A proclaimed accidental fall of an infant-an experimental case reconstruction study

Mapping the knowledge of traffic collision Reconstruction: A scientometric analysis in CiteSpace, VOSviewer, and SciMAT

Traffic collisions are incidents with high fatality rate which generate billions of US dollars of loss worldwide each year. Post-collision scene reconstruction, which involves knowledge of multiple disciplines, is an important approach to restore the traffic collision and infer the cause of it. This paper uses software CiteSpace, VOSviewer, and SciMAT to conduct a visualization study of knowledge mapping on the literature of traffic collision scene reconstruction from 2001 to 2021 based on the Web of Science database. Knowledge mapping is a cutting-edge research method in scientometric, which has been widely applied in medicine and informatics. Compared with traditional literature review, knowledge mapping with visual techniques identifies hot keywords and key literature in the field more scientifically, and displays them in schematic diagrams intuitively which allows to further predict potential hotspots. A total of 803 original papers are retrieved to analyze and discuss the evolution of the field in the past 20 years, from macro to micro, in term of background information, popular themes, and knowledge structure. Results indicate the number of publications in this field is limited, and collaborations among authors and among institutions are insufficient. In the meantime, mappings imply the top three hot themes being scene reconstruction, computer technology, and injuries. The introduction of AI related technologies, such as neural networks and genetic algorithms, into collision reconstruction would be a potential research direction.

Infant skull fracture risk for low height falls

Skull fractures are common injuries in young children, typically caused by accidental falls and child abuse. The paucity of detailed biomechanical data from real-world trauma in children has hampered development of biomechanical thresholds for skull fracture in infants. The objectives of this study were to identify biomechanical metrics to predict skull fracture, determine threshold values associated with fracture, and develop skull fracture risk curves for low-height falls in infants. To achieve these objectives, we utilized an integrated approach consisting of case evaluation, anthropomorphic reconstruction, and finite element simulation. Four biomechanical candidates for predicting skull fracture were identified (first principal stress, first principal strain, shear stress, and von Mises stress) and evaluated against well-witnessed falls in infants (0–6 months). Among the predictor candidates, first principal stress and strain correlated best with the occurrence of parietal skull fracture. The principal stress and strain thresholds associated with 50 and 95% probability of parietal skull fracture were 25.229 and 36.015 MPa and 0.0464 and 0.0699, respectively. Risk curves using these predictors determined that infant falls from 0.3 m had a low probability (0–54%) to result in parietal skull fracture, particularly with carpet impact (0–1%). Head-first falls from 0.9 m had a high probability of fracture (86–100%) for concrete impact and a moderate probability (34–81%) for carpet impact. Probabilities of fracture in 0.6 m falls were dependent on impact surface. Occipital impacts from 0.9 m onto the concrete also had the potential (27–90% probability) to generate parietal skull fracture. These data represent a multi-faceted biomechanical assessment of infant skull fracture risk and can assist in the differential diagnosis for head trauma in children.

Methods for describing different results obtained from different methods in accident reconstruction

There is always more than one method can be employed to reconstruct a traffic accident and then more than one result can be obtained. How to describe these different results becomes an issue. Two solutions were given, the first is to fuse different results to one result, while the other is to rank different results according to their credibility. Methods based on the Ordered Weighted Averaging (OWA) operator and Uncertain Ordered Weighted Averaging (UOWA) operator were proposed to fuse different certain results and different interval results to one result, respectively. And methods based on the Combination Weight Arithmetic Average (CWAA) and OWA operators were proposed to rank different certain or interval results. Finally, a true vehicle-motorcycle accident was given to demonstrate these proposed methods, results showed that all methods work well in practice. If the calculation uncertainty was not considered, the fused result 64.56km/h and a ranked vector can be obtained; if the calculation uncertainty was considered, the fused result [62.13, 68.13]km/h and a ranked interval number set can be obtained. Because that all final results were obtained by employing widely used mature operators, they deserve to be trusted. The research provides more reliable choices to describe different results obtained from different methods in accident reconstruction.