Evidence map›Paper›PMID 35720923›Full record

ArticleComputational intelligence and neuroscience2022

Design of Cloud Storage-Oriented Sports Physical Fitness Monitoring System.

Zhou Zheng, Yang Liu

Abstract read
In one paragraph

Article in Computational intelligence and neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Zhou ZhengHulunbuir University, Institute of Physical Education, Inner Mongolia, Hulunbuir 021008, China.
Yang LiuPhysical Education Institute of Shanxi Normal University, Shanxi 710119, China.ORCID https://orcid.org/0000-0003-1821-7921

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In order to improve the accuracy and response speed of sports fitness monitoring results and make the monitoring results more comprehensive, a new cloud storage-oriented sports fitness monitoring system is designed. Based on cloud storage technology, the overall framework of the sports fitness monitoring system is established; the function of the hardware module of the monitoring system is analyzed, and distributed database is established. The ray-casting image feature scanning method was used to collect the physical condition monitoring image and generate a high-quality human body target frame to realize the physical condition monitoring. Based on the monitoring data, the fitness method recommendation method is designed according to the user's physical condition. The experimental results show that the monitoring results of the proposed system have higher accuracy, faster system response speed, and higher comprehensiveness of the monitoring results, which verifies the application value of the proposed system.

Indexed as

Cloud ComputingSportsComputersHumansPhysical Fitness

Identifiers

PMID35720923
PMCPMC9205706

What OpenQuestion holds

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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.