Optimization of Human Motion Recognition Information Processing System Based on GA-BP Neural Network Algorithm

At present, there are some problems in the process of human motion recognition, such as poor timeliness and low fault tolerance rate. How to effectively identify the motion process accurately has become a hot spot in the optimization system. In the existing research studies, the recognition accuracy...

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Autor principal:	Shuwei Zhao
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Computer applications to medicine. Medical informatics R858-859.7 Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571
Acceso en línea:	https://doaj.org/article/1593405b194b4af9bcaf6d46518bb8f3
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id	oai:doaj.org-article:1593405b194b4af9bcaf6d46518bb8f3
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spelling	oai:doaj.org-article:1593405b194b4af9bcaf6d46518bb8f32021-11-08T02:37:29ZOptimization of Human Motion Recognition Information Processing System Based on GA-BP Neural Network Algorithm1687-527310.1155/2021/1110503https://doaj.org/article/1593405b194b4af9bcaf6d46518bb8f32021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/1110503https://doaj.org/toc/1687-5273At present, there are some problems in the process of human motion recognition, such as poor timeliness and low fault tolerance rate. How to effectively identify the motion process accurately has become a hot spot in the optimization system. In the existing research studies, the recognition accuracy is not very good and the response time is long. To end this issue, the paper proposed an information processing system and optimization method of human motion recognition based on the GA-BP neural network algorithm. Firstly, a human motion recognition system based on dynamic capture recognition technology is designed, which realizes the recognition of motion information from common postures such as action span, speed change, motion trajectory, and other aspects in the process of human motion. Secondly, the proposed algorithm is used to comprehensively analyse and evaluate the motion state. Finally, experiments are designed to verify and analyse the results. Compared to some baseline methods in human motion recognition information systems, the system in this paper based on the GA-BP neural network algorithm has the advantages of higher data accuracy and response speed, which can quickly and accurately identify the muscle group change in the process of human motion, and it can also provide customized motion suggestions based on the results.Shuwei ZhaoHindawi LimitedarticleComputer applications to medicine. Medical informaticsR858-859.7Neurosciences. Biological psychiatry. NeuropsychiatryRC321-571ENComputational Intelligence and Neuroscience, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Computer applications to medicine. Medical informatics R858-859.7 Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571
spellingShingle	Computer applications to medicine. Medical informatics R858-859.7 Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571 Shuwei Zhao Optimization of Human Motion Recognition Information Processing System Based on GA-BP Neural Network Algorithm
description	At present, there are some problems in the process of human motion recognition, such as poor timeliness and low fault tolerance rate. How to effectively identify the motion process accurately has become a hot spot in the optimization system. In the existing research studies, the recognition accuracy is not very good and the response time is long. To end this issue, the paper proposed an information processing system and optimization method of human motion recognition based on the GA-BP neural network algorithm. Firstly, a human motion recognition system based on dynamic capture recognition technology is designed, which realizes the recognition of motion information from common postures such as action span, speed change, motion trajectory, and other aspects in the process of human motion. Secondly, the proposed algorithm is used to comprehensively analyse and evaluate the motion state. Finally, experiments are designed to verify and analyse the results. Compared to some baseline methods in human motion recognition information systems, the system in this paper based on the GA-BP neural network algorithm has the advantages of higher data accuracy and response speed, which can quickly and accurately identify the muscle group change in the process of human motion, and it can also provide customized motion suggestions based on the results.
format	article
author	Shuwei Zhao
author_facet	Shuwei Zhao
author_sort	Shuwei Zhao
title	Optimization of Human Motion Recognition Information Processing System Based on GA-BP Neural Network Algorithm
title_short	Optimization of Human Motion Recognition Information Processing System Based on GA-BP Neural Network Algorithm
title_full	Optimization of Human Motion Recognition Information Processing System Based on GA-BP Neural Network Algorithm
title_fullStr	Optimization of Human Motion Recognition Information Processing System Based on GA-BP Neural Network Algorithm
title_full_unstemmed	Optimization of Human Motion Recognition Information Processing System Based on GA-BP Neural Network Algorithm
title_sort	optimization of human motion recognition information processing system based on ga-bp neural network algorithm
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/1593405b194b4af9bcaf6d46518bb8f3
work_keys_str_mv	AT shuweizhao optimizationofhumanmotionrecognitioninformationprocessingsystembasedongabpneuralnetworkalgorithm
_version_	1718442974947311616

Optimization of Human Motion Recognition Information Processing System Based on GA-BP Neural Network Algorithm

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