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논문 기본 정보

자료유형
학술저널
저자정보
SeungJun Oh (Sangmyung University) Dong Keun Kim (Sangmyung University)
저널정보
한국정보통신학회JICCE Journal of information and communication convergence engineering Journal of information and communication convergence engineering Vol.17 No.1
발행연도
2019.3
수록면
74 - 83 (10page)

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초록· 키워드

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This study designs a squat posture recognition system that can provide correct squat posture guidelines. This system comprises two modules: a Kinect camera for monitoring users’ body movements and a Wii Balance Board(WBB) for measuring balanced postures with legs. Squat posture recognition involves two states: “Stand” and “Squat.” Further, each state is divided into two postures: correct and incorrect. The incorrect postures of the Stand and Squat states were classified into three and two different types of postures, respectively. The factors that determine whether a posture is incorrect or correct include the difference between shoulder width and ankle width, knee angle, and coordinate of center of pressure(CoP). An expert and 10 participants participated in experiments, and the three factors used to determine the posture were measured using both Kinect and WBB. The acquired data from each device show that the expert’s posture is more stable than that of the subjects. This data was classified using a support vector machine (SVM) and naïve Bayes classifier. The classification results showed that the accuracy achieved using the SVM and naïve Bayes classifier was 95.61% and 81.82%, respectively. Therefore, the developed system that used Kinect and WBB could classify correct and incorrect postures with high accuracy. Unlike in other studies, we obtained the spatial coordinates using Kinect and measured the length of the body. The balance of the body was measured using CoP coordinates obtained from the WBB, and meaningful results were obtained from the measured values. Finally, the developed system can help people analyze the squat posture easily and conveniently anywhere and can help present correct squat posture guidelines. By using this system, users can easily analyze the squat posture in daily life and suggest safe and accurate postures.

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Abstract
I. INTRODUCTION
II. RELATED STUDIES
III. SYSTEM MODEL AND METHODS
IV. RESULTS
V. DISCUSSION
VI. CONCLUSIONS
REFERENCES

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