The purpose of this study was to analyze variables present in selected motorcycle crashes involving helmeted riders to find the best injury predictors. The helmets used in this study were collected from motorcycle crashes in Thailand. Pertinent data were collected, a conventional helmet impact drop test apparatus was used to quantify the head impact forces, and stepwise multiple regression analyses were performed. The results indicate that the geometry of the object impacting the head and Gadd Severity Index (GSI) were the best predictors for Maximum Abbreviated Injury Score (MAIS) (R-squared = .875), while geometry of the object, liner thickness and impact energy were the best predictors for Injury Severity Score (ISS) (R-squared = .911).
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