Evidence map›Paper›PMID 36128701›Full record

ArticleJournal of the Royal Society, Interface2022

Numerical investigation of the rider's head injury in typical single-electric self-balancing scooter accident scenarios.

Fang Wang, Jiaxian Huang, Lin Hu, Shenghui Hu, Mingliang Wang, Jiajie Yin, Tiefang Zou, Qiqi Li

Abstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. Article
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

8 authors.

Fang WangSchool of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha, Hunan People's Republic of China.ORCID 0000-0002-7409-0841
Jiaxian HuangSchool of Mechanical and Automotive Engineering, Xiamen University of Technology, Xiamen, Fujian, People's Republic of China.
Lin HuSchool of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha, Hunan People's Republic of China.
Shenghui HuSchool of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha, Hunan People's Republic of China.
Mingliang WangSchool of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha, Hunan People's Republic of China.
Jiajie YinSchool of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha, Hunan People's Republic of China.
Tiefang ZouSchool of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha, Hunan People's Republic of China.
Qiqi LiSchool of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha, Hunan People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As the use of electric self-balancing scooters (ESSs) increases, so does the number of related traffic accidents. Because of the special control method, mechanical structure and driving posture, ESSs are prone to various single-vehicle accidents, such as collisions with fixed obstacles and falls due to mechanical failures. In various ESS accident scenarios, the rider's head injury is the most frequent injury type. In this study, several typical single-ESS accident scenarios are reconstructed via computational methods, and the risk of riders' head/brain injury is assessed in depth using various injury criteria. Results showed that two types of ESSs (solo- and two-wheeler) do not have clear differences in head kinematics and head injury risks; the head kinematics (or falling posture) and ESS accident scenario exhibit a distinct effect on the head injury responses; half of the analysed ESS riders have a 50% probability of skull fracture, a few riders have a 50% risk of abbreviated injury scale (AIS) 4+ brain injury, and none has a diffuse axonal injury; the ESS speed plays an important role in producing the head/brain injury in ESS riders, and generally, higher ESS speed generates higher level of predicted head injury parameters. These findings will provide theoretical support for preventing head injury among ESS riders and data support for developing and legislating ESSs.

Indexed as

Brain InjuriesCraniocerebral TraumaAccidents, TrafficBiomechanical PhenomenaHeadHumanscomputational biomechanics modelelectric self-balancing scooter (ESS)head/brain injurysingle-ESS accident scenario

Identifiers

PMID36128701
PMCPMC9490341

What OpenQuestion holds

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Registered trials

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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.