Design of Motion Damage Estimation Model Based on Improved Recursive Neural Network Algorithm

Zhu, Jiaju; Hu, S. Y.; Zhang, Meng

doi:10.1155/2022/2018867

Cited by 3 publications

(2 citation statements)

References 25 publications

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“…The usage of RNNs in disciplines including pattern recognition, image processing, intelligent control, signal processing optimization calculations, and others have made them large-scale nonlinear dynamic systems with feedback loops. The issue of vanishing gradients, which affects RNNs [27], makes it difficult for these networks to learn from extended data sequences. Gradients are a vital part of the RNN variable update, and as they decrease in magnitude, the learning gains from these updates diminish to zero.…”

Section: Resultsmentioning

confidence: 99%

Investigation on the Use of Virtual Reality in the Flipped Teaching of Martial Arts Taijiquan Based on Deep Learning and Big Data Analytics

HanLiang

LiNa

2022

Journal of Sensors

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Flipping classroom teaching of martial arts “Taijiquan” is a contemporary teaching method that primarily uses information technology tools to accomplish the natural fusion of information technology and education and teaching. Digital teaching materials influence the conventional classroom. The conventional teaching approach of teacher instruction and student learning is no longer satisfactory to students. Virtual reality (VR) technology and physical education integration and development have currently emerged as a new trend, but research on its application to martial arts is still in its theoretical stages and lacks concrete application countermeasures and schemes, necessitating further investigation and study. This paper intends to investigate the use of virtual reality technology in martial arts education. The architecture of virtual reality based on the deep learning algorithm is suggested. The student dataset is collected, and they are split into two groups: control and study groups. Traditional teaching is provided to the control group, and deep learning-based VR-assisted teaching is provided to the study group using the Deep Binary Hashed Convolutional Neural Network (DBH-CNN). Statistical analysis is done using Student’s t -test, logistic regression analysis, and analysis of variance (ANOVA). According to the study findings, the majority of students see virtual reality technology-assisted martial arts education favorably, and their passion for studying martial arts has greatly increased.

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Section: Resultsmentioning

confidence: 99%

Investigation on the Use of Virtual Reality in the Flipped Teaching of Martial Arts Taijiquan Based on Deep Learning and Big Data Analytics

HanLiang

LiNa

2022

Journal of Sensors

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“…Li et al [31] recommended interactive control methods and neural networks to analyze sports training strategies. As a result, the collected sports data has been fused and processed using a neural network.…”

Section: A Backgroundmentioning

confidence: 99%

Retracted: A new machine learning approach based on fuzzy data correlation for recognizing sports activities

et al. 2024

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Wearable sensors (WS) played a vital role in health assistance to improve the patient monitoring process. However, the existing data collection process faces difficulties in error corrections, rehabilitation, and training validations. Therefore, the fuzzy data analysis requires additional effort to reduce the overall problems in sports rehabilitation. The research difficulties are overcome by applying the spatial correlation with a support vector machine (SDC-SVM). The algorithm uses the hyperplane function that recognizes the sports person activities and improves overall activity recognition efficiency. The sensor data is analyzed according to the input margin, and the classification process is performed. In addition, feature correlation and input size are considered to maximize the overall classification procedure of WS data correlation using the size and margin of the input and previously stored data. In both the differentiation and classification instances, the data's spatiotemporal features are extracted and analyzed using support vectors. This proposed method can improve the accuracy of recognition, F1 score, and computing time for the varying WS inputs, classifications, and subjects.

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A new machine learning approach based on spatial fuzzy data correlation for recognizing sports activities

Xu,

Zhou,

Kausar

et al. 2024

Demonstratio Mathematica

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Wearable sensors (WS) play a vital role in health assistance to improve the patient monitoring process. However, the existing data collection process faces difficulties in error corrections, rehabilitation, and training validations. Therefore, the data analysis requires additional effort to reduce the overall problems in sports rehabilitation. The existing research difficulties are overcome by applying the proposed spatial data correlation with a support vector machine (SDC-SVM). The algorithm uses the hyperplane function that recognizes sportsperson activities and improves overall activity recognition efficiency. The sensor data are analyzed according to the input margin, and the classification process is performed. In addition, feature correlation and input size are considered to maximize the overall classification procedure of WS data correlation using the size and margin of the input and previously stored data. In both the differentiation and classification instances, the spatiotemporal features of data are extracted and analyzed using support vectors. The proposed SDC-SVM method can improve recognition accuracy, F1 score, and computing time for the varying WS inputs, classifications, and subjects.

show abstract

Design of Motion Damage Estimation Model Based on Improved Recursive Neural Network Algorithm

Cited by 3 publications

References 25 publications

Investigation on the Use of Virtual Reality in the Flipped Teaching of Martial Arts Taijiquan Based on Deep Learning and Big Data Analytics

Investigation on the Use of Virtual Reality in the Flipped Teaching of Martial Arts Taijiquan Based on Deep Learning and Big Data Analytics

Retracted: A new machine learning approach based on fuzzy data correlation for recognizing sports activities

A new machine learning approach based on spatial fuzzy data correlation for recognizing sports activities

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