Year: 2025
Type: article
Abstract: The growing popularity of mountain biking is associated with a rapid rise in injuries. Understanding the main crash scenarios is essential for improving preventive and protective measures. This study aimed to describe crash scenarios, fall kinematics, and injury mechanisms using a large video database of traumatic mountain bike crashes. A qualitative analysis was performed on 534 traumatic crash videos from a mountain biking social network. Data recorded included rider information, terrain description, cause of crashes, crash scenario, rider kinematics upon ground impact and injury. When possible, the rider's speed before the crash was measured. Among the 534 videos analysed, six specific crash scenarios were identified: forward over-the-bars (55.2%), forward on-the-bars (9.2%), sideways ejection (12.2%), sideways sliding (10.9%), collision (9.4%) and backward fall (3.2%). In the main scenario, 'over-the-bars', riders are thrown over the handlebars due to sudden deceleration, often occurring on moderate descents (53.2%) and following poor jump landings (64.4%) at speeds exceeding 30 km/h (75.3%). Tumbles were the most common impact type on the ground (64.7%), with shoulder girdle (39.7%) and upper limbs (35.6%) injuries predominating. An association between impact type on the ground and injury location was found. The mean recorded speed before the crash was 33.7 km/h, which is higher than previously reported MTB speeds. This study is the first to systematically analyse MTB accident videos, providing crucial insights to better understand full crash kinematics and help design effective protective equipment, optimize trail design, and enhance prevention campaigns on MTB slopes.
DOI: 10.1002/ejsc.12327
Authors: S. Bonte, C. Hartweg, A. Thouzé, E. Marcaggi, M. Dupuis, N. Graillon, P.‐J. Arnoux, L. Thollon, N. Bailly
Language: English
Subfield: Orthopedics and Sports Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,680
Award: G8072241544
OpenAlex ID: W4411469116
