(D-135) Investigating the Impact of Track Roughness on Head Kinematics in Grassroots Dirt Track Racing

It is estimated that up to 1.6 to 3.8 million sport- and recreation-related concussions occur each year in the United States.[1] Current literature describing the incidence of concussion in motorsport is limited, but the evidence that exists suggests drivers experience concussions at relatively high rates, reporting an incidence of 1.7 to 17.6% at the professional level.[2] To understand the biomechanical loading experienced in motorsport environments, researchers have utilized incident data recorders (IDRs) and mouthpiece-based sensors to assess vehicle motion and head kinematics.[3,4] The grassroots level of racing involves variance in access to and use of safety equipment, oversight and rules, and track environments. Tracks vary in the type and design (e.g., dirt, clay, or paved, width and banking) and are sensitive to changes from weather and overall layout during the course of a race. These factors can affect track roughness, impacting maneuverability of the car and experience of the driver.[5] However, despite this, little investigation into the effect of the track on chassis and head motion has been performed. The objectives of this study were to develop a metric to characterize track roughness based on vehicle dynamics, assess inter-track differences, and evaluate associations between vehicle kinematics and head kinematics in a sample of grassroots drivers.

Eight drivers (n=5 male, n=3 female) were monitored throughout 63 days of racing at 27 distinct tracks. Each driver was equipped with a custom mouthpiece containing a tri-axial linear accelerometer and gyroscope.[6] Mouthpieces were reset prior to each race and configured to record linear acceleration and rotational velocity data of the head at 200 Hz in repeated and continuous ten minute and 40 second time blocks. Each vehicle was additionally equipped with an IDR that continuously recorded linear acceleration at 1000 Hz throughout all races. During each race, time-synchronized videos were collected to segment head and vehicle kinematics for each lap. A 10 Hz low pass filter was applied to raw IDR data to attenuate high frequency vibration and estimate lower frequency dynamics of the chassis. A 500 ms moving average was employed to estimate bulk motion of the vehicle. This data was integrated to obtain adjusted linear velocity, and a chassis perturbation was defined as a segment where consecutive points of the adjusted linear velocity crossed zero.[4] Peak to peak resultant linear acceleration (PLA) was calculated for each perturbation. Track roughness characteristics included the mean magnitude of PLA across all perturbations in a lap and the frequency of perturbations (i.e., perturbations per second of racing) in the lap. These parameters were compared across tracks and associated with time-aligned head perturbations.[4]

A total of 7,337 complete racing laps were segmented from all races across each track. Track roughness parameters of PLA and vehicle perturbation frequency are compared across all tracks in figures 1A and 1B, respectively. Preliminary results for all laps indicate an overall median (95^th Percentile) PLA of 6.13 g (14.49 g). The greatest magnitudes of PLA occurred at IN9, PA2, and PA5 with a range of 9.92 g – 10.68 g. Similarly, the lowest PLA values arose at VA1, SC1, and NC3 (0.36 g – 0.47 g), all paved tracks. Median frequency was compared in the anterior-posterior (A-P), medial-lateral (M-L), and inferior-superior (I-S) axes, with the greatest being in the I-S axis having a median (95^th Percentile) of 5.27 Hz (6.56 Hz). The highest median frequencies were within 6.13 Hz – 6.15 Hz and resulted from paved tracks (VA1, NC3, and NC4). The lowest frequencies were at IN5, IN9, and OH1 (4.70 Hz – 4.78 Hz). Pavement tracks had substantially lower PLA, but greater frequency. For dirt tracks specifically, the lowest PLA and highest frequencies were within 3.99 g – 5.31 g and 5.48 Hz – 5.65 Hz respectively. This finding of greater frequencies may be attributed to current methodology used to identify perturbations, with future work potentially considering other techniques for transient perturbation identification. Additionally, greater inter-track variation across dirt tracks may be correlated with a changing race environment due to racing, weather, and track conditions. Comparison of track roughness parameters to head kinematics data is currently on-going.

PLA and perturbation frequency were used as measures to assess track roughness. Differences between track types arose with paved tracks often having higher frequencies and lower magnitudes. Additionally, there was greater variation in dirt tracks in comparison to paved tracks. This suggests future research into track specific differences (e.g., length, width, and banking) and track conditions may help to inform safety measures and reduce injury risk.

This study was supported by Toyota Racing Development USA (Costa Mesa, California) and in part by the NSF REU Site (Award #1950281) in the Department of Biomedical Engineering at Wake Forest University School of Medicine.

[1] Langlois JA, J Head Trauma Rehabil. 21(5):375-8, 2006.

[2] Deakin ND, Concussion 2(3):CNC43, 2017.

[3] Miller LE et al., J Biomech Eng, 145(3), 031006, 2023.

[4] Filben TM et al., Traffic Inj Prev, 23(sup1):S38-S43, 2022.

[5] Wambold J, Transportation Research Circular, 11-24, 2009.

[6] Rich AM et al., Ann Biomed Eng, 47(10):2109-2121, 2019.