The Effects of the Badminton Teaching-Assisted System Using Electromyography and Gyroscope on Learners' Badminton Skills
Saved in:
| Title: | The Effects of the Badminton Teaching-Assisted System Using Electromyography and Gyroscope on Learners' Badminton Skills |
|---|---|
| Language: | English |
| Authors: | Lin, Kuo-Chin (ORCID |
| Source: | IEEE Transactions on Learning Technologies. 2023 16(5):780-789. |
| Availability: | Institute of Electrical and Electronics Engineers, Inc. 445 Hoes Lane, Piscataway, NJ 08854. Tel: 732-981-0060; Web site: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=4620076 |
| Peer Reviewed: | Y |
| Page Count: | 10 |
| Publication Date: | 2023 |
| Document Type: | Journal Articles Reports - Research |
| Descriptors: | Racquet Sports, Skill Development, Psychomotor Skills, Physical Education Teachers, Teaching Methods, Artificial Intelligence, Muscular Strength, Educational Technology |
| DOI: | 10.1109/TLT.2023.3292215 |
| ISSN: | 1939-1382 |
| Abstract: | Swing movements and muscle strength are essential for mastering badminton techniques. Traditionally, students learn badminton through their instructor's physical demonstration, verbal instructions, and small group activities. To enhance students' learning experience and assist badminton instructors more effectively, this study proposes an alternative teaching approach that utilizes a Badminton Teaching-Assisted System (BTAS) to teach swing movements. The system uses a gesture control armband to collect electromyography and gyroscope signals from professional players, which are then used to build a machine learning model based on the back propagation neural network. The model can be used as a scoring tool to assess the correctness of the student's swing movements and muscle strength. A total of 87 students participated in an eleven-week experiment focusing on two fundamental badminton skills: The backhand push and backhand lift. The results demonstrated a significant improvement in the correctness of the muscle strength during swing movements for the experimental group, compared to the control group. The BTAS can help to enhance the effectiveness of badminton instruction, thereby improving students' swing techniques. Future research could expand upon this study to develop more precise artificial intelligence-based sports assistance systems, which would facilitate personalized teaching and learning in physical education. |
| Abstractor: | As Provided |
| Entry Date: | 2023 |
| Accession Number: | EJ1396456 |
| Database: | ERIC |
| Abstract: | Swing movements and muscle strength are essential for mastering badminton techniques. Traditionally, students learn badminton through their instructor's physical demonstration, verbal instructions, and small group activities. To enhance students' learning experience and assist badminton instructors more effectively, this study proposes an alternative teaching approach that utilizes a Badminton Teaching-Assisted System (BTAS) to teach swing movements. The system uses a gesture control armband to collect electromyography and gyroscope signals from professional players, which are then used to build a machine learning model based on the back propagation neural network. The model can be used as a scoring tool to assess the correctness of the student's swing movements and muscle strength. A total of 87 students participated in an eleven-week experiment focusing on two fundamental badminton skills: The backhand push and backhand lift. The results demonstrated a significant improvement in the correctness of the muscle strength during swing movements for the experimental group, compared to the control group. The BTAS can help to enhance the effectiveness of badminton instruction, thereby improving students' swing techniques. Future research could expand upon this study to develop more precise artificial intelligence-based sports assistance systems, which would facilitate personalized teaching and learning in physical education. |
|---|---|
| ISSN: | 1939-1382 |
| DOI: | 10.1109/TLT.2023.3292215 |
