Evidence map›Paper›PMID 34608414›Full record

ArticleJournal of healthcare engineering2021

Design of the Exercise Load Data Monitoring System for Exercise Training Based on the Neural Network.

Panlong Qin, Wei Feng

RetractedAbstract readRetracted Publication
In one paragraph

Article in Journal of healthcare engineering, 2021. 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 It has been retracted, and should not be counted.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.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Panlong QinDepartment of Physical Education, Hebei Academy of Fine Arts, Hebei,050700, China.ORCID 0000-0001-8859-5683
Wei FengDepartment of Physical Education, Hebei Academy of Fine Arts, Hebei,050700, China.ORCID 0000-0002-1317-9500

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In order to monitor the sports load data of athletes in sports training, this paper studies the methods and systems of sports load monitoring and fatigue warning based on neural network technology. In this paper, the neural network parallel optimization algorithm based on big data is used to accurately estimate the motion load and intensity according to the determined motion mode and acceleration data, so as to realize the real-time monitoring of the exercise training. The results show that the value of

Indexed as

ExerciseSportsBayes TheoremHumansMonitoring, PhysiologicNeural Networks, Computer

Identifiers

PMID34608414
PMCPMC8487358

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.