Jump Rope Exercise Assistance Program
Jump rope exercise requires a fast tempo and breathing, which often leads to the problem of users forgetting their jump count during the workout. To address this issue, we propose a jump rope exercise assistance program that recognizes the user’s jump rope motions and analyzes the impact...
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| Format: | Article |
| Language: | English |
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IEEE
2024-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10750546/ |
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| author | Jin-Woong Kim Jae-Woo Shin Seoung-Ho Choi |
| author_facet | Jin-Woong Kim Jae-Woo Shin Seoung-Ho Choi |
| author_sort | Jin-Woong Kim |
| collection | DOAJ |
| description | Jump rope exercise requires a fast tempo and breathing, which often leads to the problem of users forgetting their jump count during the workout. To address this issue, we propose a jump rope exercise assistance program that recognizes the user’s jump rope motions and analyzes the impact of joint coordinates on these motions. The proposed solution extracts frame-by-frame joint coordinate data from jump rope performance videos. It then utilizes artificial intelligence models to recognize jump rope motions and measure the jump count through motion recognition. We employed five machine learning models and two deep learning models to validate the jump rope motion recognition and count measurement. We analyzed the joint coordinates significantly influencing each jump rope motion using SHAP. Furthermore, we used Odds Ratios to analyze the jump rope motion occurrence probability based on joint coordinate values. Through these methods, we confirmed that the proposed solution effectively performs jump rope motion recognition and joint coordinate impact analysis for jump rope motions. |
| format | Article |
| id | doaj-art-d415fe0316674324b157bd6f25d15e9a |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-d415fe0316674324b157bd6f25d15e9a2024-11-20T00:01:14ZengIEEEIEEE Access2169-35362024-01-011216914916916210.1109/ACCESS.2024.349651010750546Jump Rope Exercise Assistance ProgramJin-Woong Kim0https://orcid.org/0009-0001-0707-5908Jae-Woo Shin1https://orcid.org/0000-0003-2986-0058Seoung-Ho Choi2https://orcid.org/0000-0002-7318-095XDepartment of Convergence IT Engineering, Hansung University, Seoul, South KoreaDepartment of IT Business Admiration, Hanshin University, Osan-si, Gyeonggi-do, Republic of KoreaCollege of Liberal Arts, Faculty of Basic Liberal Arts, Hansung University, Seoul, South KoreaJump rope exercise requires a fast tempo and breathing, which often leads to the problem of users forgetting their jump count during the workout. To address this issue, we propose a jump rope exercise assistance program that recognizes the user’s jump rope motions and analyzes the impact of joint coordinates on these motions. The proposed solution extracts frame-by-frame joint coordinate data from jump rope performance videos. It then utilizes artificial intelligence models to recognize jump rope motions and measure the jump count through motion recognition. We employed five machine learning models and two deep learning models to validate the jump rope motion recognition and count measurement. We analyzed the joint coordinates significantly influencing each jump rope motion using SHAP. Furthermore, we used Odds Ratios to analyze the jump rope motion occurrence probability based on joint coordinate values. Through these methods, we confirmed that the proposed solution effectively performs jump rope motion recognition and joint coordinate impact analysis for jump rope motions.https://ieeexplore.ieee.org/document/10750546/Exercise assistance programartificial intelligencejump rope recognitionjump rope factor analysisjump rope odd ratio |
| spellingShingle | Jin-Woong Kim Jae-Woo Shin Seoung-Ho Choi Jump Rope Exercise Assistance Program IEEE Access Exercise assistance program artificial intelligence jump rope recognition jump rope factor analysis jump rope odd ratio |
| title | Jump Rope Exercise Assistance Program |
| title_full | Jump Rope Exercise Assistance Program |
| title_fullStr | Jump Rope Exercise Assistance Program |
| title_full_unstemmed | Jump Rope Exercise Assistance Program |
| title_short | Jump Rope Exercise Assistance Program |
| title_sort | jump rope exercise assistance program |
| topic | Exercise assistance program artificial intelligence jump rope recognition jump rope factor analysis jump rope odd ratio |
| url | https://ieeexplore.ieee.org/document/10750546/ |
| work_keys_str_mv | AT jinwoongkim jumpropeexerciseassistanceprogram AT jaewooshin jumpropeexerciseassistanceprogram AT seounghochoi jumpropeexerciseassistanceprogram |