Journal of the Korean Institute of Electrical and Electronic Material Engineers (한국전기전자재료학회논문지)

The Korean Institute of Electrical and Electronic Material Engineers (한국전기전자재료학회)
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System Implementation and Algorithm Development for Classification of the Activity States Using 3 Axial Accelerometer

3축 가속도를 이용한 활동상태 분류 시스템 구현 및 알고리즘 개발

  • Noh, Yun-Hong (Graduate School of Ubiquitous IT, Dongseo University) ;
  • Ye, Soo-Young (Department of Medhatronics, Division of Information System Engineering, Dongseo University) ;
  • Jeong, Do-Un (Division of computer and information Engineering, Dongseo University)
  • 노윤홍 (동서대학교 유비쿼터스 IT학과) ;
  • 예수영 (동서대학교 메카트로닉스공학과) ;
  • 정도운 (동서대학교 컴퓨터정보공학부)
  • Received : 2010.10.18
  • Accepted : 2010.12.06
  • Published : 2011.01.01
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Abstract

A real time monitoring system from a PC has been developed which can be accessed through transmitted data, which incorporates an established low powered transport system equipped with a single chip combined with wireless sensor network technology from a three-axis acceleration sensor. In order to distinguish between static posture and dynamic posture, the extracted parameter from the rapidly transmitted data needs differentiation of movement and activity structures and status for an accurate measurement. When results interpret a static formation, statistics referring to each respective formation, known as the K-mean algorithm is utilized to carry out a determination of detailed positioning, and when results alter towards dynamic activity, fuzzy algorithm (fuzzy categorizer), which is the relationship between speed and ISVM, is used to categorize activity levels into 4 stages. Also, the ISVM is calculated with the instrumented acceleration speed on the running machine according to various speeds and its relationship with kinetic energy goes through correlation analysis. With the evaluation of the proposed system, the accuracy level stands at 100% at a static formation and also a 96.79% accuracy with kinetic energy and we can easily determine the energy consumption through the relationship between ISVM and kinetic energy.

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References

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