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4개 관절 기반 인체모션 분석을 위한 특징 추출 및 자세 분류
고경리(Kyeong-Ri Ko),반성범(Sung Bum Pan) 대한전자공학회 2015 전자공학회논문지 Vol.52 No.6
앉아있는 시간이 긴 현대인들에게 바른 자세를 유지하도록 하는 것은 중요하다. 자세 교정을 위한 치료는 많은 시간과 비용이 소요되며, 전문의의 지속적인 관찰이 필요하다. 그러므로 사용자 스스로 자신의 자세를 판단하고 교정하기 위한 시스템이 필요하다. 본 논문에서는 사용자의 자세 데이터를 취득하여 취득된 자세가 정상자세인지 비정상자세인지 판단한다. 사용자의 자세 데이터 취득을 위해 관성 센서를 이용한 4개 관절 기반 모션캡쳐 시스템을 제안한다. 이 시스템을 통해 대상자의 자세데이터를 취득하고, 취득한 데이터를 기반으로 특징을 추출하여 DB를 구축한다. 구축한 DB를 K-means 클러스터링 알고리즘을 이용하여 자세 학습을 수행한 후, 정상자세와 비정상자세를 분류한다. 관절의 회전각도, 위치정보, 분석정보를 이용하여 자세분류를 수행한 결과, 정상자세 판단 성공률은 99.79%로 나타났다. 이 결과로 미루어 4개 관절에 대한 특징을 이용하여 사용자의 자세를 판단 가능하며, 향후 척추질환 예방 시스템에 적용하여 사용자의 자세를 교정하는 데 도움을 줄 수 있을 것으로 판단된다. In the modern age, it is important for people to maintain a good sitting posture because they spend long hours sitting. Posture correction treatment requires a great deal of time and expenses with continuous observation by a specialist. Therefore, there is a need for a system with which users can judge and correct their postures on their own. In this study, we collected users’ postures and judged whether they are normal or abnormal. To obtain a user’s posture, we propose a four-joint motion capture system that uses inertial sensors. The system collects the subject’s postures, and features are extracted from the collected data to build a database. The data in the DB are classified into normal and abnormal postures after posture learning using the K-means clustering algorithm. An experiment was performed to classify the posture from the joints’ rotation angles and positions; the normal posture judgment reached a success rate of 99.79%. This result suggests that the features of the four joints can be used to judge and help correct a user’s posture through application to a spinal disease prevention system in the future.
고경리(Kyeong-Ri Ko),채승훈(Seung-Hoon Chae),배성봉(Seong Bong Bae),최장식(Jang Sik Choi),반성범(Sung Bum Pan) 한국정보기술학회 2014 한국정보기술학회논문지 Vol.12 No.8
Bad posture triggers spinal diseases by forming a twisted or crooked body. Therefore, it is vital for modern people mostly living a sedentary lifestyle to have correct posture. In this paper, we construct a reasonably priced motion capture system requiring less preparation time and measurement space by using small-sized and lightweight micro electro-mechanical systems-based wireless inertial sensors to address the problems with the existing motion capture system. In addition, we have acquired and analyzed 4-joint motion data. The analysis results show that the motion data of four joints acquired through the embodied system can be applied to the self-coaching system, and users can employ the system for spinal disease diagnosis themselves.
셀프-코칭을 위한 관성센서 기반 인체모션 취득 시스템 구현
고경리(Kyeong-Ri Ko),배성봉(Seong Bong Bae),최장식(Jang Sik Choi),반성범(Sung Bum Pan) 한국정보기술학회 2014 한국정보기술학회논문지 Vol.12 No.4
Recently due to the increasing attention paid to personal education, medical welfare, leisure sports and other leisure activities, various self-coaching systems are being developed for education, rehabilitation exercises and sports for self-learning without external help. In this paper, we explain the human motion capturing system for realization of a self-coaching system, and present the results of the captured human motions using this system. The human body model based motion capture system comprises 15 inertial sensors, a 3-channel receiver, a human body model based 3-dimensional simulation program, and a personal computer. We experiments of subjects motion data obtaining using the commercial motion capture system for verification of construction motion capture system. As a result, the expert and user takes action was appear equally on three-dimensional simulation.
고경리(Kyeong-Ri Ko),반성범(Sung Bum Pan) 한국정보기술학회 2018 한국정보기술학회논문지 Vol.16 No.1
As the golfing population increases, there is an increasing need for an analysis system capable of analyzing the users own swing posture. In this paper, we define six main analysis items for constructing golf swing motion analysis system based on inertial sensors. Motion data was acquired for teaching pros and general users using inertial sensors based motion capture system, and analyzed through the proposed system. As a result of general swing motion analysis, the upper body and head movements were larger and the twist angle was lower by 25 degrees than the teaching pros. The swing tempo, which has a large effect on the swing trajectory, was also confirmed to be kept short compared to the expert, and the swing speed was slower. Experts confirmed that the plane of the backswing and the downswing occur on the same plane, whereas the general users plane has fallen away from the impact point and the address point.