Comparison of Six Data Cleaning Methods for Determining Repetitive Head Impact Exposure in Youth Tackle Football

Samantha DeAngelo; Adam Culiver; Enora Le Flao; Nick Shoaf; Durshil Doshi; Ryan Tracy; Nii-Ayi Aryeetey; Anna Quatrale; Carly Smith; Jianing Ma; Jeff Pan; Jingzhen Yang; Sean C Rose; James Onate; Nathan Edwards; Zeynep Saygin; Jaclyn B Caccese

doi:10.1007/s10439-026-03991-4

Comparison of Six Data Cleaning Methods for Determining Repetitive Head Impact Exposure in Youth Tackle Football

Ann Biomed Eng. 2026 Jan 23. doi: 10.1007/s10439-026-03991-4. Online ahead of print.

Authors

Samantha DeAngelo^{1

2}, Adam Culiver^{3

4}, Enora Le Flao^{1

2

5}, Nick Shoaf¹, Durshil Doshi¹, Ryan Tracy¹, Nii-Ayi Aryeetey⁶, Anna Quatrale⁶, Carly Smith^{1

2}, Jianing Ma⁷, Jeff Pan⁷, Jingzhen Yang^{2

8}, Sean C Rose^{2

9}, James Onate^{1

2

5}, Nathan Edwards⁵, Zeynep Saygin^{2

6}, Jaclyn B Caccese^{10

11

12}

Affiliations

¹ School of Health and Rehabilitation Sciences, College of Medicine, The Ohio State University Wexner Medical Center, Columbus, OH, USA.
² Chronic Brain Injury Program, The Ohio State University, Columbus, OH, USA.
³ Department of Physical Therapy, School of Health and Human Sciences, Indiana University Indianapolis, Indianapolis, IN, USA.
⁴ Academic Health Center, Indiana University Health, Indianapolis, IN, USA.
⁵ Human Performance Collaborative, The Ohio State University, Columbus, OH, USA.
⁶ Department of Psychology, College of Arts and Sciences, The Ohio State University, Columbus, OH, USA.
⁷ Center for Biostatistics, The Ohio State University, Columbus, OH, USA.
⁸ Center for Injury Research and Policy, Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, OH, USA.
⁹ Neurology, Nationwide Children's Hospital, Columbus, OH, USA.
¹⁰ School of Health and Rehabilitation Sciences, College of Medicine, The Ohio State University Wexner Medical Center, Columbus, OH, USA. jaclyn.caccese@osumc.edu.
¹¹ Chronic Brain Injury Program, The Ohio State University, Columbus, OH, USA. jaclyn.caccese@osumc.edu.
¹² , 246C Atwell Hall, 453 W 10th Ave, Columbus, OH, 43210, USA. jaclyn.caccese@osumc.edu.

PMID: 41575729
DOI: 10.1007/s10439-026-03991-4

Abstract

Purpose: Instrumented mouthguards (iMGs) are commonly used to quantify head acceleration event (HAE) exposure, but accurate interpretation requires rigorous data cleaning methods. This study compared six data cleaning methods for determining HAE rates and magnitudes, as well as cleaning method validity compared to the 5^th method video verification in youth tackle football.

Methods: Fifty athletes (ages 8-12) wore Impact Monitoring Mouthguards during games across one season. Six data cleaning methods were applied to HAEs, including uncleaned data, time-windowing, proprietary classification algorithms, video verification, and combinations thereof. Impact rate, peak linear acceleration (PLA), and peak rotational velocity (PRV) were compared across methods using rate ratios, and intra-class correlation coefficients (ICCs), and non-parametric analyses.

Results: Data cleaning methods significantly influenced HAE rate but had minimal effect on magnitude. The uncleaned dataset produced the highest HAE rate (67.75 per athlete exposure), while the most stringent method (i.e., time-windowed, proprietary algorithm-classified, video-verified data) yielded the lowest (0.70 per athlete exposure). Although the time-windowed, proprietary algorithm-classified data demonstrated high specificity (0.96), it demonstrated low sensitivity (0.37) and positive predictive value (0.39) when compared to video-verified data. Differences in PLA across methods were not significant; only one significant difference in PRV was observed.

Conclusions: These findings highlight the impact of data cleaning on HAE quantification in youth tackle football. Although video verification remains best practice, it is resource intensive. Time-windowed, algorithm-classified data may serve as an efficient proxy in similar cohorts, though researchers should recognize its limitations. Findings support the need for standardized data cleaning methods and transparent reporting to ensure accurate and comparable HAE exposure estimates.

Keywords: Concussion; Head acceleration events; Sensor validation; Video verification.

Grants and funding

R01HD110401/National Institute of Child Health and Human Development