Citation

Sobotta VMG, Flormann M, Henze R, Deserno TM. Stud. Health Technol. Inform. 2023; 302: 118-122.

Copyright

(Copyright © 2023, IOS Press)

DOI

10.3233/SHTI230076

PMID

37203621

Abstract

For people involved in road traffic accidents, the time necessary to respond is crucial and it is hard to discern, which persons in which cars most urgently need help. To plan the rescue operation before arriving at the scene, digital information regarding the severity of the accident is vital. Our framework aims to transmit available data from the in-car sensors and to simulate the forces enacted on occupants using injury models. To avoid data security and privacy issues, we install low-cost hardware in the car for aggregation and preprocessing. Our framework can be retrofitted to existing cars and therefore could extend the benefits to a wide range of people.

Language: en

Keywords

Framework; Injury prediction; Traffic accident simulation