Wireless Sensor Network Topology Theory for Data Collection and Analysis of Sports Training Human Body

Beibei, FU

doi:10.1155/2021/9746107

Cited by 4 publications

(2 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is of practical significance and application value to meet the basic needs of table tennis enthusiasts in mass fitness to learn sports skills. On the other hand, by combining computer vision and motion capture technologies, the system can analyze and guide the user's technical movements in a real-time, efficient, and objective manner [30]. To be specific, it can balance the deviations of the gesture guidance evaluation caused by human subjective judgment, which is important for the realization of a digital and scientific auxiliary evaluation system.…”

Section: Introductionmentioning

confidence: 99%

A Table Tennis Motion Correction System Based on Human Motion Feature Recognition

Han

2022

Security and Communication Networks

View full text Add to dashboard Cite

Computer-aided sports systems are an important area of current research. To be specific, it can combine computer vision, computer graphics, and motion capture technologies with the characteristics of sports, and design and develop assisted systems according to user needs. As a result, it is of great practical importance and application to improve the entertainment and science of sports learning, to stimulate public participation in sports, and to learn sports skills. Table tennis has a very great popular base in China and has a wide range of audiences. However, for beginners or amateurs of table tennis, it is difficult to learn table tennis skills by relying on books, videos, etc., due to the lack of professional technical guidance, which makes it relatively difficult for them to continuously improve their skills. Sometimes they tend to form wrong technical habits, which are not easy to detect and correct in time, and can lead to sports injuries over time. Therefore, the lack of professional instruction has hindered the development of table tennis in public fitness to a certain extent. On the other hand, in a table tennis course, the learning of table tennis techniques is mostly dependent on the teacher’s explanation. Students are bored with the repetitive and boring teaching because they need to repeat the exercises several times. The formation of correct table tennis movements requires repeated instruction from the instructor to address problems with the student’s movements. However, due to limited teaching resources, it is difficult for teachers to accommodate different students during the teaching process. In addition, with a limited team of instructors, the level of proficiency varies, making it difficult for them to make an objective assessment. As a result, with the rapid development and application of modern science and technology in the field of sports, there is an urgent need to explore intelligent sports technology instructional support systems to improve the shortcomings of the traditional teaching model. Motion recognition technology, as an essential branch of multimodal interaction technology, has been developing rapidly in recent years. This research focus on designing and implementing a system for recognizing human motion based on skeletal point pose information by combining inertial sensors. This system can collect data from sensors located at the main skeletal points of the human body and transmits them to the host computer through multi-Bluetooth pairing transmission. After that, support vector machines are applied to classify human movements and to recognize general human movements. This system has significant advantages for human movement recognition and classification due to the distinctive technical characteristics of table tennis. The recognition and classification of both players in the video can play an important role in the technical analysis and tactical arrangement of the players. As a result, the table tennis motion correction system based on human motion feature recognition has crucial research significance and application value.

show abstract

Section: Introductionmentioning

confidence: 99%

A Table Tennis Motion Correction System Based on Human Motion Feature Recognition

Han

2022

Security and Communication Networks

View full text Add to dashboard Cite

show abstract

“…The model determines the factors that affect this sports mode according to the current situation of the relevant literature, which provides a reference for the development of sports training programs. Fu [ 19 ] has collected sports training data using wireless sensor technology, and also carried out in-depth research on the collected data. The researcher designed an athlete data collection system according to the needs of sports trainers, which includes data collection terminals and wireless sensors and other technologies.…”

Section: Related Workmentioning

confidence: 99%

Construction of a Public Health-Oriented Sports Training Big Data Analysis Platform

Nie

2022

Journal of Environmental and Public Health

View full text Add to dashboard Cite

Sports health has become a goal pursued by most people, both young and old, which is mainly due to the improvement of people’s living standards and the improvement of economic level. Different groups have great differences in the way of physical exercise for public health. The idea of pursuing physical exercise is better but most ignore the factors that affect exercise. Not only will this have a certain negative impact on body function but it also defeats the purpose of physical exercise. Reasonable physical exercise is more urgently needed. However, for public health physical exercise, reasonable methods are also difficult to obtain. This is mainly due to the large differences in the number of groups and hurdles faced by public health. This study designs a public health-oriented sports training platform based on big data technology. It mainly uses the hollow convolutional neural network (A-CNN) and the GRU method to extract the relationship between physical training and physical function, weather factors, and exercise intensity. The research results show that the A-CNN and GRU methods can better map the relationship between sports training parameters and the three characteristics that affect sports health. This kind of sports training platform based on big data technology can better guide young people or the elderly to carry out reasonable physical exercise. A-CNN and GRU techniques have relatively high accuracy in predicting the three characteristics of physical exercise. The smallest error is only 1.43%, and the largest error is also 2.56%.

show abstract

Investigating and Checking the Javelin Athlete's Movement Parameters Using Smart WSN

P¹,

Sabitha²,

Shirisha

et al. 2023

2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC)

View full text Add to dashboard Cite

Wireless Sensor Network Topology Theory for Data Collection and Analysis of Sports Training Human Body

Cited by 4 publications

References 33 publications

A Table Tennis Motion Correction System Based on Human Motion Feature Recognition

A Table Tennis Motion Correction System Based on Human Motion Feature Recognition

Construction of a Public Health-Oriented Sports Training Big Data Analysis Platform

Investigating and Checking the Javelin Athlete's Movement Parameters Using Smart WSN

Contact Info

Product

Resources

About