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The analysis and research of accidents aimed at improving the safety of vehicles and infrastructures are typically based on the retrospective investigation of data that are collected in in-depth accident databases. In particular, kinematic data related to accidents (impact velocity, velocity change of the vehicles, etc.) make possible the identification of correlations between impact severity and injury risk (IR), as well as assessing the effectiveness of vehicle protection systems. The necessary condition to conduct suitable and significant analyses is to utilise data which are correct and representative of national statistics, i.e., congruent with physical laws governing the accident phenomena. Whereas representativeness can generally be retrospectively verified, the checks on kinematic data coherence during codification are rarely performed. The present work describes a procedure to verify the internal coherence of kinematic data collected in in-depth accident databases. The introduced checks allow the identification of parameters, which are not internally coherent because the accident reconstruction model employed is inappropriate or improperly used. These checks pertain to physical laws on which road accident reconstruction is based, i.e., momentum conservation, compatibility of velocity triangles, and energy conservation. Moreover, they can be modified and expanded to consider other parameters, making the methodology virtually applicable to any database. In the case of vehicle-to-vehicle collisions, the application of the procedure to detect incongruent data inside two real databases demonstrates how their number is often not negligible. Furthermore, consequences can be substantial for both direct and secondary analysis, i.e., determining IR curves (for example, logistic regression on input data) and identifying IR associated to an accident. Accordingly, the application of checks is particularly recommended during both analysis and collection phases to confirm the congruence of collected data; consequently, the quality of investigation is enhanced.
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http://dx.doi.org/10.1016/j.aap.2018.12.004 | DOI Listing |
J Biomech
March 2025
Simulation and Movement Analysis Lab (SIMMA Lab), Department of Mechanical Engineering, Universitat Politècnica de Catalunya, Barcelona, Catalonia, Spain. Electronic address:
Dynamic variables contribute to understand the mechanics of pedalling and can assist with injury prevention. Measuring pedal forces and joint moments and powers has a high cost, which can be mitigated by using trained artificial neural networks (ANN) to predict forces from kinematics. Thus, this study aimed at training and validating recurrent ANN to predict 3D pedal forces, lower limb joint moments and powers from lower limb kinematics.
View Article and Find Full Text PDFSci Rep
March 2025
Faculty of Health and Life Sciences, University of Exeter, Exeter, Devon, EX2 4TA, UK.
Jumping on vibrating platforms is described not only by the frequency of jumping (FoJ) but also by the timing of key events in a cycle of jumping relative to vibrations. This study aimed to capture timing and efficiency-related adaptations during jumping on vertically vibrating platforms. Whole body kinematic and kinetic data were collected as ten participants jumped on a sinusoidally vibrating platform of 2.
View Article and Find Full Text PDFJ Am Med Dir Assoc
March 2025
Department of Biomedical Engineering, Virginia Tech, Blacksburg, VA, USA.
Objectives: To quantify real-world impact conditions of falls, which cause 50% to 90% of older adult traumatic brain injuries, and reconstruct them using dummy headforms to analyze kinematics and injury outcomes.
Design: Mixed-methods: Observational and experimental.
Setting And Participants: An open-access dataset of 118 videos of head impacts at long-term care facilities was used.
Sci Rep
March 2025
Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, 98124, Messina, Italy.
In the past decade, immersive virtual reality (VR) has garnered significant interest due to its capacity to ability a strong sense of presence and allow users to act in virtual environments. In particular, VR has been increasingly used in clinical settings to present scenarios for motor rehabilitation purposes. Existing research efforts mostly focus on investigating the clinical effectiveness of different routines.
View Article and Find Full Text PDFJ Arthroplasty
March 2025
Department of Orthopedic Surgery, NYU Langone Health, NYU Langone Orthopedic Hospital, 301 E 17th St, New York, NY, 10003.
Background: A frequently stated goal of an artificial knee arthroplasties is to achieve normal kinematics. However, this is not easily defined based on variations in motions previously measured for a range of activities. For activities such as crouching up and down, a fan pattern has been measured, where the lateral femoral contact displaces progressively posteriorly with flexion, and the medial contact remains almost constant.
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