ArticleContrast media & molecular imaging2022
Application of Biomechanics Based on Intelligent Technology and Big Data in Physical Fitness Training of Athletes.
Article in Contrast media & molecular imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed, 4 citations in OpenAlex.
- Retracted: Application of Biomechanics Based on Intelligent Technology and Big Data in Physical Fitness Training of Athletes.Contrast media & molecular imaging · 2023Article
Corrections and comments
- Retraction · 2023-07-19Concerns/Issues about Data · Concerns/Issues about Referencing/Attributions · Concerns/Issues about Peer Review · Investigation by Journal/Publisher · Investigation by Third Party · Unreliable Results and/or Conclusions · · See also: https://pubpeer.com/publications/A3C10E30A3A20C7CCB6FAB41AF23DA
- Retracted
Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Physical training has a high degree of participation all over the world. With the opening of the era of national fitness, physical training has become more popular from the original specialization, and the complex training methods and contents have gradually become simplified. The development and change of physical training has also brought many problems to the professional training of athletes, such as high training intensity but poor effect, insufficient training posture, and long-term physical injury. In order to help athletes achieve better results in physical training and reduce the probability of injury, taking sprint training as an example, this article adopted the sports and body data of elite athletes through intelligent technology and big data analysis, established a human motion model from the perspective of biomechanics, and then conducted a corresponding test run experiment for athletes. The experimental results suggested that drag resistance running could improve the specific strength quality of sprinting. At the same time, when using resistance load for training, the maximum speed should not exceed 90% of the maximum speed without resistance. The average horizontal maximum velocity decreased by approximately 9% when training under a resistance load, and the best training results were obtained by training athletes within this range.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.