발간년도 : [2023]
| 논문정보 |
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| 논문명(한글) |
[Vol.18, No.3] OpenCV-based Squat Posture Correction Model |
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| 논문투고자 |
Yeong-Hwi Ahn, Dong-Hyun Kim |
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| 논문내용 |
The pandemic caused by COVID-19 has affected many fields at home and abroad, and many changes have occurred. In particular, the home training market has expanded through e-commerce, and the population training at home has rapidly spread. However, if you exercise alone at home without the help of experts, you are inevitably exposed to the risk of injury, and watching videos online has many limitations. Squat, one of the types of training, has the best exercise effect for lower body exercise and is programmed and operated for therapeutic purposes such as performance improvement and injury prevention. However, due to an unstable posture, damage to the waist and knees may occur and may be a factor threatening health. In this paper, we propose a model that can analyze unstable postures based on OpenCV and MediaPipe to provide comprehensive information on problem-solving and posture correction for injury prevention and feedback on squat posture. The proposed model is based on the standard squat and wide squat, which are routinely applied by beginners to experts. As a result of measuring the accuracy of the squat pose of the proposed model, it showed an accuracy of 97.85%, and as a result of a survey of users, 83.3% of them were satisfied. The proposed model is expected to contribute to health by maintaining the correct posture of squat, one of the exercise types of home training. |
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