Application of Wireless Network Multisensor Fusion Technology in Sports Training.


Journal

Computational intelligence and neuroscience
ISSN: 1687-5273
Titre abrégé: Comput Intell Neurosci
Pays: United States
ID NLM: 101279357

Informations de publication

Date de publication:
2022
Historique:
received: 01 04 2022
revised: 30 04 2022
accepted: 21 05 2022
entrez: 13 6 2022
pubmed: 14 6 2022
medline: 15 6 2022
Statut: epublish

Résumé

Fencing is an advantageous event for a country to participate in the Asian Games. The discussion and research on the means and methods of special fencing ability training are of great significance to the further development of fencing in the country. Based on the multisensor information fusion technology, this paper develops a special fencing training system with digital monitoring and intelligent decision-making. The multisensor information fusion technology scheme, which is reported in this paper, is used to perform decision-level fusion based on fuzzy inference technology whereas Kalman filter is used to optimize the original information. On the basis of the overall structure, mechanical mechanism, and performance analysis, the mechanical prototype of the fencing special ability training system was developed whereas design, processing, and debugging of the prototype were completed. Combined with the mechanical prototype design of various index parameter display structures based on multisensor information fusion technology, the digital processing of the fencing special ability training system is realized. The force, speed, position, and other characteristic quantities in the fencing special training system are collected by the pressure and rotational speed sensors respectively whereas USB communication technology is used for data transmission. On the basis of in-depth analysis of the characteristics of the special training system for fencing, an abstract system of pedaling power based on the center of gravity and trend models is designed where the Kalman filter is reserved for the special application fields. Moreover, the core role of Kalman filter is carried out when original data information is needed to be obtained. By constructing a force distribution pressure center trajectory measurement model, a training load and training parameter measurement model, and a training level evaluation model, the data-level raw information is specially processed to generate more training parameters that meet specific characteristics, making the multisensor information fusion technology more efficient. It is well integrated into the fencing special ability training system. By applying fuzzy reasoning technology, the special training parameters and the relationship between these parameters are transformed into fuzzy sets and fuzzy rules, and the perceptual knowledge of sports training experience is transformed into fuzzy rules. With this decision-level data fusion method, the fencing special training system has certain intelligent functions.

Identifiants

pubmed: 35694566
doi: 10.1155/2022/9836697
pmc: PMC9187449
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

9836697

Informations de copyright

Copyright © 2022 Wenjun Tang.

Déclaration de conflit d'intérêts

The authors declare that they have no conflicts of interest regarding the publication of this paper.

Références

Front Neurosci. 2020 Aug 05;14:637
pubmed: 32903824
Comput Intell Neurosci. 2022 Mar 7;2022:7624578
pubmed: 35295278

Auteurs

Wenjun Tang (W)

PE Department of Tongling University, Tongling 244061, Anhui 244061, China.

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