineering, KTH Royal Institute of Technology, Stockholm, Sweden
| | | | - Svein Kleiven
- Division of Neuronic Engineering, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Xiaogai Li
- Division of Neuronic Engineering, KTH Royal Institute of Technology, Stockholm, Sweden
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Devane K, Hsu FC, Koya B, Davis M, Weaver AA, Scott Gayzik F, Guleyupoglu B. Assessment of finite element human body and ATD models in estimating injury risk in far-side impacts using field-based injury risk. ACCIDENT; ANALYSIS AND PREVENTION 2023; 192:107274. [PMID: 37659277 DOI: 10.1016/j.aap.2023.107274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 08/11/2023] [Accepted: 08/26/2023] [Indexed: 09/04/2023]
Abstract
The objective of this study was to assess the ability of finite element human body models (FEHBMs) and Anthropometric Test Device (ATD) models to estimate occupant injury risk by comparing it with field-based injury risk in far-side impacts. The study used the Global Human Body Models Consortium midsize male (M50-OS+B) and small female (F05-OS+B) simplified occupant models with a modular detailed brain, and the ES-2Re and SID-IIs ATD models in the simulated far-side crashes. A design of experiments (DOE) with a total of 252 simulations was conducted by varying lateral ΔV (10-50kph; 5kph increments), the principal direction of force (PDOF 50°, 60°, 65°, 70°, 75°, 80°, 90°), and occupant models. Models were gravity-settled and belted into a simplified vehicle model (SVM) modified for far-side impact simulations. Acceleration pulses and vehicle intrusion profiles used for the DOE were generated by impacting a 2012 Camry vehicle model with a mobile deformable barrier model across the 7 PDOFs and 9 lateral ΔV's in the DOE for a total of 63 additional simulations. Injury risks were estimated for the head, chest, lower extremity, pelvis (AIS 2+; AIS 3+), and abdomen (AIS 3+) using logistic regression models. Combined AIS 3+ injury risk for each occupant was calculated using AIS 3+ injury risk estimations for the head, chest, abdomen, and lower extremities. The injury risk calculated using computational models was compared with field-based injury risk derived from NASS-CDS by calculating their correlation coefficient. The field-based injury risk was calculated using risk curves that were created based on real-world crash data in a previous study (Hostetler et al., 2020). Occupant age (40 years), seatbelt use (belted occupant), collision deformation classification, lateral ΔV, and PDOF of the crash event were used in these curves to estimate field injury risk. Large differences in the kinematics were observed between HBM and ATD models. ATD models tended to overestimate risk in almost every case whereas HBMs yielded better risk estimates overall. Chest and lower extremity risks were the least correlated with field injury risk estimates. The overall risk of AIS 3+ injury risk was the strongest comparison to the field data-based risk curves. The HBMs were still not able to capture all the variance but future studies can be carried out that are focused on investigating their shortfalls and improving them to estimate injury risk closer to field injury risk in far-side crashes.
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Affiliation(s)
- Karan Devane
- Biomedical Engineering, Wake Forest University School of Medicine, Winston-Salem, NC, USA.
| | - Fang-Chi Hsu
- Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Bharath Koya
- Biomedical Engineering, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | | | - Ashley A Weaver
- Biomedical Engineering, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - F Scott Gayzik
- Biomedical Engineering, Wake Forest University School of Medicine, Winston-Salem, NC, USA
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Grindle D, Balubaid A, Untaroiu C. Investigation of traffic accidents involving seated pedestrians using a finite element simulation-based approach. Comput Methods Biomech Biomed Engin 2023; 26:484-497. [PMID: 35507427 DOI: 10.1080/10255842.2022.2068349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
Pedestrians who use wheelchairs (seated pedestrians) report 36% - 75% higher mortality rates than standing pedestrians in car-to-pedestrian collisions but the cause of this mortality is unknown. This is the first study to investigate the cause of seated pedestrian mortality in vehicle impacts using finite element simulations. In this study a manual wheelchair model was developed using geometry taken from publicly available CAD data, and was tested to meet ISO standards. The GHBMC 50th percentile male simplified occupant model was used as the seated pedestrian and the EuroNCAP family car and sports utility vehicle models were used as the impacting vehicles. The seated pedestrian was impacted by the two vehicles at three different locations on the vehicle and at 30 and 40 km/h. In 75% of the impacts the pedestrian was ejected from the wheelchair. In the rest of the impacts, the pedestrian and wheelchair were pinned to the vehicle and the pedestrian was not ejected. The underlying causes of seated pedestrian mortality in these impacts were head and brain injury. Life-threatening head injury risks (0.0% - 100%) were caused by the ground-pedestrian contact, and life-threatening brain injury risks (0.0 - 97.9%) were caused by the initial vehicle-wheelchair contact and ground-pedestrian contact. Thoracic and abdominal compression reported no risks of life-threatening injuries, but may do so in faster impacts or with different wheelchair designs. Protective equipment such as the wheelchair seatbelt or personal airbag may be useful in reducing injury risks but future research is required to investigate their efficacy.
