Evidence map›Paper›PMID 29920559›Full record

ArticlePloS one2018

Comparison of video-based and sensor-based head impact exposure.

Calvin Kuo, Lyndia Wu, Jesus Loza, Daniel Senif, Scott C Anderson, David B Camarillo

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed, 4 pooled it
6.3field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

43 citing papers in PubMed, 4 syntheses or guidelines pooled it, 73 citations in OpenAlex.

  1. Pooled it
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  3. A Systematic Review of Head Impacts and Acceleration Associated with Soccer.International journal of environmental research and public health · 2022
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  12. Quantitative video analysis of head acceleration events: a review.Frontiers in bioengineering and biotechnology · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Calvin KuoDepartment of Mechanical Engineering, Stanford University, Stanford CA, United States of America.ORCID 0000-0001-8401-9136
Lyndia WuDepartment of Bioengineering, Stanford University, Stanford CA, United States of America.
Jesus LozaDepartment of Mechanical Engineering, Stanford University, Stanford CA, United States of America.
Daniel SenifStanford Sports Medicine, Stanford University, Stanford CA, United States of America.
Scott C AndersonStanford Sports Medicine, Stanford University, Stanford CA, United States of America.
David B CamarilloDepartment of Mechanical Engineering, Stanford University, Stanford CA, United States of America.
Stanford University · USStanford Medicine · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Previous research has sought to quantify head impact exposure using wearable kinematic sensors. However, many sensors suffer from poor accuracy in estimating impact kinematics and count, motivating the need for additional independent impact exposure quantification for comparison. Here, we equipped seven collegiate American football players with instrumented mouthguards, and video recorded practices and games to compare video-based and sensor-based exposure rates and impact location distributions. Over 50 player-hours, we identified 271 helmet contact periods in video, while the instrumented mouthguard sensor recorded 2,032 discrete head impacts. Matching video and mouthguard real-time stamps yielded 193 video-identified helmet contact periods and 217 sensor-recorded impacts. To compare impact locations, we binned matched impacts into frontal, rear, side, oblique, and top locations based on video observations and sensor kinematics. While both video-based and sensor-based methods found similar location distributions, our best method utilizing integrated linear and angular position only correctly predicted 81 of 217 impacts. Finally, based on the activity timeline from video assessment, we also developed a new exposure metric unique to American football quantifying number of cross-verified sensor impacts per player-play. We found significantly higher exposure during games (0.35, 95% CI: 0.29-0.42) than practices (0.20, 95% CI: 0.17-0.23) (p<0.05). In the traditional impacts per player-hour metric, we observed higher exposure during practices (4.7) than games (3.7) due to increased player activity in practices. Thus, our exposure metric accounts for variability in on-field participation. While both video-based and sensor-based exposure datasets have limitations, they can complement one another to provide more confidence in exposure statistics.

Indexed as

AccelerationAthletic InjuriesBiomechanical PhenomenaBiosensing TechniquesCraniocerebral TraumaFootballHeadHumansMotionVideo RecordingWearable Electronic Devices

Identifiers

PMID29920559
PMCPMC6007917
OpenAlexW2950789770

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.