Evidence map›Paper›PMID 36172318›Full record

ArticleComputational intelligence and neuroscience2022

Research on Movement Analysis and Guidance in Dance Learning Based on Data Mining.

Guangle Yin, Jing Liu

Open access · hybridAbstract 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
1.0field-weighted citation impact, top 23% 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

0 citing papers in PubMed, 5 citations in OpenAlex.

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 at 1 institution in 1 country.

Guangle YinMusic Academy, Henan Polytechnic, Zhengzhou 450046, China.ORCID https://orcid.org/0000-0001-7280-0785
Jing LiuMusic Academy, Henan Polytechnic, Zhengzhou 450046, China.
Henan Polytechnic University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In dance, we must understand the essential meaning of dance movements from the inside and express them on the basis of dance. Therefore, in the process of developing new dance teaching methods, it is necessary to improve the basic education of dance students, so that they can express the emotions conveyed by dance through body language and movements, and improve dance expression ability. In this context, we made the research and reached the following conclusions: (1) the number of frames of different dance types is also different, and the number of frames to be learned is also increasing. The dance with the highest number of frames is Latin2, which has 3635 frames, and the dance with the highest number of frames that need to be learned is also Latin2, which requires 2519 frames to learn. (2) The data mining method is still the highest among the three methods, and the accuracy of the complete teaching method is 82%, which is the lowest among the three methods, and the accuracy of the decentralized teaching method is 87%. No matter in the test set or the mixed test set, the curve values of deep mining are very stable. First of all, human movements emphasize that in dance, the essential meaning of dance movements needs to be understood from the inside and expressed through the foundation of dance. Therefore, when developing new dance teaching methods, it is necessary to strengthen the basic dance training of students so that students can express the emotions conveyed by dance through body language and movements and improve their dance expression ability. We conduct research in this ecological environment. Different types of dance learning process using different frames, different types of dance in the algorithm transport have different recognition methods, using better and different algorithms can achieve the best performance. Both groups in the Hip Hop dance had a shorter average learning time than both groups in the Latin dance.

Indexed as

LearningMovementData MiningHumansStudents

Identifiers

PMID36172318
PMCPMC9512616
OpenAlexW4296389478

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.