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Affiliation(s)
- Daniel Grindle
- Department of Biomedical Engineering and Mechanics, Virginia Tech, Blacksburg, Virginia, USA
| | - Ahmed Balubaid
- Department of Biomedical Engineering and Mechanics, Virginia Tech, Blacksburg, Virginia, USA
| | - Costin Untaroiu
- Department of Biomedical Engineering and Mechanics, Virginia Tech, Blacksburg, Virginia, USA
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Grindle D, Untaroiu C. Effect of Tissue Erosion Modeling Techniques on Pedestrian Impact Kinematics. STAPP CAR CRASH JOURNAL 2022; 66:207-216. [PMID: 37733826 DOI: 10.4271/2022-22-0007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/23/2023]
Abstract
The pedestrian is one of the most vulnerable road users and has experienced increased numbers of injuries and deaths caused by car-to-pedestrian collisions over the last decade. To curb this trend, finite element models of pedestrians have been developed to investigate pedestrian protection in vehicle impact simulations. While useful, modeling practices vary across research groups, especially when applying knee/ankle ligament and bone failure. To help better standardize modeling practices this study explored the effect of knee ligament and bone element elimination on pedestrian impact outcomes. A male 50th percentile model was impacted by three European generic vehicles at 30, 40, and 50 km/h. The pedestrian model was set to three element elimination settings: the "Off-model" didn't allow any element erosion, the "Lig-model" allowed lower-extremity ligament erosion, and the "All-model" allowed lower-extremity ligament and bone erosion. Failure toggling had a significant effect on impact outcomes (0 < p ≤ 0.03). The head impact time response was typically the smallest for the "Off-model" while the wrap around distance response was always largest for the All-model. Moderate differences in maximum vehicle-pedestrian contact forces across elimination techniques were reported in this study (0.1 - 1.7 kN). Future work will examine additional failure modelling approaches, model anthropometries and vehicles to expand this investigation.
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Affiliation(s)
- Daniel Grindle
- Department of Biomedical Engineering and Mechanics (BEAM), Center for Injury Biomechanics, Virginia Tech
| | - Costin Untaroiu
- Department of Biomedical Engineering and Mechanics (BEAM), Center for Injury Biomechanics, Virginia Tech
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Design and Scaling of Exoskeleton Power Units Considering Load Cycles of Humans. ROBOTICS 2022. [DOI: 10.3390/robotics11050107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
Exoskeletons are powerful tools for aiding humans with pathological conditions, in dangerous environments or in manually exhausting tasks. Typically, they are designed for specific maximum scenarios without taking into account the diversity of tasks and the individuality of the user. To address this discrepancy, a framework was developed for personalizing an exoskeleton by scaling the components, especially the electrical machine, based on different simulated human muscle forces. The main idea was to scale a numerical arm model based on body mass and height to predict different movements representing both manual labor and daily activities. The predicted torques necessary to produce these movements were then used to generate a load/performance cycle for the power unit design. Considering these torques, main operation points of this load cycle were defined and a reference power unit was scaled and optimized. Therefore, a scalability model for an electrical machine is introduced. This individual adaptation and scaling of the power unit for different users leads to a better performance and a lighter design.
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Costa C, Aira J, Koya B, Decker W, Sink J, Withers S, Beal R, Schieffer S, Gayzik S, Stitzel J, Weaver A. Finite element reconstruction of a vehicle-to-pedestrian impact. TRAFFIC INJURY PREVENTION 2020; 21:S145-S147. [PMID: 33147058 DOI: 10.1080/15389588.2020.1829911] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
OBJECTIVE This study aims to reconstruct a real-world Crash Injury Research and Engineering Network vehicle-to-pedestrian impact to supplement the determination of pedestrian kinematics and injury causation. METHODS A case involving a 46-year-old male pedestrian with a height of 163 cm and mass of 100 kg that was impacted by a 2019 Dodge Charger Pursuit police cruiser at an approximate velocity of 20.1 m/s was reconstructed. The case vehicle was represented by a rigid shell of a 2019 Dodge Charger vehicle exterior from an open-source database. The case pedestrian was represented by the Global Human Body Models Consortium (GHBMC) 50th percentile male simplified pedestrian human body model. The GHBMC model was isometrically scaled to a height of 163 cm and the external layer of flesh was morphed to a male reference geometry with the same age, height, and body mass index as the case pedestrian. The approximate location and position of the pedestrian at the time of impact was determined from case vehicle dashboard camera images and the pedestrian model was adjusted accordingly. RESULTS Reconstruction kinematics aligned with proposed CIREN case kinematics. The GHBMC model predicted fractures of the left inferior ischiopubic ramus, superior pubic ramus, ilium, sacral ala, acetabulum, and right ilium. CONCLUSIONS Finite element reconstructions of real-world pedestrian impacts are useful for analyzing pedestrian kinematics and provide an effective tool for improving pedestrian impact injury analyses.
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Affiliation(s)
- Casey Costa
- Department of Biomedical Engineering, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Jazmine Aira
- Department of Biomedical Engineering, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Bharath Koya
- Department of Biomedical Engineering, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - William Decker
- Department of Biomedical Engineering, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Joel Sink
- Department of Biomedical Engineering, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Shanna Withers
- Department of Biomedical Engineering, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Rukiya Beal
- Department of Biomedical Engineering, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Sydney Schieffer
- Department of Biomedical Engineering, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Scott Gayzik
- Department of Biomedical Engineering, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Joel Stitzel
- Department of Biomedical Engineering, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Ashley Weaver
- Department of Biomedical Engineering, Wake Forest School of Medicine, Winston-Salem, North Carolina
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