Journal of the Korea Society of Computer and Information (한국컴퓨터정보학회논문지)

Korean Society of Computer Information (한국컴퓨터정보학회)
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Recognition of Basic Motions for Figure Skating using AHRS

AHRS를 이용한 피겨스케이팅 기본 동작 인식

  • Kwon, Ki-Hyeon (Dept. of Electronics, Information & Communication Engineering, Kangwon National University) ;
  • Lee, Hyung-Bong (Dept. of Computer Science & Engineering, Gangneung-Wonju National University)
  • 권기현 (강원대학교 전자정보통신공학부) ;
  • 이형봉 (강릉원주대학교 컴퓨터공학과)
  • Received : 2015.01.06
  • Accepted : 2015.02.14
  • Published : 2015.03.31
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Abstract

IT is widely used for biomechanics and AHRS sensor also be highlighted with small sized characteristics and price competitiveness in the field of motion measurement and analysis of sports. In this paper, we attach the AHRS to the figure skate shoes to measure the motion data like spin, forward/backward, jump, in/out edge and toe movement. In order to reduce the measurement error, we have adopted the sensors equipped with Madgwick complementary filtering and also use Euler angle to quaternion conversion to reduce the Gimbal-lock effect. We test and experiment the accuracy and execution time of the pattern recognition algorithms like PCA, ICA, LDA, SVM to show the recognition possibility of it on the basic motions of figure skating from the 9-axis trajectory information which is gathered from AHRS sensor. From the result, PCA, ICA have low accuracy, but LDA, SVM have good accuracy to use for recognition of basic motions of figure skating.

IT 기술이 생체역학 분야와 폭넓게 접목되고 있으며 AHRS 센서가 스포츠 모션분석 분야에 소형화 및 가격 경쟁력 측면에서 조명을 받고 있다. 본 논문에서는 피겨스케이트화에 소형의 AHRS 센서를 부착하고, 스핀(spin), 점프, 전/후진, 인/아웃 에지, 토(toe) 등의 기본 동작을 AHRS를 통해 측정한다. AHRS 센서의 측정 오차를 줄이기 위해 Madgwick의 상보필터를 적용하였으며, 짐벌락 현상(Gimbal Lock)을 줄이기 위해 쿼터니언(Quaternion)을 이용하였다. 취득한 9축 궤적 정보에 대해 PCA, ICA, LDA, SVM의 패턴인식 알고리즘을 적용하여 인식정확도 및 실행시간을 구하고, 여러 패턴인식 알고리즘 중에서 어떤 알고리즘이 인식정확도 및 실행시간 측면에서 적용이 가능한지 제시한다. 실험결과, PCA, ICA는 인식정확도가 낮아 사용하기에 부적합하며 LDA, SVM은 인식정확도가 우수하여 피겨스케이팅 기본 동작 인식에 사용이 적합함을 보인다.

Keywords

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