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Navigation based Motion Counting Algorithm for a Wearable Smart Device

항법 기반 웨어러블 스마트 디바이스 동작 카운트 알고리즘

  • Park, So Young (Department of Mechanical & Aerospace Engineering, Seoul National University, ASRI) ;
  • Lee, Min Su (Department of Mechanical & Aerospace Engineering, Seoul National University, ASRI) ;
  • Song, Jin Woo (Department of Mechanical & Aerospace Engineering, Seoul National University, ASRI) ;
  • Park, Chan Gook (Department of Mechanical & Aerospace Engineering, Seoul National University, ASRI)
  • 박소영 (서울대학교 기계항공공학부) ;
  • 이민수 (서울대학교 기계항공공학부) ;
  • 송진우 (서울대학교 기계항공공학부) ;
  • 박찬국 (서울대학교 기계항공공학부)
  • Received : 2015.02.15
  • Accepted : 2015.03.15
  • Published : 2015.06.01

Abstract

In this paper, an ARS-EKF based motion counting algorithm for repetitive exercises such as calisthenics is proposed using a smartwatch. Raw sensor signals from accelerometers and gyroscopes are widely used for conventional smartwatch counting algorithms based on pattern recognition. However, generated features from raw data are not intuitive to reflect the movement of motions. The proposed motion counter algorithm is composed of navigation based feature generation and counting with error correction. The candidate features for each activity are velocity and attitude calculated through an ARS-EKF algorithm. In order to select those features which reveal the characteristics of each motion, an exercise frame from the initial sensor frame is introduced. Counting processes are basically based on the zero crossing method, and misdetected counts are eliminated via simple classification algorithms considering the frequency of the counted motions. Experimental results show that the proposed algorithm efficiently and accurately counts the number of exercises.

Keywords

References

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